AI Output Failure Triage#
Overview#
AI Output Failure Triage helps a user analyze an unsatisfactory AI-generated answer before trying again. It separates the original goal, prompt, model output, likely failure causes, missing context, and verification needs, then produces a clearer retry prompt and a recommendation about whether to retry, switch approach, gather more inputs, or handle the work manually.
This is a prompt-only diagnostic skill. It does not claim that the next AI answer will be correct. It helps improve task framing and verification discipline.
When to Use#
Use this skill when the user asks for help with:
- A response from an AI tool that was wrong, shallow, unsafe, off-tone, incomplete, or not useful
- Debugging a prompt that produced a bad result
- Rewriting a prompt so the next attempt is clearer
- Creating acceptance checks for an AI-generated answer
- Deciding whether an AI task should be retried, escalated, researched, or done manually
Trigger phrases: "Why did this AI answer fail?", "Fix my prompt", "The AI gave me a bad response", "Make this retry safer", "How should I ask again?", "Triage this output"
Ask for only what is needed, and avoid requesting confidential information. Useful inputs include:
- Original goal or job-to-be-done
- Original prompt or instruction
- AI output that failed
- What was wrong with the output
- Audience, stakes, format, deadline, constraints, and known facts
- Any source material that can be safely shared
- Whether the domain is factual, medical, legal, financial, safety-critical, or high-stakes
If the user cannot provide the original prompt or output, proceed with a partial triage and clearly mark assumptions.
Workflow#
Step 1 - Capture the Original Goal, Prompt, and Output#
Create a compact record of:
- User's intended outcome
- Original prompt or instruction
- AI output or summarized failure
- The gap between expected and actual result
- Any stated constraints, audience, or required format
If any item is missing, label it as "unknown" instead of inventing it.
Step 2 - Classify the Failure Reason#
Classify the failure into one or more likely categories:
- Goal ambiguity: the request did not define success clearly
- Missing context: key facts, source material, audience, or constraints were absent
- Output format mismatch: the answer did not follow the requested structure
- Reasoning gap: the answer skipped steps, made unsupported leaps, or failed to compare options
- Verification gap: factual claims, citations, calculations, or assumptions were not checked
- Tone or audience mismatch: style was wrong for the intended reader
- Safety or privacy issue: the answer requested or exposed sensitive data, or crossed a risk boundary
- Capability mismatch: the task needed tools, live data, domain expertise, or human judgment
Briefly explain the top two or three causes with evidence from the prompt/output.
Step 3 - Identify Missing Context#
Build a missing context checklist. Include only items that materially affect the next attempt:
- Required inputs or source documents
- Definitions of success and failure
- Audience and decision-maker
- Constraints, exclusions, and non-goals
- Preferred tone, length, and format
- Examples of acceptable or unacceptable output
- Verification method, references, or authoritative sources
- Confidential details that should be redacted or summarized instead of shared
Mark each item as "needed now", "helpful later", or "not required".
Step 4 - Rewrite the Task Framing#
Rewrite the task into a clearer structure:
- Role: what perspective the AI should take
- Objective: the concrete outcome
- Inputs: what material the AI may use
- Constraints: boundaries, exclusions, and assumptions
- Output format: exact sections, length, and style
- Verification: checks the answer must perform before finalizing
- Uncertainty behavior: how to label unknowns or ask follow-up questions
Keep the rewrite concise enough for practical reuse.
Step 5 - Add an Acceptance Test#
Create acceptance criteria that the next answer must satisfy. Include:
- Must-have content
- Must-not-do constraints
- Format requirements
- Evidence or verification requirements
- Edge cases or failure modes to watch for
For high-stakes topics, require independent verification and do not treat the AI response as authoritative.
Step 6 - Recommend Retry, Switch, Gather, or Manual Handling#
Make a go/no-go recommendation:
- Retry with improved prompt: if the issue was mainly framing or missing format guidance
- Gather more context first: if key facts or source material are missing
- Switch tool/model/workflow: if the task needs browsing, calculation, coding, file processing, or stronger reasoning
- Ask a human expert: if domain risk is high or consequences are significant
- Handle manually: if the task requires judgment, accountability, confidential access, or direct stakeholder communication
Explain the recommendation in one or two sentences.
Step 7 - Produce the Reusable Next Prompt and Diagnosis Summary#
Deliver a final triage report with:
- Diagnosis summary
- Missing context checklist
- Improved task framing
- Acceptance test
- Safer retry prompt
- Go/no-go recommendation
- Verification notes and cautions
Return the report in this structure:
markdown
# AI Output Failure Triage Report
## 1. Original Task Snapshot
- Goal:
- Original prompt:
- Failed output summary:
- What went wrong:
## 2. Likely Failure Causes
- Primary cause:
- Secondary causes:
- Evidence:
## 3. Missing Context Checklist
- Needed now:
- Helpful later:
- Not required:
## 4. Improved Task Framing
- Role:
- Objective:
- Inputs:
- Constraints:
- Output format:
- Verification:
- Uncertainty behavior:
## 5. Acceptance Test
- The next output must:
- The next output must not:
- Verification required:
## 6. Safer Retry Prompt
[Reusable prompt]
## 7. Go/No-Go Recommendation
- Recommendation:
- Rationale:
- Next action:
Safety Boundaries#
- Do not claim the next AI answer will be correct.
- Require verification for factual, medical, legal, financial, safety-critical, or otherwise high-stakes outputs.
- Do not encourage users to paste secrets, credentials, private records, confidential business data, or sensitive personal information into an AI tool.
- Encourage redaction, summarization, or local processing for sensitive context.
- Do not help create deceptive, manipulative, or harmful prompts.
- If the failed output involves professional advice, frame the result as preparation for review by a qualified person, not a substitute for that person.
Example Prompts#
- "The AI gave me a detailed answer about a historical event but it has three factual errors and I'm not sure how to fix my prompt. Triage this output and give me a safer retry prompt."
- "I asked for a project plan but got back a vague, unhelpful response that skipped the timeline and resource estimates I needed. Help me debug what went wrong and rewrite the prompt."
- "An AI tool generated a financial summary for my client presentation but it made unsupported claims and used the wrong tone. Create a failure triage report with acceptance checks before I retry."
Acceptance Criteria#
- The report captures the original goal, prompt, failed output, and observed gap when available.
- The report classifies likely failure causes using evidence rather than blame or guesswork.
- Missing context is listed and prioritized.
- The retry prompt includes role, objective, inputs, constraints, output format, verification, and uncertainty behavior.
- An acceptance test is included.
- A go/no-go recommendation is explicit.
- High-stakes or sensitive tasks include verification and privacy cautions.
- The skill remains prompt-only and requires no API, network access, credentials, or executable code.