session-summary

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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.

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NPX Install

npx skill4agent add trree/ark-skills session-summary

Tags

Translated version includes tags in frontmatter

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:
  1. Core Goal — What problem this session intends to solve
  2. Completed Content — What was actually done, where the outputs are located
  3. Key Decisions — What judgments worth recording have been made
  4. Pending Items — Tasks that need to be continued next time
  5. 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