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oliverweissloliverweissl/context-garden/skills/compost/SKILL.md

compost

Skill4 starsChanged 16 days agoMITView on GitHub

Run long or repetitive commands (builds, pytest/ctest, SLURM jobs, solver logs) through a clustering summarizer instead of reading raw output; re-runs show only what changed. Use for output likely over ~100 lines or fix-test-fix loops.

1 other project uses a version of this.

Adopted by

Most recently taken up by

  • Other versions1 project uses a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 1

    1. Leebonggu/slop-compost★ 0same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository5 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Read the summary, not the raw log.

    line 26
  2. Very specific:

    Only if the summary is insufficient, use the printed retrieval_handles (get <id> --lines A:B, event <id> --event N, grep <id> '<pattern>', …

    line 29

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

compost

!"${CLAUDE_SKILL_DIR}/bin/compost" mode --banner

Agents that do not expand the line above (e.g. Codex): run <this-skill-dir>/bin/compost mode --banner first and follow it.

Offline, deterministic: output is parsed and clustered by script (no LLM); the full raw output is always kept on disk. Skip it for short output -- just read that directly.

compost is not on PATH: always use the full <this-skill-dir>/bin/compost path (or python3 <this-skill-dir>/scripts/compost.py if executables are not permitted).

  1. Run: <this-skill-dir>/bin/compost run -- <command...> (pipes/redirects need bash -c '...'). Prints the root error (first error in user code), secondary failure groups with counts, warnings, numerical summary, and a raw_output_id.
  2. Read the summary, not the raw log.
  3. Re-run the same command the same way: only new/resolved errors and count deltas are printed ("No structural changes." if none).
  4. Only if the summary is insufficient, use the printed retrieval_handles (get <id> --lines A:B, event <id> --event N, grep <id> '<pattern>', show <id> --json). They never re-run the command; they read the already-stored raw output.
  5. Existing log file: bin/compost ingest --file <path> (or --stdin).
  6. The plugin's Bash hook may deny a raw build/test command and name the compost command to run instead: run that. Need raw output (e.g. to show the user)? Append # raw to the command.

Profiles (auto-detected, --profile to override): pytest, ctest, gcc/clang, cmake, python_traceback, slurm, numerical_solver, generic.

Output fields, statuses, storage and retention: references/schema.md. Per-profile detection: references/profiles.md.

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