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session-reflection会话反思

Agent Skill

session-reflection 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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

2,444

周安装

105

GitHub Stars

2

下载量

857
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:session-reflection(会话反思)
来源仓库:https://github.com/jwilger/agent-skills
仓库路径:skills/session-reflection
安装命令:
npx skills add https://github.com/jwilger/agent-skills --skill session-reflection
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/jwilger/agent-skills --skill session-reflection

简介

session-reflection 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。

  • 它能自动提取仓库元数据、变更摘要和协作动态,便于跟踪项目进展。
  • 安装命令为 npx skills add https://github.com/jwilger/agent-skills --skill session-reflection,需确认权限范围和维护状态。
  • 使用前建议核验是否会触发联网、命令执行或文件读写,并参考原始 README 了解具体用法。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Session Reflection

Value: Feedback -- every user intervention is a signal that the system prompt is incomplete. Turning corrections into durable instructions creates compound improvement across sessions.

Purpose

Teaches agents to analyze session history for recurring corrections, generate project-specific instructions that prevent known failure modes, and maintain working state that survives context compaction and crashes. Transforms reactive corrections into proactive prevention.

Practices

Reflection Triggers

Reflect after: milestones (PR merged, feature complete), 3+ repeated corrections from the user, session restart or crash recovery, every 5 completed tasks, and on explicit user request. Do not wait for a "good time" -- reflect when triggered.

Analyze Session History

Examine conversation history, git log, memory files, WORKING_STATE.md, and session logs. Categorize each user intervention into one of five types:

  • Correction: Agent did the wrong thing (instruction gap)
  • Repetition: Agent was told the same thing again (emphasis gap)
  • Role Redirect: Agent stepped outside its role (boundary gap)
  • Frustration Escalation: User became more forceful (decay problem)
  • Workaround: User did it themselves (skill gap)

See references/analysis-framework.md for detailed categorization and prioritization.

Generate or Refine Project Instructions

Route project-specific directives into the appropriate instruction file based on content type. There is no separate system prompt file — everything flows from CLAUDE.md → AGENTS.md →.team/coordinator-instructions.md:

  • CLAUDE.md — Session management (startup procedure, compaction recovery, state tracking), harness-specific configuration
  • AGENTS.md — General project rules, dos/don'ts, coding conventions, workflow configuration
  • .team/coordinator-instructions.md — Coordinator/pipeline-controller role distinctions, build pre-flight gates, spawn discipline, domain review checklists

Refinement rules: add new items for new gaps, promote advisory to structural when gaps recur, rewrite ambiguous items for clarity. Never remove items until the gap is confirmed solved across 3+ sessions. See references/system-prompt-patterns.md for writing patterns and references/launcher-templates.md for harness-specific file routing.

Self-Reminder Protocol

See CONSTRAINT-RESOLUTION.md in the template directory for the consolidated self-reminder protocol (frequency, combined re-read list, and post-compaction rules).

Working State Persistence

Maintain WORKING_STATE.md as insurance against context compaction and crashes. Update after every significant state change. Always read before acting after any interruption. Location: .factory/WORKING_STATE.md (pipeline) or project root (standalone). See references/working-state-schema.md for format.

Do:

  • Update on task start, phase change, decision made, blocker encountered
  • Overwrite with current state (not append)
  • Read FIRST after any interruption

Do not:

  • Guess state from memory after a compaction or restart
  • Use as a journal -- keep it concise and current
  • Skip updates because "nothing important changed"

Post-Session Learning Loop

At session end: identify patterns from this session, update memory files, refine project instructions if triggers were hit, archive working state.

The loop closes when the same category of intervention stops recurring. If an intervention category persists across 3+ sessions after instruction refinement, escalate: the gap may require a new skill or a structural change to the workflow.

Enforcement Note

Advisory in all modes. Reflection triggers and instruction generation are self-enforced.

Hard constraints:

  • Mandatory after context compaction: [H] -- context compaction destroys implicit state; re-reading is not optional.

Constraints

  • "3+ repeated corrections": A "repeated correction" means the user corrected the same underlying behavior multiple times. Different phrasings of the same correction count as one correction repeated. Different corrections in the same category (e.g., two different formatting preferences) count separately.
  • "Never remove instructions until confirmed solved across 3+ sessions": This prevents premature cleanup. An instruction that hasn't triggered in 3 sessions might be preventing the problem -- that's success, not staleness. Remove only when you have positive evidence the underlying behavior is fixed (e.g., the code pattern that caused the issue no longer exists).

Verification

After completing work guided by this skill, verify:

  • Reflection performed at every trigger point (milestone, repeated correction, restart)
  • User interventions categorized using the five-type taxonomy
  • Project instructions refined with structural (not just advisory) language
  • Directives routed to correct file (CLAUDE.md / AGENTS.md / coordinator-instructions.md)
  • Self-reminder protocol followed (state re-read every 5-10 messages)
  • WORKING_STATE.md current and accurate
  • State re-read after every context compaction (not guessed)

If any criterion is not met, revisit the relevant practice before proceeding.

Dependencies

This skill works standalone. For enhanced workflows, it integrates with:

  • memory-protocol: Persistent storage for session learnings and working state
  • agent-coordination: Coordination patterns referenced in instruction generation
  • pipeline: Pipeline controller benefits from self-reminder and crash recovery
  • ensemble-team: Team retrospectives feed into session reflection analysis

Missing a dependency? Install with:

npx skills add jwilger/agent-skills --skill memory-protocol

适合场景

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能力概览

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能力 2

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能力 3

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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

34.93%
按下载量换算299

Claude

27.71%
按下载量换算237

Cursor

19.83%
按下载量换算170

Gemini CLI

9.72%
按下载量换算83

安全审计

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通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/jwilger/agent-skills --skill session-reflection 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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