Agent审查
- 作者仓库星标 267
- 作者更新于 实时读取
- 作者仓库 mini-diarium
- 领域
- AI 智能
- 兼容 Agent
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- 信任分
- 88 / 100 · 社区维护
- 作者 / 版本 / 许可
- @fjrevoredo · 未声明 license
- Token 消耗评级
- 低消耗
- 接入复杂程度
- 需简单配置
- 是否需要外部 API Key
- 不需要
- 兼容的系统
- macOS · Linux · Windows
- 底层运行要求
- Node.js
- 文件与系统权限
-
- 只读
- 允许写入 / 修改
- Shell 执行
- 网络行为
- 仅限本地
- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: skill-improver
description: | Turn every hard-earned lesson into a reusable improvement. After completing a non-trivial task…
category: AI 智能
runtime: Node.js
---
# skill-improver 输出预览
## PART A: 任务判断
- 适用问题:提示词、Agent 工作流、模型评估或自动化推理。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“When to Run / Workflow / Step 1 — Reflect”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于提示词、Agent 工作流、模型评估或自动化推理,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“When to Run / Workflow / Step 1 — Reflect”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、执行终端命令、主要在本地完成、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件、执行终端命令;主要在本地完成;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文没有稳定的斜杠命令要求。安装验证后通常全局生效,直接在对话里点名这个 Skill 并描述任务即可。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件、执行终端命令。
先用一个小任务确认它会围绕“When to Run / Workflow / Step 1 — Reflect”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: skill-improver
description: | Turn every hard-earned lesson into a reusable improvement. After completing a non-trivial task…
category: AI 智能
source: fjrevoredo/mini-diarium
---
# skill-improver
## 什么时候使用
- 把 AI / Agent方向的常用动作沉淀成 Agent 可调用的技能 适合处理AI Agent、提示词、模型评估与自动化推理,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查…
- 面向提示词、Agent 工作流、模型评估或自动化推理,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「When to Run / Workflow / Step 1 — Reflect」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件、执行终端命令;主要在本地完成;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "skill-improver" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> When to Run / Workflow / Step 1 — Reflect
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> Node.js | 读取文件、写入/修改文件、执行终端命令 | 主要在本地完成
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} Skill Improver
Turn every hard-earned lesson into a reusable improvement. After completing a non-trivial task (especially one that hit friction), run this skill to catalog what happened, classify the gaps, and apply fixes — either directly for obvious issues, or via a structured plan for larger changes.
When to Run
Proactive (run without being asked):
- A build, deploy, or CI job failed and was debugged
- A task took more than 3 rounds of trial-and-error
- A session lasted more than one hour and involved multiple skill uses
- The user explicitly expressed frustration or surprise at a gap
On-demand (run when the user says):
- "Reflect on this session" / "post-mortem" / "what went wrong"
- "Improve the skill" / "update the skill with these learnings"
- "Lessons learned" / "what should we change"
Scope: Reflect on ALL skills used during the session, plus any repo artifacts and process steps involved. If multiple skills were loaded, review each one. If the session didn't use any skill, focus on repo/process improvements only.
Workflow
Step 1 — Reflect
Catalog observations in three buckets, with concrete examples:
What went well:
- Patterns, tools, or decisions that saved time or prevented errors
- Skill instructions that proved particularly useful
- Diagnoses or fixes that were reached quickly
What went wrong:
- Mistakes, dead ends, or incorrect assumptions
- Skill instructions that were missing, wrong, or misleading
- Manual workarounds that had to be invented on the fly
What was missing:
- Scripts, checks, or tooling that would have caught the issue earlier
- Documentation or guardrails that didn't exist
- Process steps that were skipped or not automated
Step 2 — Classify
Group findings into three categories. For each finding, identify the concrete artifact that needs to change (file path, skill section, CI workflow, etc.).
Skill changes — improvements to an existing skill:
- Missing failure entries in a diagnosis table
- Wrong fix instructions
- Undocumented pitfalls or edge cases
- Better log access or debugging workflows
Repo artifact changes — new or modified files in the repository:
- Utility scripts (e.g.,
check-node-sources.mjs) - CI workflow steps or pre-release checks
- Configuration or lockfile validation
Process changes — workflow or convention changes:
- Release checklist items
- Pre-commit or pre-tag validation steps
- Cross-skill integration (e.g., pre-release skill should validate lockfiles)
Step 3 — Apply
If no improvements are identified: state that explicitly and stop. Do not invent changes.
The user can always override the plan/execute decision. If the user says "just fix it directly" for something that would normally need a plan, apply the changes directly instead. If the user says "make a plan" for something small, create one.
For obvious fixes (typos, missing warnings, incomplete instructions): Apply directly to the target file using the Edit tool. These are changes where:
- The fix is a single addition or correction to an existing section
- There's no design decision to make
- The change can't break anything else
- Example: adding a missing failure entry to a diagnosis table, or a warning about a known pitfall
For structural changes (new sections, new scripts, reorganized workflows): Create a plan using the manual-planning skill's format. These are changes where:
- The fix requires creating a new file or reorganizing existing content
- Multiple files are affected
- The user should review the approach before implementation
- Example: adding a new utility script, restructuring a skill's diagnosis workflow, adding pre-release steps
Step 4 — Verify
After applying fixes (directly or via plan execution):
- Run format/lint commands if the changed files are in checked languages
- For scripts, run a syntax check and a quick smoke test
- Re-read the changed skill sections to ensure they don't contradict other parts of the skill or adjacent skills
- Summarize what was changed and why
Output Format
At the end, present using this template:
## Session Reflection
### What Went Well
- [item]
### What Went Wrong
- [item]
### What Was Missing
- [item]
## Changes Made
| File | Change |
|------|--------|
| path/to/file | what changed and why |
<!-- If no changes were made: -->
No improvements identified.
If a plan was created, add: **Plan:** docs/plan-name.md — awaiting approval.
Gotchas
- Don't over-improve. If the session went smoothly and no concrete gaps were found, say so and stop. Inventing minor tweaks dilutes the skill.
- One session, one reflection. Don't chain multiple reflection cycles. If the user wants another, they'll ask.
- Obvious fix ≠ trivial preference. "I'd word this differently" is a preference, not a fix. Only apply direct edits when the current text is objectively wrong or missing.
- Respect the user's override. If the user says "just fix it" for something structural, apply directly. If they say "make a plan" for something small, create one. Their call always wins.
Integration with Other Skills
- Use manual-planning for any change that needs a plan (structural changes)
- Use todo-manager if the reflection surfaces new TODO items for the backlog
- The output format mirrors what you'd see in a good commit message: what, why, and where
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核