session-retro

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Review the full conversation and identify actionable improvements to the project's AI agent configuration and documentation.

Never delegate this skill to a subagent. The retro requires full conversation context.

复盘完整对话，识别可落地的项目AI Agent配置和文档改进项。

绝对不要将该技能委派给子Agent。 复盘需要完整的对话上下文。

Scan the session for:
- Corrections: where you were corrected or redirected.
- Repeated patterns: workflows or knowledge applied multiple times.
- Failed approaches: dead ends that future sessions should avoid.
- Discoveries: codebase knowledge, architectural insights, or debugging techniques learned during the session.
- Missing context: information you had to look up that should have been readily available.
- Costly research: topics where significant time or tokens were spent exploring the codebase or external sources. Propose adding results to
```
docs/knowledge-base/
```
  so future sessions start with the answer.
Every correction must produce at least one proposal. Re-scan the conversation to confirm none were missed.
Produce proposals only, each with: What, Why (evidence), Where (exact file), Risk.
Changes should follow the Guidelines

Present every proposal to the user using the multi-choice question tool (one question,
```
multiple: true
```
). Each option label is the proposal ID + short title; each description is a one-sentence summary.
Every correction received during the session must produce at least one proposal. Do not silently drop corrections.
No edits before explicit approval.

Prefer updating existing files over creating new ones.
Keep skills focused: one workflow per skill.
Keep docs factual and concise.
Do not add speculative content. Only propose changes backed by concrete conversation evidence.
Proposed text must match the target file's style and brevity. In particular,
```
AGENTS.md
```
changes must be minimal (one or two short lines per rule).
Use
```
.agents/skills/
```
for all agent conventions, including background knowledge (with
```
user-invocable: false
```
).

Skills (
```
.agents/skills/
```
): new skills for recurring workflows, or refinements to existing skills.
Human-readable docs (
```
docs/knowledge-base
```
): codebase knowledge, architecture guides, debugging playbooks, patterns. Anything useful to both humans and AI agents. Terms should be defined in
```
docs/knowledge-base/glossary.md
```
. Other topics should be organized into documents with relevant names. Closely related subjects should be grouped under subfolders with understandable names. When creating or updating a document, use markdown links to refer to the glossary.
Always-on rules (
```
AGENTS.md
```
): behavioral refinements to the agent interaction model. Keep changes minimal; this file should stay concise.