session-summary

Original：🇨🇳 Chinese

Translated

1 scripts

Automatically generate a Chinese session summary when a Claude Code session ends, and save it to .claude/summaries/. It is used when users need to record conversation history, generate work logs, or review context.

2installs

Sourcetrree/ark-skills

Added on2026-03-31

NPX Install

npx skill4agent add trree/ark-skills session-summary

SKILL.md Content (Chinese)

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Session Summary

Automatically generate a structured Chinese summary at the end of each session, and persist it to the project directory.

Trigger Method

Automatically triggered via the

SessionEnd

hook, no manual call required.

After installation, you need to merge the hooks configuration into

~/.claude/settings.json

, see

references/setup.md

for details.

Implementation Note: Since the
agent
type hook of
SessionEnd
has a silent failure bug (anthropics/claude-code#40010), switch to the
command
hook to call
scripts/summarize.sh
, and the script asynchronously completes the summary via
claude -p
internally.

Deduplication Mechanism

Only generated once for the same session (
```
once: true
```
)
The file name contains the first 8 characters of session_id, and it will be overwritten instead of creating a new one when triggered repeatedly
Automatically skipped if the number of conversation rounds is less than 3

Summary Format

Refer to

templates/summary.md.template

, output 5 fields:

Core Goal — What problem this session intends to solve
Completed Content — What was actually done, where the outputs are located
Key Decisions — What judgments worth recording have been made
Pending Items — Tasks that need to be continued next time
Skills Used — Which skills were called

Manual Trigger

Say "Generate a summary of this session" in the conversation to trigger manually, the output path is the same as that of automatic trigger.

Position in ark-skills

Public role: Conversation recording and context persistence
Working directory:
```
<project_root>/.claude/summaries/
```
Recommended collocations:
- Use with
```
wechat-pipeline
```
  to record the execution status of each production line
- Use with
```
ai-workflow-brand
```
  to record each positioning decision