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Agent Skill · 研究检索

retro(retro 分析)

retro 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。

retro 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 58,406。

总安装 416周安装 17GitHub Stars 76下载 135核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:retro(retro 分析)
来源仓库:https://github.com/corca-ai/claude-plugins
仓库路径:skills/retro
安装命令:
npx skills add https://github.com/corca-ai/claude-plugins --skill retro
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/corca-ai/claude-plugins --skill retro

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

在会话结束时生成回顾报告,将结果转化为可复用的过程改进建议。适用于深度分析会话产出、提取经验教训并优化后续工作流程。默认生成 retro.md 文件,支持专家视角分析与学习资源推荐。

安装方式:GitHub,命令为 npx skills add https://github.com/corca-ai/claude-plugins --skill retro。retro 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/retro

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/corca-ai/claude-plugins --skill retro;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

retro 怎么安装?

在终端执行 npx skills add https://github.com/corca-ai/claude-plugins --skill retro。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

retro 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

retro 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

retro 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

retro 用的人多吗?

公开数据是累计安装 416 次,近一周安装 17 次,下载 135 次,GitHub 76 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

retro 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
retro

retro 分析 · 本页

41676只读未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Session Retrospective

Adaptive end-of-session review that converts outcomes into durable process/context/tool improvements. Deep by default; light mode is used with --light or for tiny routine sessions. Produces retro.md alongside plan.md and lessons.md in the session artifact directory.

Quick Start

/retro [path]            # adaptive (deep by default)
/retro --deep [path]     # full analysis with expert lens
/retro --from-run [path] # internal flag when invoked by cwf:run
  • path: optional override for output directory
  • --deep: force full 7-section analysis (expert lens, learning resources, web search)
  • --from-run: internal invocation context flag; enables compact report for run-chain orchestration

Workflow

0. Update Live State

Run:

bash {CWF_PLUGIN_DIR}/scripts/cwf-live-state.sh set . phase="retro"

1. Locate Output Directory

Resolution order:

  1. If [path] argument provided, use it
  2. Reuse .cwf/projects/ path already used in this session (plan.md/lessons.md writes)
  3. If reused session path date prefix (YYMMDD) differs from today's local date, AskUserQuestion:

- Continue existing session directory (recommended for same logical session across midnight/day rollover) - Start a new dated directory for today

  1. If user selects a new dated directory, run {CWF_PLUGIN_DIR}/scripts/next-prompt-dir.sh --bootstrap <title>, then copy plan.md and lessons.md from the previous session directory when present so retro context is preserved.
  2. If multiple candidates exist, AskUserQuestion with candidates
  3. Otherwise run {CWF_PLUGIN_DIR}/scripts/next-prompt-dir.sh --bootstrap <title>
1.1 Non-Interactive Fallback (Required)

If AskUserQuestion is unavailable/blocked, do not wait. Resolve path in this order: explicit [path] -> live.dir -> latest .cwf/projects/ -> bootstrap via {CWF_PLUGIN_DIR}/scripts/next-prompt-dir.sh --bootstrap retro-light. Record a short note (Fast path or Post-Retro Findings) so the fallback choice is auditable.

1.2 Early Light Fast-Path Short-Circuit (Required)

If invocation includes --light, run deterministic fast path immediately after output-dir resolution (before evidence collection and large artifact reads):

bash {CWF_PLUGIN_DIR}/scripts/retro-light-fastpath.sh \
  --session-dir "{output-dir}" \
  --invocation "{invocation_mode}" \
  --lang "{user-language}"

Then validate retro stage gate immediately:

bash {CWF_PLUGIN_DIR}/scripts/check-run-gate-artifacts.sh \
  --session-dir "{output-dir}" \
  --stage retro \
  --strict

Rules:

  • Determine invocation_mode with the same criteria as Section 3.1 before running this command.
  • In non-interactive direct runs, stop after this short-circuit path succeeds.
  • Do not call AskUserQuestion in this path.

2. Read Existing Artifacts

Skip this section when Section 1.2 completed and execution already ended in non-interactive light mode.

Before reading artifacts, run the evidence collector (it includes best-effort Codex session-log sync with timeout protection):

bash {CWF_PLUGIN_DIR}/scripts/retro-collect-evidence.sh --session-dir "{output-dir}"

Then read retro-evidence.md (if generated), plan.md, lessons.md, and cwf-state.yaml. Read AGENTS/adapter docs and project-context docs only when those files exist.

When running deep mode (or when user explicitly specifies a diff baseline/scope), generate coverage-contract artifacts before drafting narrative sections:

bash {CWF_PLUGIN_DIR}/scripts/retro-coverage-contract.sh \
  --session-dir "{output-dir}" \
  --base-ref "{retro_base_ref:-HEAD~1}"

Then cite at least:

  • total changed file count (artifact name: "diff-all-excl-session-logs.txt")
  • top-level breakdown (artifact name: "diff-top-level-breakdown.txt")
  • historical lessons/retro primary corpus count (artifact name: "project-lessons-retro-primary.txt")

3. Select Mode

Parse the --deep flag from the invocation arguments.

If --deep is present: mode = deep (full 7 sections).

If --deep is absent: assess session weight to decide mode:

  • Light (Sections 1-4 + 7): Only when --light is explicitly specified, OR session < 3 turns with routine/simple tasks (config changes, small fixes, doc edits)
  • Default bias: Deep. Invoking retro is itself a signal that the session warrants analysis. Use --light to explicitly request lightweight mode when cost savings is desired.

3.2 Light Fast Path (Required for --light)

Reuse the command and gate in Section 1.2. Do not rerun unless retro.md is missing/invalid. In non-interactive runs, stop after fast path + gate. Do not call AskUserQuestion when fallback policy is sufficient.

3.1 Detect Invocation Context

Determine invocation context from arguments and live task:

  • Run-chain invocation: --from-run present, or live task explicitly indicates cwf:run.
  • Direct user invocation: all other cases.

Persist this as:

invocation_mode: run_chain | direct

4. Draft Retro

Draft everything internally before writing to file.

Light Mode Path

After fast path bootstrap, enrich sections 1-4 and 7 inline only if time/context budget allows. No sub-agents.

Deep Mode Path

Draft sections 1-3 inline (these require full conversation access), then launch parallel sub-agents in two batches.

Resolve session directory: Resolve the effective live-state file, then read live.dir.

live_state_file=$(bash {CWF_PLUGIN_DIR}/scripts/cwf-live-state.sh resolve)
session_dir: "{live.dir value from resolved live-state file}"

Apply the context recovery protocol to these files before launching each batch:

BatchAgentOutput file
1CDM Analysis{session_dir}/retro-cdm-analysis.md
1Learning Resources{session_dir}/retro-learning-resources.md
2Expert α{session_dir}/retro-expert-alpha.md
2Expert β{session_dir}/retro-expert-beta.md

Stage-tier policy for deep mode outputs:

  • Critical (hard gate): {session_dir}/retro-cdm-analysis.md
  • Non-critical (soft gate): {session_dir}/retro-learning-resources.md, {session_dir}/retro-expert-alpha.md, {session_dir}/retro-expert-beta.md

For all outputs: bounded retry = 1 for missing/invalid files.

Run slot preflight before each batch launch:

bash {CWF_PLUGIN_DIR}/scripts/agent-slot-preflight.sh --required 2 --json
  • If preflight returns launch_mode=blocked, wait/close active agents and retry once.
  • If it returns launch_mode=multi_batch, run the batch sequentially agent-by-agent.
  • Otherwise keep the default parallel launch.

Batch 1 — launch with the preflight-selected mode (only for agents whose result files are missing or invalid):

  • Agent A — CDM Analysis: subagent_type: general-purpose, max_turns: 16. Read {SKILL_DIR}/references/cdm-guide.md, analyze Sections 1-3 summary + relevant cwf-state.yaml, write Section 4 content to {session_dir}/retro-cdm-analysis.md, append <!-- AGENT_COMPLETE -->.
  • Agent B — Learning Resources: subagent_type: general-purpose, max_turns: 20. Find 2-3 external resources using the Web Research Protocol in {CWF_PLUGIN_DIR}/references/agent-patterns.md, write Section 6 content to {session_dir}/retro-learning-resources.md, append <!-- AGENT_COMPLETE -->.

Wait for Batch 1 to complete. Read output files from session directory:

  • {session_dir}/retro-cdm-analysis.md — CDM analysis (needed by Batch 2 experts)
  • {session_dir}/retro-learning-resources.md — Learning resources

Gate behavior after Batch 1:

  • If retro-cdm-analysis.md remains invalid after retry: hard fail deep retro.
  • If retro-learning-resources.md remains invalid after retry: continue with warning and render Section 6 with explicit omission note.
  • Record gate path in output (PERSISTENCE_GATE=HARD_FAIL or PERSISTENCE_GATE=SOFT_CONTINUE, or equivalent wording).

Batch 2 — launch with the preflight-selected mode (after Batch 1, only for agents whose result files are missing or invalid):

  • Agent C — Expert alpha: subagent_type: general-purpose, max_turns: 20. Read {CWF_PLUGIN_DIR}/references/expert-advisor-guide.md + {SKILL_DIR}/references/expert-lens-guide.md, analyze Sections 1-4 summary (including CDM output), write to {session_dir}/retro-expert-alpha.md, append <!-- AGENT_COMPLETE -->.
  • Agent D — Expert beta: subagent_type: general-purpose, max_turns: 20. Same contract as Expert alpha; write to {session_dir}/retro-expert-beta.md, append <!-- AGENT_COMPLETE -->.

After Batch 2: read output files from session directory ({session_dir}/retro-expert-alpha.md, {session_dir}/retro-expert-beta.md). Draft Section 5 with the required agreement/disagreement synthesis subsection, then draft Section 7 inline (capability/tool scan), then integrate all results into retro.md.

Gate behavior after Batch 2:

  • If either expert file remains invalid after retry: continue with warning and render Section 5 from available expert output(s) plus explicit omission note.
  • Record soft gate path in output (PERSISTENCE_GATE=SOFT_CONTINUE or equivalent).

Rationale for 2-batch design: Expert Lens depends on CDM results. Batch 1 produces CDM + Learning in parallel, Batch 2 runs experts after CDM is available.

Section 1: Context Worth Remembering

Use section-writing guidance from section-authoring.md.

Section 2: Collaboration Preferences

Use section-writing guidance from section-authoring.md.

Section 3: Waste Reduction

Use section-writing guidance from section-authoring.md, including mandatory 5 Whys depth for major waste signals.

Section 4: Critical Decision Analysis (CDM)

Use section-writing guidance from section-authoring.md.

Section 5: Expert Lens

Use section-writing guidance from section-authoring.md. Agreement/disagreement synthesis subsection remains mandatory in deep mode.

Section 6: Learning Resources

Use section-writing guidance from section-authoring.md.

Section 7: Relevant Tools (Capabilities Included)

Use section-writing guidance from section-authoring.md, including capability inventory, gap classification, and action path.

5. Write retro.md

Write to {output-dir}/retro.md using the format below.

Immediately enforce deterministic retro artifact gate:

bash {CWF_PLUGIN_DIR}/scripts/check-run-gate-artifacts.sh \
  --session-dir "{output-dir}" \
  --stage retro \
  --strict \
  --record-lessons

If this gate fails, do not mark retro complete. Fix artifacts/mode labeling first, then re-run the gate.

6. Link Session Log

Discover runtime logs under:

  1. .cwf/sessions/
  • Prefer suffix files: {YYMMDD}-*.claude.md, {YYMMDD}-*.codex.md
  • Also allow unsuffixed files: {YYMMDD}-*.md

Then:

  1. Filter out already-symlinked candidates.
  2. Read a sample of each candidate to verify it matches the current session.
  3. Ensure {output-dir}/session-logs/ exists.
  4. For each verified log, create a relative symlink: ln -s "{relative-log-path}/{filename}" "{output-dir}/session-logs/{filename}"
  5. If no candidates or directories do not exist, skip silently.

7. Persist Findings

retro.md is session-specific. Persist findings to project-level improvements with a required ownership check before applying the eval > state > doc hierarchy.

7.0 Ownership Gate (Required, before tiering)

For each finding, classify ownership first:

  • owner=repo — the fix belongs to this repository's local artifacts/policies.
  • owner=plugin — the fix belongs to CWF plugin/runtime/shared tooling behavior.

Then set apply layer deterministically:

  • owner=repo -> apply_layer=local
  • owner=plugin -> apply_layer=upstream

Required metadata for every persist proposal:

  • owner
  • apply_layer
  • promotion_target
  • due_release
  • evidence (command output, artifact path, or session-log line)

Routing rules:

  • owner=repo: continue with tiering and local target updates.
  • owner=plugin: do not propose local AGENTS/doc edits as the primary fix. Output an upstream backlog item (issue/patch target under plugins/cwf/ or related shared runtime files). Local edits are allowed only as clearly marked stopgaps.
  • If ownership is ambiguous: default to owner=plugin, state uncertainty explicitly, and avoid adding repo-local policy noise.
  • Keep durable behavior contracts in AGENTS/runtime adapters. Keep next-session.md delta-focused; do not move global contracts there.

After ownership routing, evaluate enforcement mechanisms strongest-first:

  1. Tier 1: Eval/Hook (deterministic) — Can a script/hook catch this?

- check-session.sh / session_defaults for missing artifacts - PreToolUse/PostToolUse hook for tool usage patterns - Lint rule for style enforcement

  1. Tier 2: State (structural) — Does this change workflow state?

- cwf-state.yaml schema (new artifacts, stage transitions) - session_defaults (new always/milestone artifacts)

  1. Tier 3: Doc (behavioral, last resort) — Only for judgment calls

- project-context.md for architectural patterns - AGENTS.md or runtime adapter docs only for rules that can't be automated

Per-section persist actions:

  • S1 Context → project-context.md (Tier 3 — context is inherently behavioral). Offer to append new context.
  • S2 Collaboration → Classify owner first, then evaluate tier. AskUserQuestion "Apply?" for AGENTS.md/adapter changes only when owner=repo.
  • S3 Waste / Root causes → For each 5 Whys structural cause, present: "Finding: X. Owner: {repo|plugin}. Apply layer: {local|upstream}. Recommended tier: {1|2|3}. Mechanism: {specific change}. Evidence: {concrete trace}." Right-placement check: AGENTS.md (or runtime adapters) for behavioral rules, project-context.md for architectural patterns, protocol/skill docs for process changes.
  • S4 CDM → Key lessons through tiers (most → Tier 3 project-context.md).
  • S7 Tools → For owner=repo, AskUserQuestion "Implement now?". For owner=plugin, AskUserQuestion "Queue upstream issue/patch now?".

Expert Roster Maintenance (deep mode only, when Section 5 was produced):

  1. Extract expert names from Section 5 (Expert Lens) output
  2. Follow the Roster Maintenance procedure in {CWF_PLUGIN_DIR}/references/expert-advisor-guide.md (including the retro-specific gap analysis step)
  3. Report changes to the user in the retro output (Section 5 or post-section note) for visibility

8. Direct Invocation Report (Mandatory)

After writing retro.md, always report outcomes to the user.

If invocation_mode=direct (user-triggered /retro or cwf:retro):

  1. Provide Retro Brief with 4-6 bullets:

- session objective/result - top waste/root-cause signal - most important CDM lesson - critical tool/capability takeaway

  1. Provide Persist Proposals with 2-5 concrete items:

- Finding - Owner (repo, plugin) - Apply layer (local, upstream) - Promotion target (gate/script/doc/backlog endpoint) - Due release (or due date) - Recommended tier (Eval-Hook, State, Doc) - Evidence - Target file/script (local) or upstream backlog target (plugin) - Apply-now recommendation

  1. Ask whether to apply persist proposals now:

- repo-owned items: apply locally now? (yes/no) - plugin-owned items: queue upstream issue/patch now? (yes/no)

If invocation_mode=run_chain:

  • Provide compact 2-3 bullet completion report (pipeline continuity first), and include at least one concrete takeaway (waste/root-cause signal, CDM lesson, or next action).
  • Include a short Persist Proposals mini-list with 1-2 concrete items that each state owner/apply-layer/target (file or backlog). If no actionable item exists, state that explicitly.
  • Do not ask apply-now questions in run-chain mode; keep this report informative and hand off execution decisions to downstream run/ship flow.

9. Post-Retro Discussion

The user may continue the conversation after the retro. During post-retro discussion:

  • Update retro.md — append under ### Post-Retro Findings
  • Update lessons.md with new learnings
  • Ownership check first — for each new learning, classify owner/apply_layer, then evaluate through eval > state > doc.
  • If owner=plugin, append an upstream backlog note instead of adding repo-local policy prose.
  • For deep retro lessons, include metadata lines:

- - **Owner**: \repo|plugin` - - Apply Layer: \local|upstream - - Promotion Target: \... - - Due Release: \...`

  • If plugin code was changed, follow normal release procedures (version bump and release note updates in README/docs as needed)

Do not prompt the user to start this discussion.

Output Format

Use canonical templates from section-authoring.md for both light/deep modes.

Rules

  1. Never duplicate content already in lessons.md.
  2. Be specific — cite session moments, not generic advice.
  3. Keep each section focused; if there is no meaningful signal, state that briefly.
  4. AGENTS.md/runtime adapter changes require explicit user approval.
  5. Use the deterministic gate checklist in retro-gates-checklist.md for deep-mode artifacts, persistence tiering, and direct-invocation reporting requirements.
  6. For Section 5 in deep mode, use {SKILL_DIR}/references/expert-lens-guide.md and include the mandatory agreement/disagreement synthesis subsection.
  7. Language override: retro.md and deep-mode companion outputs are written in the user's language.

References

  • {SKILL_DIR}/references/cdm-guide.md — CDM probe methodology and output format
  • {SKILL_DIR}/references/expert-lens-guide.md — Retro-specific expert lens constraints and output format
  • section-authoring.md — Section 1-7 writing guidance and canonical light/deep output templates
  • retro-gates-checklist.md — Deterministic retro artifact gates and reporting checklist
  • expert-advisor-guide.md — Expert identity, grounding, selection, and retro mode format
  • agent-patterns.md — Shared agent orchestration patterns

平台分布

Codex

36.9%
按下载量换算50

Claude

29.83%
按下载量换算40

Cursor

17.77%
按下载量换算24

Gemini CLI

10.01%
按下载量换算14

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

可疑

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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