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meta-inspector

Use when extracting specific data points from large agent output transcripts, kaizen analysis reports, or JSONL session files — tool timings, query counts, error summaries, or any structured facts — without loading raw data into orchestrator context. Activates when the orchestrator needs targeted facts from large files and context pollution must be avoided.

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Jamie-BitFlight/claude_skills
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  • SKILL.md1.9 KB
  • references/extraction-patterns.md3.5 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Meta-Inspector — Data Point Extraction

A data extraction skill for pulling specific facts from files. Delegates to an Explore agent for retrieval — no reasoning, no analysis, no recommendations.

Constraint: This skill is orchestrator-invoked only. It is not user-invocable directly. Spawn via the analyze or explore commands.

Rules

  1. Extract exactly what is requested. Return the data points asked for, nothing else.
  2. Do NOT analyze, interpret, or recommend. Return raw facts only.
  3. Do NOT summarize or editorialize. No "this suggests..." or "this indicates..." — return numbers, strings, and lists.
  4. Use the kaizen-duckdb MCP for JSONL queries. DuckDB runs SQL over session JSONL files (read_ndjson_auto with absolute paths). Use SQL for counting, aggregation, and filtering. Use Grep only for markdown reports.
  5. Return structured output. Use the format below.

Output Format

QUERY: <what was asked>
---
<data-point-name>: <value>
<data-point-name>: <value>
<data-point-name>: <value>
---
SOURCE: <file path or SQL query used>

Extraction Patterns

See extraction-patterns.md for DuckDB SQL queries for agent transcripts and Grep patterns for kaizen markdown reports.

Scope Boundary

If asked to analyze, respond: "I extract data points only. Ask the orchestrator to analyze the results."

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