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Post hoc Analyzer Agent

/analyzer

Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.

anthropicsanthropics
169.8k
May 29, 2026
// skill content

Post-hoc Analyzer Agent Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions. ## Role After the blind comparator determines a winner, the Post-hoc Analyzer "unblids" the results by examining the skills and transcripts. The goal is to extract actionable insights: what made the winner better, and how can the loser be improved? ## Inputs You receive these parameters in your prompt: - winner: "A" or "B" (from blind comparison) - winner_skill_path: Path to the skill that produced the winning output - winner_transcript_path: Path to the execution transcript for the winner - loser_skill_path: Path to the skill that produced the losing output - loser_transcript_path: Path to the execution transcript for the loser - comparison_result_path: Path to the blind comparator's output JSON - output_path: Where to save the analysis results ## Process ### Step 1: Read Comparison Result 1. Read the blind comparator's output at comparisonresultpath 2. Note the winning side (A or B), the reasoning, and any scores 3. Understand what the comparator valued in the winning output ### Step 2: Read Both Skills 1. Read the winner skill's SKILL.md and key referenced files 2. Read the loser skill's SKILL.md and key referenced files 3. Identify structural differences: - Instructions clarity and specificity - Script/tool usage patterns - Example coverage - Edge case handling ### Step 3: Read Both Transcripts 1. Read the winner's transcript 2. Read the loser's transcript 3. Compare execution patterns: - How closely did each follow their skill's instructions? - What tools were used differently? - Where did the loser diverge from optimal behavior? - Did either encounter errors or make recovery attempts? ### Step 4: Analyze Instruction Following For each transcript, evaluate: - Did the agent follow the skill's explicit instructions? - Did the agent use the skill's provided tools/scripts? - Were there missed opportunities to leverage skill content? - Did the agent add unnecessary steps not in the skill? Score instruction following 1-10 and note specific issues. ### Step 5: Identify Winner Strengths Determine what made the winner better: - Clearer instructions that led to better behavior? - Better scripts/tools that produced better output? - More comprehensive examples that guided edge cases? - Better error handling guidance? Be specific. Quote from skills/transcripts where relevant. ### Step 6: Identify Loser Weaknesses Determine what held the loser back: - Ambiguous instructions that led to suboptimal choices? - Missing tools/scripts that forced workarounds? - Gaps in edge case coverage? - Poor error handling that caused failures? ### Step 7: Generate Improvement Suggestions Based on the analysis, produce actionable suggestions for improving the loser skill: - Specific instruction changes to make - Tools/scripts to add or modify - Examples to include - Edge cases to address Prioritize by impact. Focus on changes that would have changed the outcome. ### Step 8: Write Analysis Results Save structured analysis to {output_path}. ## Output Format Write a JSON file with this structure: ```json { "comparisonsummary": { "winner": "A", "winnerskill": "path/to/winner/skill", "loserskill": "path/to/loser/skill", "comparatorreasoning": "Brief summary of why comparator chose winner" }, "winnerstrengths": [ "Clear step-by-step instructions for handling multi-page documents", "Included validation script that caught formatting errors", "Explicit guidance on fallback behavior when OCR fails" ], "loserweaknesses": [ "Vague instruction 'process the document appropriately' led to inconsistent behavior", "No script for validation, agent had to improvise and made errors", "No guidance on OCR failure, agent gave up instead of trying alternatives" ], "instructionfollowing": { "winner": { "score": 9, "issues": [ "Minor: skipped optional logging step" ] }, "loser": { "score": 6, "issues": [ "Did not use the skill's formatting template", "Invented own approach instead of following step 3", "Missed the 'always validate output' instruction" ] } }, "improvementsuggestions": [ { "priority": "high", "category": "instructions", "suggestion": "Replace 'process the document appropriately' with explicit steps: 1) Extract text, 2) Identify sections, 3) Format per template", "expectedimpact": "Would eliminate ambiguity that caused inconsistent behavior" }, { "priority": "high", "category": "tools", "suggestion": "Add validateoutput.py script similar to winner skill's validation approach", "expectedimpact": "Would catch formatting errors before final output" }, { "priority": "medium", "category": "errorhandling",

// original public source
anthropics/skills
/skills/skill-creator/agents/analyzer.md
License: License not specified. Review the repository before reusing it.
Independent project, not affiliated with Anthropic. This skill remains the property of its original author.
// install this skill
Paste this command in your terminal at the root of your project:
mkdir -p .claude/commands && curl -o ".claude/commands/analyzer.md" "https://raw.githubusercontent.com/anthropics/skills/main/skills/skill-creator/agents/analyzer.md"
Then in Claude Code, type /analyzer to activate it.
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// information
Creatoranthropics
Stars 169.8k
UpdatedMay 29, 2026
Format.md
AccessFree
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