| name | session-distill |
| description | Distill Codex session JSONL files into review packets, local session notes,
and reusable memory candidates. Use when the user asks to整理/提炼 Codex
对话, process `.codex/archived_sessions` or `.codex/sessions` rollouts,
generate session packets, review packet coverage, or mark Codex sessions as
distilled.
|
Codex Session Distiller
This is the Codex-native session-distill skill. It reads Codex rollout
JSONL, not Claude Code session files.
Inputs And Outputs
- Input sessions:
~/.codex/archived_sessions/rollout-*.jsonl~/.codex/sessions/**/*.jsonl~/.codex/session_index.jsonl for thread names when available
- Workspace:
~/.codex/session-distill/manifest.json~/.codex/session-distill/packets/<session-id>.md~/.codex/session-distill/distilled/sessions/<session-id>.md~/.codex/session-distill/knowledge-base.md- optional
~/.codex/session-distill/memory-drafts/<session-id>.json
Default Workflow
Deep Distill (servers, recommended)
python ~/.codex/skills/manhua/session-distill/bin/deep-distill-run.py --offset 0 --batch-size 3
Then: answer-me verify → promote ANSWERED only → session-knowledge-base.md §Codex → check-work → mark distilled.
See references/deep-distill-workflow.md.
Legacy single-session flow
- Run
python ~/.codex/skills/manhua/session-distill/bin/session-distill.py run --next 1.
- Read the generated packet and inspect
Packet Audit first.
- If
Coverage: partial, inspect the raw JSONL span before promoting any conclusion.
- Write a session note under
distilled/sessions/<session-id>.md.
- Append only stable reusable knowledge to
knowledge-base.md, or explicitly record no promotion.
- Before marking distilled, run a lightweight knowledge review when you promoted anything:
python ~/.codex/skills/manhua/session-distill/bin/session-distill.py review-kb --next 20 --query <session-id-or-topic>
- If memory drafts exist, review every entry so none remain
pending.
- Run
python ~/.codex/skills/manhua/session-distill/bin/session-distill.py mark <session-id> distilled.
This retains the original Codex rollout JSONL. If it is ever necessary to
remove raw data, use the separate audited prune-raw <session-id> --confirm
command with a reason.
The mark distilled command has guardrails: it fails unless the note exists,
partial packets mention raw review, memory drafts have no pending entries, and
the note records a promotion decision. If knowledge-base.md already contains
entries sourced from the same session, obvious volatile or weak entries are also
rejected unless you use --force. Raw-file deletion still only applies under
~/.codex/archived_sessions or ~/.codex/sessions.
Commands
python ~/.codex/skills/manhua/session-distill/bin/deep-distill-run.py --offset 0 --batch-size 3
python ~/.codex/skills/manhua/session-distill/bin/session-distill.py status
python ~/.codex/skills/manhua/session-distill/bin/session-distill.py list --size 100
python ~/.codex/skills/manhua/session-distill/bin/session-distill.py run --next 1
python ~/.codex/skills/manhua/session-distill/bin/session-distill.py mark <session-id> distilled
python ~/.codex/skills/manhua/session-distill/bin/session-distill.py prune-raw <session-id> --confirm --reason "retention policy"
python ~/.codex/skills/manhua/session-distill/bin/session-distill.py review-kb --next 20
python ~/.codex/skills/manhua/session-distill/bin/session-distill.py verify-entry <session-id|keyword>
python ~/.codex/skills/manhua/session-distill/bin/session-distill.py prune-kb --statuses stale,superseded
python ~/.codex/skills/manhua/session-distill/bin/session-distill.py self-test
References
references/codex-session-format.md: Codex JSONL event shapes and packet rules.references/deep-distill-workflow.md: Grok-paradigm batch pipeline for servers.references/distillation-rules.md: promotion and filtering rules.references/output-layout.md: workspace layout and status meanings.
Use the older Claude session distiller only for ~/.claude/projects/*.jsonl.
