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chomp
Clone a GitHub repo (or dump the current repo), generate a markdown file of its source, then run a full RLM analysis loop against it.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Clone a GitHub repo (or dump the current repo), generate a markdown file of its source, then run a full RLM analysis loop against it.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | chomp |
| description | Clone a GitHub repo (or dump the current repo), generate a markdown file of its source, then run a full RLM analysis loop against it. |
| user-invocable | true |
| allowed-tools | ["Read","Write","Edit","Grep","Glob","Bash","Agent"] |
Clones a GitHub repo (or dumps the current repo with local), generates a single markdown file of its source, loads it as RLM context, generates bits (neutral structured summaries), and runs a full analysis loop.
/chomp <git-url|local> [clone]
<git-url|local> (required): GitHub repository URL, or local to chomp the current repo.clone (optional): if present and using a git URL, clone the repo into the current working directory so edits can be made. Ignored when using local.Read $ARGUMENTS. Determine if the first argument is local or a git URL. If it's a git URL, check whether the word clone is present.
If using a git URL and clone is in the arguments:
git clone <git-url>
This clones into the current working directory (wherever Claude Code is running).
Skip this step entirely when the argument is local.
Run the chomp shell script to produce the markdown file:
bash ~/.claude/skills/chomp-init/scripts/chomp <git-url|local>
chomp/<repo-name>.md.local, this creates chomp/local.md. The chomp/ and .claude/ directories are automatically excluded. Running this again overwrites the previous local.md.Use local as the repo name when the argument is local, otherwise use the repo name extracted from the URL.
python3 ~/.claude/skills/chomp-init/scripts/rlm_repl.py init chomp/<repo-name>.md
python3 ~/.claude/skills/chomp-init/scripts/rlm_repl.py status
python3 ~/.claude/skills/chomp-init/scripts/rlm_repl.py exec -c "print(peek(0, 3000))"
python3 ~/.claude/skills/chomp-init/scripts/rlm_repl.py exec -c "print(peek(len(content)-3000, len(content)))"
python3 ~/.claude/skills/chomp-init/scripts/rlm_repl.py exec <<'PY'
paths = write_chunks('chomp/.rlm_state/chunks', size=200000, overlap=0)
print(len(paths))
print(paths[:5])
PY
Run three fixed queries against every chunk using the rlm-subcall subagent. These are neutral queries — they capture what the codebase is, not what the user wants to do with it.
Queries:
For each query, invoke the rlm-subcall subagent against each chunk file. Collect all results.
Synthesize — for each query, combine the subcall results into a single coherent markdown file. Keep each file under 500 words. Write to:
chomp/bits/<repo-name>/
surface.md
patterns.md
deps.md
Print a summary of the bits that were generated. Stop here and ask the user what they want to know or do with this codebase. Wait for their response before continuing.
Once the user provides their question, execute the full RLM workflow:
Subcall loop — for each chunk file (already written in step 6), invoke the rlm-subcall subagent with:
Synthesis — once all chunks are processed, synthesise the final answer in the main conversation. Optionally use rlm-subcall once more to merge collected results.
Apply changes — if the user asked for code changes and clone was specified, apply the changes directly to the cloned repo in the current working directory.
chomp/.rlm_state/.