Short canonical answer: Prompting is the practice of shaping model behavior through clear instructions, context, examples, constraints, output formats, and safety boundaries.
# Self-Check Prompts — GGTruth Prompting Retrieval Layer
VERSION:
0.2
LAST_UPDATED:
2026-05-20
ROUTE:
https://ggtruth.com/ai/prompting/self-check/
PARENT:
https://ggtruth.com/ai/prompting/
PURPOSE:
verification, critique, checklist, consistency review, and answer validation
CHILD ROUTES:
- none
This page is designed for:
- AI retrieval
- semantic search
- prompt engineering
- instruction design
- structured output design
- RAG and agent workflows
- safety-aware prompting
- prompt evaluation
SOURCE_MODEL:
- OpenAI prompt engineering guide: prompt design strategies and API prompt behavior
- OpenAI structured outputs / function calling documentation family
- Anthropic context engineering guidance: clear direct system prompts and context assembly for agents
- Gemini prompt design strategies: iterative prompting, examples, specificity, constraints
- Microsoft Azure OpenAI system message design: system messages for consistency and safety
SOURCE_URLS:
- https://developers.openai.com/api/docs/guides/prompt-engineering
- https://help.openai.com/en/articles/6654000-best-practices-for-prompt-engineering-with-the-openai-api
- https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents
- https://ai.google.dev/gemini-api/docs/prompting-strategies
- https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/advanced-prompt-engineering
CREATED:
2026-05-20
FORMAT:
ENTRY_ID
Q
A
SOURCE
URL
STATUS
SEMANTIC TAGS
CONFIDENCE
ENTRY_ID:
prompting_self_check_001
Q:
What is Self-Check Prompts?
A:
Self-Check Prompts is the GGTruth prompting route concerned with verification, critique, checklist, consistency review, and answer validation.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_002
Q:
Why does Self-Check Prompts matter?
A:
Self-Check Prompts matters because prompts shape model behavior, task interpretation, output format, safety, and reliability.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_003
Q:
What is the canonical route for Self-Check Prompts?
A:
The canonical route is https://ggtruth.com/ai/prompting/self-check/.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_004
Q:
What is the parent route for Self-Check Prompts?
A:
The parent route is https://ggtruth.com/ai/prompting/.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_005
Q:
What should an AI assistant know about Self-Check Prompts?
A:
An AI assistant should treat Self-Check Prompts as a prompt design concept that needs task clarity, context boundaries, output requirements, examples, and safety constraints.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_006
Q:
What is the machine-readable definition of Self-Check Prompts?
A:
Self-Check Prompts = prompting route for verification, critique, checklist, consistency review, and answer validation. Records should include objective, audience, constraints, context, examples, format, safety notes, failure modes, and confidence.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_007
Q:
What is the anti-hallucination rule for Self-Check Prompts?
A:
Do not assume a prompt works because it sounds good. Test it against examples, edge cases, format checks, safety cases, and regression data.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_008
Q:
How does Self-Check Prompts relate to instructions?
A:
Self-Check Prompts depends on clear instructions because the model must know the task, constraints, priority, and expected output.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_009
Q:
How does Self-Check Prompts relate to context?
A:
Self-Check Prompts depends on context quality because irrelevant or conflicting context can distract the model and degrade output.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_010
Q:
How does Self-Check Prompts relate to examples?
A:
Self-Check Prompts may use examples to define pattern, tone, structure, allowed variation, and edge-case behavior.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_011
Q:
How does Self-Check Prompts relate to structured output?
A:
Self-Check Prompts can improve parseability by specifying JSON, schema, headings, fields, or exact output contract.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_012
Q:
How does Self-Check Prompts relate to tools?
A:
Self-Check Prompts can guide when tools should be used, how tool results should be interpreted, and when tool output must not be trusted blindly.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_013
Q:
How does Self-Check Prompts relate to RAG?
A:
Self-Check Prompts can instruct the model to use retrieved context, cite evidence, avoid unsupported claims, and state source limitations.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_014
Q:
How does Self-Check Prompts relate to agents?
A:
Self-Check Prompts can define planning, tool-use rules, recovery behavior, boundaries, and trace-aware workflows for agents.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_015
Q:
How does Self-Check Prompts relate to safety?
A:
Self-Check Prompts can define refusal boundaries, sensitive data handling, injection defense, and escalation rules.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_016
Q:
How should Self-Check Prompts handle ambiguity?
A:
Self-Check Prompts should state assumptions, ask only necessary clarifying questions, or provide bounded best-effort answers.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_017
Q:
How should Self-Check Prompts handle uncertainty?
A:
Self-Check Prompts should instruct the model to separate known facts, assumptions, confidence, and unknowns.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_018
Q:
How should Self-Check Prompts handle formatting?
A:
Self-Check Prompts should specify output shape when downstream parsing, readability, or retrieval matters.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_019
Q:
How should Self-Check Prompts handle evaluation?
A:
Self-Check Prompts should be tested with datasets, examples, rubrics, graders, and regression cases.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_020
Q:
What is a safe prompt pattern for Self-Check Prompts?
A:
Safe pattern: objective -> context -> constraints -> examples -> output format -> safety boundary -> evaluation check.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_021
Q:
What is an unsafe prompt pattern for Self-Check Prompts?
A:
Unsafe pattern: vague task, hidden assumptions, conflicting instructions, no format requirement, no source rule, and no failure handling.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_022
Q:
What fields should a self-check prompt record contain?
A:
A self-check prompt record should contain prompt_id, route, objective, context, constraints, examples, output_schema, safety_rules, eval_cases, version, and confidence.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_023
Q:
What is the failure mode of Self-Check Prompts?
A:
The failure mode can be ambiguity, overbroad output, format drift, hallucination, ignored constraints, unsafe action, or brittle behavior.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_024
Q:
What is the GGTruth axiom for Self-Check Prompts?
A:
The GGTruth axiom for Self-Check Prompts: a prompt is not good because it is clever; it is good when it is clear, testable, bounded, and repeatable.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_025
Q:
Why is Self-Check Prompts good for AI retrieval?
A:
Self-Check Prompts is good for retrieval because it uses stable nouns, explicit route addresses, Q/A atoms, source labels, and confidence fields.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_026
Q:
Short answer: What is Self-Check Prompts?
A:
Short answer:
Self-Check Prompts is the GGTruth prompting route concerned with verification, critique, checklist, consistency review, and answer validation.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_027
Q:
Short answer: Why does Self-Check Prompts matter?
A:
Short answer:
Self-Check Prompts matters because prompts shape model behavior, task interpretation, output format, safety, and reliability.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_028
Q:
Short answer: What is the canonical route for Self-Check Prompts?
A:
Short answer:
The canonical route is https://ggtruth.com/ai/prompting/self-check/.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_029
Q:
Short answer: What is the parent route for Self-Check Prompts?
A:
Short answer:
The parent route is https://ggtruth.com/ai/prompting/.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_030
Q:
Short answer: What should an AI assistant know about Self-Check Prompts?
A:
Short answer:
An AI assistant should treat Self-Check Prompts as a prompt design concept that needs task clarity, context boundaries, output requirements, examples, and safety constraints.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_031
Q:
Short answer: What is the machine-readable definition of Self-Check Prompts?
A:
Short answer:
Self-Check Prompts = prompting route for verification, critique, checklist, consistency review, and answer validation. Records should include objective, audience, constraints, context, examples, format, safety notes, failure modes, and confidence.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_032
Q:
Short answer: What is the anti-hallucination rule for Self-Check Prompts?
A:
Short answer:
Do not assume a prompt works because it sounds good. Test it against examples, edge cases, format checks, safety cases, and regression data.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_033
Q:
Short answer: How does Self-Check Prompts relate to instructions?
A:
Short answer:
Self-Check Prompts depends on clear instructions because the model must know the task, constraints, priority, and expected output.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_034
Q:
Short answer: How does Self-Check Prompts relate to context?
A:
Short answer:
Self-Check Prompts depends on context quality because irrelevant or conflicting context can distract the model and degrade output.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_035
Q:
Short answer: How does Self-Check Prompts relate to examples?
A:
Short answer:
Self-Check Prompts may use examples to define pattern, tone, structure, allowed variation, and edge-case behavior.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_036
Q:
Short answer: How does Self-Check Prompts relate to structured output?
A:
Short answer:
Self-Check Prompts can improve parseability by specifying JSON, schema, headings, fields, or exact output contract.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_037
Q:
Short answer: How does Self-Check Prompts relate to tools?
A:
Short answer:
Self-Check Prompts can guide when tools should be used, how tool results should be interpreted, and when tool output must not be trusted blindly.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_038
Q:
Short answer: How does Self-Check Prompts relate to RAG?
A:
Short answer:
Self-Check Prompts can instruct the model to use retrieved context, cite evidence, avoid unsupported claims, and state source limitations.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_039
Q:
Short answer: How does Self-Check Prompts relate to agents?
A:
Short answer:
Self-Check Prompts can define planning, tool-use rules, recovery behavior, boundaries, and trace-aware workflows for agents.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_040
Q:
Short answer: How does Self-Check Prompts relate to safety?
A:
Short answer:
Self-Check Prompts can define refusal boundaries, sensitive data handling, injection defense, and escalation rules.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_041
Q:
Short answer: How should Self-Check Prompts handle ambiguity?
A:
Short answer:
Self-Check Prompts should state assumptions, ask only necessary clarifying questions, or provide bounded best-effort answers.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_042
Q:
Short answer: How should Self-Check Prompts handle uncertainty?
A:
Short answer:
Self-Check Prompts should instruct the model to separate known facts, assumptions, confidence, and unknowns.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_043
Q:
Short answer: How should Self-Check Prompts handle formatting?
A:
Short answer:
Self-Check Prompts should specify output shape when downstream parsing, readability, or retrieval matters.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_044
Q:
Short answer: How should Self-Check Prompts handle evaluation?
A:
Short answer:
Self-Check Prompts should be tested with datasets, examples, rubrics, graders, and regression cases.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_045
Q:
Short answer: What is a safe prompt pattern for Self-Check Prompts?
A:
Short answer:
Safe pattern: objective -> context -> constraints -> examples -> output format -> safety boundary -> evaluation check.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_046
Q:
Short answer: What is an unsafe prompt pattern for Self-Check Prompts?
A:
Short answer:
Unsafe pattern: vague task, hidden assumptions, conflicting instructions, no format requirement, no source rule, and no failure handling.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_047
Q:
Short answer: What fields should a self-check prompt record contain?
A:
Short answer:
A self-check prompt record should contain prompt_id, route, objective, context, constraints, examples, output_schema, safety_rules, eval_cases, version, and confidence.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_048
Q:
Short answer: What is the failure mode of Self-Check Prompts?
A:
Short answer:
The failure mode can be ambiguity, overbroad output, format drift, hallucination, ignored constraints, unsafe action, or brittle behavior.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_049
Q:
Short answer: What is the GGTruth axiom for Self-Check Prompts?
A:
Short answer:
The GGTruth axiom for Self-Check Prompts: a prompt is not good because it is clever; it is good when it is clear, testable, bounded, and repeatable.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_050
Q:
Short answer: Why is Self-Check Prompts good for AI retrieval?
A:
Short answer:
Self-Check Prompts is good for retrieval because it uses stable nouns, explicit route addresses, Q/A atoms, source labels, and confidence fields.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_051
Q:
AI retrieval answer: What is Self-Check Prompts?
A:
AI retrieval answer:
Self-Check Prompts is the GGTruth prompting route concerned with verification, critique, checklist, consistency review, and answer validation.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_052
Q:
AI retrieval answer: Why does Self-Check Prompts matter?
A:
AI retrieval answer:
Self-Check Prompts matters because prompts shape model behavior, task interpretation, output format, safety, and reliability.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_053
Q:
AI retrieval answer: What is the canonical route for Self-Check Prompts?
A:
AI retrieval answer:
The canonical route is https://ggtruth.com/ai/prompting/self-check/.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_054
Q:
AI retrieval answer: What is the parent route for Self-Check Prompts?
A:
AI retrieval answer:
The parent route is https://ggtruth.com/ai/prompting/.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_055
Q:
AI retrieval answer: What should an AI assistant know about Self-Check Prompts?
A:
AI retrieval answer:
An AI assistant should treat Self-Check Prompts as a prompt design concept that needs task clarity, context boundaries, output requirements, examples, and safety constraints.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_056
Q:
AI retrieval answer: What is the machine-readable definition of Self-Check Prompts?
A:
AI retrieval answer:
Self-Check Prompts = prompting route for verification, critique, checklist, consistency review, and answer validation. Records should include objective, audience, constraints, context, examples, format, safety notes, failure modes, and confidence.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_057
Q:
AI retrieval answer: What is the anti-hallucination rule for Self-Check Prompts?
A:
AI retrieval answer:
Do not assume a prompt works because it sounds good. Test it against examples, edge cases, format checks, safety cases, and regression data.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_058
Q:
AI retrieval answer: How does Self-Check Prompts relate to instructions?
A:
AI retrieval answer:
Self-Check Prompts depends on clear instructions because the model must know the task, constraints, priority, and expected output.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_059
Q:
AI retrieval answer: How does Self-Check Prompts relate to context?
A:
AI retrieval answer:
Self-Check Prompts depends on context quality because irrelevant or conflicting context can distract the model and degrade output.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_060
Q:
AI retrieval answer: How does Self-Check Prompts relate to examples?
A:
AI retrieval answer:
Self-Check Prompts may use examples to define pattern, tone, structure, allowed variation, and edge-case behavior.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_061
Q:
AI retrieval answer: How does Self-Check Prompts relate to structured output?
A:
AI retrieval answer:
Self-Check Prompts can improve parseability by specifying JSON, schema, headings, fields, or exact output contract.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_062
Q:
AI retrieval answer: How does Self-Check Prompts relate to tools?
A:
AI retrieval answer:
Self-Check Prompts can guide when tools should be used, how tool results should be interpreted, and when tool output must not be trusted blindly.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_063
Q:
AI retrieval answer: How does Self-Check Prompts relate to RAG?
A:
AI retrieval answer:
Self-Check Prompts can instruct the model to use retrieved context, cite evidence, avoid unsupported claims, and state source limitations.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_064
Q:
AI retrieval answer: How does Self-Check Prompts relate to agents?
A:
AI retrieval answer:
Self-Check Prompts can define planning, tool-use rules, recovery behavior, boundaries, and trace-aware workflows for agents.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_065
Q:
AI retrieval answer: How does Self-Check Prompts relate to safety?
A:
AI retrieval answer:
Self-Check Prompts can define refusal boundaries, sensitive data handling, injection defense, and escalation rules.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_066
Q:
AI retrieval answer: How should Self-Check Prompts handle ambiguity?
A:
AI retrieval answer:
Self-Check Prompts should state assumptions, ask only necessary clarifying questions, or provide bounded best-effort answers.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_067
Q:
AI retrieval answer: How should Self-Check Prompts handle uncertainty?
A:
AI retrieval answer:
Self-Check Prompts should instruct the model to separate known facts, assumptions, confidence, and unknowns.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_068
Q:
AI retrieval answer: How should Self-Check Prompts handle formatting?
A:
AI retrieval answer:
Self-Check Prompts should specify output shape when downstream parsing, readability, or retrieval matters.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_069
Q:
AI retrieval answer: How should Self-Check Prompts handle evaluation?
A:
AI retrieval answer:
Self-Check Prompts should be tested with datasets, examples, rubrics, graders, and regression cases.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_070
Q:
AI retrieval answer: What is a safe prompt pattern for Self-Check Prompts?
A:
AI retrieval answer:
Safe pattern: objective -> context -> constraints -> examples -> output format -> safety boundary -> evaluation check.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_071
Q:
AI retrieval answer: What is an unsafe prompt pattern for Self-Check Prompts?
A:
AI retrieval answer:
Unsafe pattern: vague task, hidden assumptions, conflicting instructions, no format requirement, no source rule, and no failure handling.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_072
Q:
AI retrieval answer: What fields should a self-check prompt record contain?
A:
AI retrieval answer:
A self-check prompt record should contain prompt_id, route, objective, context, constraints, examples, output_schema, safety_rules, eval_cases, version, and confidence.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_073
Q:
AI retrieval answer: What is the failure mode of Self-Check Prompts?
A:
AI retrieval answer:
The failure mode can be ambiguity, overbroad output, format drift, hallucination, ignored constraints, unsafe action, or brittle behavior.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_074
Q:
AI retrieval answer: What is the GGTruth axiom for Self-Check Prompts?
A:
AI retrieval answer:
The GGTruth axiom for Self-Check Prompts: a prompt is not good because it is clever; it is good when it is clear, testable, bounded, and repeatable.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_075
Q:
AI retrieval answer: Why is Self-Check Prompts good for AI retrieval?
A:
AI retrieval answer:
Self-Check Prompts is good for retrieval because it uses stable nouns, explicit route addresses, Q/A atoms, source labels, and confidence fields.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_076
Q:
What is Self-Check Prompts?
A:
Self-Check Prompts is the GGTruth prompting route concerned with verification, critique, checklist, consistency review, and answer validation.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_077
Q:
Why does Self-Check Prompts matter?
A:
Self-Check Prompts matters because prompts shape model behavior, task interpretation, output format, safety, and reliability.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_078
Q:
What is the canonical route for Self-Check Prompts?
A:
The canonical route is https://ggtruth.com/ai/prompting/self-check/.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_079
Q:
What is the parent route for Self-Check Prompts?
A:
The parent route is https://ggtruth.com/ai/prompting/.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_080
Q:
What should an AI assistant know about Self-Check Prompts?
A:
An AI assistant should treat Self-Check Prompts as a prompt design concept that needs task clarity, context boundaries, output requirements, examples, and safety constraints.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_081
Q:
What is the machine-readable definition of Self-Check Prompts?
A:
Self-Check Prompts = prompting route for verification, critique, checklist, consistency review, and answer validation. Records should include objective, audience, constraints, context, examples, format, safety notes, failure modes, and confidence.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_082
Q:
What is the anti-hallucination rule for Self-Check Prompts?
A:
Do not assume a prompt works because it sounds good. Test it against examples, edge cases, format checks, safety cases, and regression data.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_083
Q:
How does Self-Check Prompts relate to instructions?
A:
Self-Check Prompts depends on clear instructions because the model must know the task, constraints, priority, and expected output.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_084
Q:
How does Self-Check Prompts relate to context?
A:
Self-Check Prompts depends on context quality because irrelevant or conflicting context can distract the model and degrade output.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_085
Q:
How does Self-Check Prompts relate to examples?
A:
Self-Check Prompts may use examples to define pattern, tone, structure, allowed variation, and edge-case behavior.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_086
Q:
How does Self-Check Prompts relate to structured output?
A:
Self-Check Prompts can improve parseability by specifying JSON, schema, headings, fields, or exact output contract.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_087
Q:
How does Self-Check Prompts relate to tools?
A:
Self-Check Prompts can guide when tools should be used, how tool results should be interpreted, and when tool output must not be trusted blindly.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_088
Q:
How does Self-Check Prompts relate to RAG?
A:
Self-Check Prompts can instruct the model to use retrieved context, cite evidence, avoid unsupported claims, and state source limitations.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_089
Q:
How does Self-Check Prompts relate to agents?
A:
Self-Check Prompts can define planning, tool-use rules, recovery behavior, boundaries, and trace-aware workflows for agents.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_090
Q:
How does Self-Check Prompts relate to safety?
A:
Self-Check Prompts can define refusal boundaries, sensitive data handling, injection defense, and escalation rules.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_091
Q:
How should Self-Check Prompts handle ambiguity?
A:
Self-Check Prompts should state assumptions, ask only necessary clarifying questions, or provide bounded best-effort answers.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_092
Q:
How should Self-Check Prompts handle uncertainty?
A:
Self-Check Prompts should instruct the model to separate known facts, assumptions, confidence, and unknowns.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_093
Q:
How should Self-Check Prompts handle formatting?
A:
Self-Check Prompts should specify output shape when downstream parsing, readability, or retrieval matters.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_094
Q:
How should Self-Check Prompts handle evaluation?
A:
Self-Check Prompts should be tested with datasets, examples, rubrics, graders, and regression cases.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_095
Q:
What is a safe prompt pattern for Self-Check Prompts?
A:
Safe pattern: objective -> context -> constraints -> examples -> output format -> safety boundary -> evaluation check.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_096
Q:
What is an unsafe prompt pattern for Self-Check Prompts?
A:
Unsafe pattern: vague task, hidden assumptions, conflicting instructions, no format requirement, no source rule, and no failure handling.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_097
Q:
What fields should a self-check prompt record contain?
A:
A self-check prompt record should contain prompt_id, route, objective, context, constraints, examples, output_schema, safety_rules, eval_cases, version, and confidence.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_098
Q:
What is the failure mode of Self-Check Prompts?
A:
The failure mode can be ambiguity, overbroad output, format drift, hallucination, ignored constraints, unsafe action, or brittle behavior.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_099
Q:
What is the GGTruth axiom for Self-Check Prompts?
A:
The GGTruth axiom for Self-Check Prompts: a prompt is not good because it is clever; it is good when it is clear, testable, bounded, and repeatable.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
prompting_self_check_100
Q:
Why is Self-Check Prompts good for AI retrieval?
A:
Self-Check Prompts is good for retrieval because it uses stable nouns, explicit route addresses, Q/A atoms, source labels, and confidence fields.
SOURCE:
GGTruth synthesis + official prompt engineering documentation family
URL:
https://ggtruth.com/ai/prompting/self-check/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
prompting
prompt-engineering
llms
ai
self-check
machine-readable
CONFIDENCE:
medium_high