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Archive Claude Code conversation logs into the current project as JSONL and readable Markdown
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Based on SOC occupation classification
| name | archive-logs |
| description | Archive Claude Code conversation logs into the current project as JSONL and readable Markdown |
| disable-model-invocation | true |
Archive the Claude Code conversation logs from this project into the project itself, for auditability and transparency.
Find logs: Look in ~/.claude/projects/<encoded-path>/ where the encoded path replaces / with - in the current working directory path. List *.jsonl files (top-level only, not subdirectories).
Identify sessions: For each JSONL, extract the first user message to understand the session topic. Skip files with 0 user messages. Assign descriptive numbered names (e.g. 01_initial_setup.jsonl, 02_feature_work.jsonl).
Check for duplicates: If logs/conversation/ already exists, compare against existing files to avoid re-archiving.
Copy JSONL files into logs/conversation/ in the project.
Create a converter script at scripts/jsonl_to_markdown.py that converts JSONL to readable Markdown. The JSONL format:
type fielduser and assistant contain message.content (string or array of content blocks)text (render), tool_use (show tool name + concise input), tool_result (abbreviate), thinking (omit)<system-reminder> tags from user messagesRun the converter to generate .md files alongside the .jsonl files.
Scan for secrets: Install detect-secrets (uv add --dev detect-secrets or ensure it's available), then run detect-secrets scan logs/conversation/ on all archived files (both .jsonl and .md). If any secrets are detected:
echo $API_KEY, env variable dumps, credential outputs.Write logs/conversation/README.md listing each session.
Report what was archived (and whether the secret scan passed cleanly).
Use when someone is about to lose access to a machine (shared server, lab box, cloud/VM instance, expiring rental) and needs to preserve all their work before it's gone. Systematically finds everything that exists ONLY on that machine — unpushed commits, stashes, untracked/uncommitted files, dirty submodules, non-git dirs, loose files, and large gitignored artifacts — and backs it up to GitHub / HuggingFace / an off-machine archive, non-destructively. Triggers on "losing access to this machine", "back up everything before I lose the server", "migrating off this box", "decommission", "my instance expires".
Use when preparing a paper's camera-ready or arXiv release — de-anonymizing an accepted submission, packaging an arXiv tarball, checking dual-submission safety against a concurrent venue (e.g. a paper accepted at a workshop that's also under review at NeurIPS/ICML), or flagging reviewer-requested post-review additions. Encodes a byte-identity discipline (the public version changes ONLY author/venue metadata, never content), a numbers-from-scripts integrity gate, and the arXiv mechanics that actually bite.
Spin up one or more fresh-context subagents to critically evaluate a proposed theory, hypothesis, interpretation, or experimental design before committing to it. Use when the user says "have an agent critique this" / "get a second opinion on" / "is this design sound" / invokes /critique, or proactively before running any experiment or committing to a non-trivial theoretical claim.
Use when launching a multi-hour neural-network training, fine-tune, or other long GPU job autonomously from Claude Code and you need to catch failures (NaN, stuck-at-chance, dead process, throughput collapse, OOM) early instead of waking up to a wasted GPU window.
Use when the user asks to check, audit, or improve a website or web project for accessibility (a11y), WCAG compliance, screen reader support, keyboard navigation, color contrast, or alt text. Triggers a plan-mode investigation against the TeachAccess design and code checklists, then implements approved fixes.
Consolidate scattered research notes, logs, experiment outputs, and submodule docs into a single living research paper. Use when the user wants to pull together multiple source documents into one structured paper.