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ce-session-inventoryCE 会话清单

Agent Skill

ce-session-inventory 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,508

周安装

61

GitHub Stars

15,923

下载量

473
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ce-session-inventory(CE 会话清单)
来源仓库:https://github.com/everyinc/compound-engineering-plugin
仓库路径:skills/ce-session-inventory
安装命令:
npx skills add https://github.com/everyinc/compound-engineering-plugin --skill ce-session-inventory
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/everyinc/compound-engineering-plugin --skill ce-session-inventory

简介

用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 可结合关键词、任务场景或来源线索进行信息定位,提供会话文件发现。
  • 需确认权限范围和维护状态,避免触发联网或文件读写操作。
  • 安装前建议检查原始 README 和仓库路径,确保符合宿主环境要求。
  • ce-session-inventory 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Session inventory

Agent-facing primitive. Discover session files and emit session metadata as JSONL across Claude Code, Codex, and Cursor.

This skill exists so that agents researching session history do not need to know the layout of session stores on disk or the JSONL shapes of each platform. The scripts under scripts/ own that knowledge.

Arguments

Space-separated positional args:

  1. <repo> — repo folder name (e.g., my-project). Used for directory matching in Claude Code and Cursor, and as the CWD filter for Codex sessions.
  2. <days> — scan window in days (e.g., 7). Session files older than this are skipped.
  3. <platform> *(optional)* — one of claude, codex, cursor. Omit to search all three.
  4. --keyword K1[,K2,...] *(optional)* — filter to sessions whose full file content matches at least one of the comma-separated keywords (case-insensitive substring). Each emitted session line gains match_count and keyword_matches ({K: N,...}) fields, and the _meta line gains files_matched. Use this instead of rolling per-file grep -l calls when ranking many sessions by topical relevance.

Execution

Run the discovery-plus-metadata pipeline from the skill's own scripts/ directory:

bash scripts/discover-sessions.sh <repo> <days> [--platform <platform>] \
  | tr '\n' '\0' \
  | xargs -0 python3 scripts/extract-metadata.py --cwd-filter <repo>

To filter by keyword, append --keyword K1[,K2,...] to the extract-metadata.py invocation. Keyword scanning reads the full file (not just the head metadata window), so it costs more than a metadata-only run — use it when you need to rank candidates by topic across many sessions, not as a default.

Return the raw stdout verbatim — one JSON object per session, then a final _meta line. Callers parse the JSONL directly, so do not paraphrase, reformat, or summarize.

If discovery finds no files, the pipeline still emits a clean _meta line (files_processed: 0). Return that as-is.

Output format

Each session line is a JSON object. Common fields across platforms:

  • platformclaude, codex, or cursor
  • file — absolute path to the session JSONL
  • size — file size in bytes
  • ts — session start timestamp (ISO 8601)
  • session — session identifier

Platform-specific fields:

  • Claude Code adds branch (git branch) and last_ts (last message timestamp).
  • Codex adds cwd (working directory), source, cli_version, model, last_ts.
  • Cursor has no in-file timestamps or metadata — ts is derived from file mtime and session from the containing directory name.

The final _meta line has files_processed, parse_errors, and optionally filtered_by_cwd (count of Codex sessions dropped by the CWD filter) and files_matched (count of sessions retained by the keyword filter, present only when --keyword was set).

When --keyword is set, each session line additionally carries:

  • match_count — total occurrences across all keywords
  • keyword_matches — per-keyword counts, e.g., {"middleware": 4, "auth": 12}

Sessions with match_count: 0 are excluded from output.

Error handling

If the discovery script errors (e.g., unreadable home directory, permission failure), let the error surface to the caller. Do not substitute git log, file listings, or other sources — this skill's contract is session metadata, nothing else.

If _meta reports parse_errors > 0, return the JSONL as-is. The caller decides how to handle partial data.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.4%
按下载量换算177

Claude

30.8%
按下载量换算146

Cursor

20.03%
按下载量换算95

Gemini CLI

9.46%
按下载量换算45

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

权限需确认

当前来源未能明确判断权限范围,默认进入异常复核队列。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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