ros/claude-plugins-official
1
0
Fork 0
mirror of https://github.com/anthropics/claude-plugins-official.git synced 2026-03-19 11:13:08 +00:00
Code Issues Packages Projects Releases Wiki Activity
Files
987d0f4b2edc83732c950f19946583d0d7ea483f
claude-plugins-official/plugins/skill-creator/skills/skill-creator/references/schemas.md
Kenshiro Nakagawa e05013d229 chore(skill-creator): update to latest skill-creator
2026-02-24 17:14:53 -08:00

12 KiB
Raw Blame History

JSON Schemas

This document defines the JSON schemas used by skill-creator.

evals.json

Defines the evals for a skill. Located at evals/evals.json within the skill directory.

{
  "skill_name": "example-skill",
  "evals": [
    {
      "id": 1,
      "prompt": "User's example prompt",
      "expected_output": "Description of expected result",
      "files": ["evals/files/sample1.pdf"],
      "expectations": [
        "The output includes X",
        "The skill used script Y"
      ]
    }
  ]
}

Fields:

  • skill_name: Name matching the skill's frontmatter
  • evals[].id: Unique integer identifier
  • evals[].prompt: The task to execute
  • evals[].expected_output: Human-readable description of success
  • evals[].files: Optional list of input file paths (relative to skill root)
  • evals[].expectations: List of verifiable statements

history.json

Tracks version progression in Improve mode. Located at workspace root.

{
  "started_at": "2026-01-15T10:30:00Z",
  "skill_name": "pdf",
  "current_best": "v2",
  "iterations": [
    {
      "version": "v0",
      "parent": null,
      "expectation_pass_rate": 0.65,
      "grading_result": "baseline",
      "is_current_best": false
    },
    {
      "version": "v1",
      "parent": "v0",
      "expectation_pass_rate": 0.75,
      "grading_result": "won",
      "is_current_best": false
    },
    {
      "version": "v2",
      "parent": "v1",
      "expectation_pass_rate": 0.85,
      "grading_result": "won",
      "is_current_best": true
    }
  ]
}

Fields:

  • started_at: ISO timestamp of when improvement started
  • skill_name: Name of the skill being improved
  • current_best: Version identifier of the best performer
  • iterations[].version: Version identifier (v0, v1, ...)
  • iterations[].parent: Parent version this was derived from
  • iterations[].expectation_pass_rate: Pass rate from grading
  • iterations[].grading_result: "baseline", "won", "lost", or "tie"
  • iterations[].is_current_best: Whether this is the current best version

grading.json

Output from the grader agent. Located at <run-dir>/grading.json.

{
  "expectations": [
    {
      "text": "The output includes the name 'John Smith'",
      "passed": true,
      "evidence": "Found in transcript Step 3: 'Extracted names: John Smith, Sarah Johnson'"
    },
    {
      "text": "The spreadsheet has a SUM formula in cell B10",
      "passed": false,
      "evidence": "No spreadsheet was created. The output was a text file."
    }
  ],
  "summary": {
    "passed": 2,
    "failed": 1,
    "total": 3,
    "pass_rate": 0.67
  },
  "execution_metrics": {
    "tool_calls": {
      "Read": 5,
      "Write": 2,
      "Bash": 8
    },
    "total_tool_calls": 15,
    "total_steps": 6,
    "errors_encountered": 0,
    "output_chars": 12450,
    "transcript_chars": 3200
  },
  "timing": {
    "executor_duration_seconds": 165.0,
    "grader_duration_seconds": 26.0,
    "total_duration_seconds": 191.0
  },
  "claims": [
    {
      "claim": "The form has 12 fillable fields",
      "type": "factual",
      "verified": true,
      "evidence": "Counted 12 fields in field_info.json"
    }
  ],
  "user_notes_summary": {
    "uncertainties": ["Used 2023 data, may be stale"],
    "needs_review": [],
    "workarounds": ["Fell back to text overlay for non-fillable fields"]
  },
  "eval_feedback": {
    "suggestions": [
      {
        "assertion": "The output includes the name 'John Smith'",
        "reason": "A hallucinated document that mentions the name would also pass"
      }
    ],
    "overall": "Assertions check presence but not correctness."
  }
}

Fields:

  • expectations[]: Graded expectations with evidence
  • summary: Aggregate pass/fail counts
  • execution_metrics: Tool usage and output size (from executor's metrics.json)
  • timing: Wall clock timing (from timing.json)
  • claims: Extracted and verified claims from the output
  • user_notes_summary: Issues flagged by the executor
  • eval_feedback: (optional) Improvement suggestions for the evals, only present when the grader identifies issues worth raising

metrics.json

Output from the executor agent. Located at <run-dir>/outputs/metrics.json.

{
  "tool_calls": {
    "Read": 5,
    "Write": 2,
    "Bash": 8,
    "Edit": 1,
    "Glob": 2,
    "Grep": 0
  },
  "total_tool_calls": 18,
  "total_steps": 6,
  "files_created": ["filled_form.pdf", "field_values.json"],
  "errors_encountered": 0,
  "output_chars": 12450,
  "transcript_chars": 3200
}

Fields:

  • tool_calls: Count per tool type
  • total_tool_calls: Sum of all tool calls
  • total_steps: Number of major execution steps
  • files_created: List of output files created
  • errors_encountered: Number of errors during execution
  • output_chars: Total character count of output files
  • transcript_chars: Character count of transcript

timing.json

Wall clock timing for a run. Located at <run-dir>/timing.json.

How to capture: When a subagent task completes, the task notification includes total_tokens and duration_ms. Save these immediately — they are not persisted anywhere else and cannot be recovered after the fact.

{
  "total_tokens": 84852,
  "duration_ms": 23332,
  "total_duration_seconds": 23.3,
  "executor_start": "2026-01-15T10:30:00Z",
  "executor_end": "2026-01-15T10:32:45Z",
  "executor_duration_seconds": 165.0,
  "grader_start": "2026-01-15T10:32:46Z",
  "grader_end": "2026-01-15T10:33:12Z",
  "grader_duration_seconds": 26.0
}

benchmark.json

Output from Benchmark mode. Located at benchmarks/<timestamp>/benchmark.json.

{
  "metadata": {
    "skill_name": "pdf",
    "skill_path": "/path/to/pdf",
    "executor_model": "claude-sonnet-4-20250514",
    "analyzer_model": "most-capable-model",
    "timestamp": "2026-01-15T10:30:00Z",
    "evals_run": [1, 2, 3],
    "runs_per_configuration": 3
  },

  "runs": [
    {
      "eval_id": 1,
      "eval_name": "Ocean",
      "configuration": "with_skill",
      "run_number": 1,
      "result": {
        "pass_rate": 0.85,
        "passed": 6,
        "failed": 1,
        "total": 7,
        "time_seconds": 42.5,
        "tokens": 3800,
        "tool_calls": 18,
        "errors": 0
      },
      "expectations": [
        {"text": "...", "passed": true, "evidence": "..."}
      ],
      "notes": [
        "Used 2023 data, may be stale",
        "Fell back to text overlay for non-fillable fields"
      ]
    }
  ],

  "run_summary": {
    "with_skill": {
      "pass_rate": {"mean": 0.85, "stddev": 0.05, "min": 0.80, "max": 0.90},
      "time_seconds": {"mean": 45.0, "stddev": 12.0, "min": 32.0, "max": 58.0},
      "tokens": {"mean": 3800, "stddev": 400, "min": 3200, "max": 4100}
    },
    "without_skill": {
      "pass_rate": {"mean": 0.35, "stddev": 0.08, "min": 0.28, "max": 0.45},
      "time_seconds": {"mean": 32.0, "stddev": 8.0, "min": 24.0, "max": 42.0},
      "tokens": {"mean": 2100, "stddev": 300, "min": 1800, "max": 2500}
    },
    "delta": {
      "pass_rate": "+0.50",
      "time_seconds": "+13.0",
      "tokens": "+1700"
    }
  },

  "notes": [
    "Assertion 'Output is a PDF file' passes 100% in both configurations - may not differentiate skill value",
    "Eval 3 shows high variance (50% ± 40%) - may be flaky or model-dependent",
    "Without-skill runs consistently fail on table extraction expectations",
    "Skill adds 13s average execution time but improves pass rate by 50%"
  ]
}

Fields:

  • metadata: Information about the benchmark run
    • skill_name: Name of the skill
    • timestamp: When the benchmark was run
    • evals_run: List of eval names or IDs
    • runs_per_configuration: Number of runs per config (e.g. 3)
  • runs[]: Individual run results
    • eval_id: Numeric eval identifier
    • eval_name: Human-readable eval name (used as section header in the viewer)
    • configuration: Must be "with_skill" or "without_skill" (the viewer uses this exact string for grouping and color coding)
    • run_number: Integer run number (1, 2, 3...)
    • result: Nested object with pass_rate, passed, total, time_seconds, tokens, errors
  • run_summary: Statistical aggregates per configuration
    • with_skill / without_skill: Each contains pass_rate, time_seconds, tokens objects with mean and stddev fields
    • delta: Difference strings like "+0.50", "+13.0", "+1700"
  • notes: Freeform observations from the analyzer

Important: The viewer reads these field names exactly. Using config instead of configuration, or putting pass_rate at the top level of a run instead of nested under result, will cause the viewer to show empty/zero values. Always reference this schema when generating benchmark.json manually.

comparison.json

Output from blind comparator. Located at <grading-dir>/comparison-N.json.

{
  "winner": "A",
  "reasoning": "Output A provides a complete solution with proper formatting and all required fields. Output B is missing the date field and has formatting inconsistencies.",
  "rubric": {
    "A": {
      "content": {
        "correctness": 5,
        "completeness": 5,
        "accuracy": 4
      },
      "structure": {
        "organization": 4,
        "formatting": 5,
        "usability": 4
      },
      "content_score": 4.7,
      "structure_score": 4.3,
      "overall_score": 9.0
    },
    "B": {
      "content": {
        "correctness": 3,
        "completeness": 2,
        "accuracy": 3
      },
      "structure": {
        "organization": 3,
        "formatting": 2,
        "usability": 3
      },
      "content_score": 2.7,
      "structure_score": 2.7,
      "overall_score": 5.4
    }
  },
  "output_quality": {
    "A": {
      "score": 9,
      "strengths": ["Complete solution", "Well-formatted", "All fields present"],
      "weaknesses": ["Minor style inconsistency in header"]
    },
    "B": {
      "score": 5,
      "strengths": ["Readable output", "Correct basic structure"],
      "weaknesses": ["Missing date field", "Formatting inconsistencies", "Partial data extraction"]
    }
  },
  "expectation_results": {
    "A": {
      "passed": 4,
      "total": 5,
      "pass_rate": 0.80,
      "details": [
        {"text": "Output includes name", "passed": true}
      ]
    },
    "B": {
      "passed": 3,
      "total": 5,
      "pass_rate": 0.60,
      "details": [
        {"text": "Output includes name", "passed": true}
      ]
    }
  }
}

analysis.json

Output from post-hoc analyzer. Located at <grading-dir>/analysis.json.

{
  "comparison_summary": {
    "winner": "A",
    "winner_skill": "path/to/winner/skill",
    "loser_skill": "path/to/loser/skill",
    "comparator_reasoning": "Brief summary of why comparator chose winner"
  },
  "winner_strengths": [
    "Clear step-by-step instructions for handling multi-page documents",
    "Included validation script that caught formatting errors"
  ],
  "loser_weaknesses": [
    "Vague instruction 'process the document appropriately' led to inconsistent behavior",
    "No script for validation, agent had to improvise"
  ],
  "instruction_following": {
    "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"
      ]
    }
  },
  "improvement_suggestions": [
    {
      "priority": "high",
      "category": "instructions",
      "suggestion": "Replace 'process the document appropriately' with explicit steps",
      "expected_impact": "Would eliminate ambiguity that caused inconsistent behavior"
    }
  ],
  "transcript_insights": {
    "winner_execution_pattern": "Read skill -> Followed 5-step process -> Used validation script",
    "loser_execution_pattern": "Read skill -> Unclear on approach -> Tried 3 different methods"
  }
}