Agent测试
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- 作者仓库 aeon
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- 通用 · meta · dev
- 兼容 Agent
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- Claude Code
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- Gemini CLI
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- 94 / 100 · 已通过审计
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- @aaronjmars · 未声明 license
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- 低消耗
- 接入复杂程度
- 需简单配置
- 是否需要外部 API Key
- 需要 · GitHub
- 兼容的系统
- macOS · Linux · Windows
- 底层运行要求
- Node.js
- 文件与系统权限
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- 只读
- 允许写入 / 修改
- 网络行为
- 允许外网请求
- 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。
---
name: Skill Dependency Graph
description: Generate a navigable Mermaid dependency map of all skills with change detection, per-category dr…
category: 通用
runtime: Node.js
---
# Skill Dependency Graph 输出预览
## PART A: 任务判断
- 适用问题:通用任务拆解、检查和交付。
- 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“Steps / 1. Fingerprint inputs and check for change / 2. Parse all inputs (explicit + derived)”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通用任务拆解、检查和交付,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“Steps / 1. Fingerprint inputs and check for change / 2. Parse all inputs (explicit + derived)”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、会按任务需要访问外部网络、需要准备 GitHub API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件;会按任务需要访问外部网络;需要准备 GitHub 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。 原文出现了 `/tmp` 这类斜杠命令;如果你的 Agent 支持命令触发,优先用命令开场,再补充目标和边界。
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。
先用一个小任务确认它会围绕“Steps / 1. Fingerprint inputs and check for change / 2. Parse all inputs (explicit + derived)”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 Dependency Graph
description: Generate a navigable Mermaid dependency map of all skills with change detection, per-category dr…
category: 通用
source: aaronjmars/aeon
---
# Skill Dependency Graph
## 什么时候使用
- 把通用方向的常用动作沉淀成 Agent 可调用的技能 适合处理通用任务拆解、检查、交付和复盘,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。 围绕 meta、dev 组织上下文、步骤和验收口径;使用前…
- 面向通用任务拆解、检查和交付,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「Steps / 1. Fingerprint inputs and check for change / 2. Parse all inputs (explicit + derived)」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件;会按任务需要访问外部网络;需要准备 GitHub 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 Dependency Graph" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Steps / 1. Fingerprint inputs and check for change / 2. Parse all inputs (explicit + derived)
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 | 会按任务需要访问外部网络
安全层 -> 需要准备 GitHub 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
} ${var} — Output path override. If empty, writes to
docs/skill-graph.md.
Today is ${today}. Generate a navigable, decision-ready Mermaid map of all Aeon skills. Skip notify and PR when nothing changed.
Steps
1. Fingerprint inputs and check for change
Build an input fingerprint:
{
sha1sum aeon.yml skills.json
for f in skills/*/SKILL.md; do
awk '/^---$/{n++;next} n==1{print FILENAME": "$0}' "$f" # frontmatter only
grep -hE '^depends_on:|^- skill:|consume:|parallel:|trigger:' "$f" || true
grep -hoE 'memory/(topics|state)/[a-zA-Z0-9_.-]+' "$f" | sort -u
done | sha1sum
} > /tmp/skill-graph.fingerprint
Compare against memory/topics/skill-graph-state.json (key input_fingerprint). If identical:
- Append
## skill-graphblock tomemory/logs/${today}.md:SKILL_GRAPH_NO_CHANGE — N skills, identical fingerprint - Exit silently. No notify. No PR. No file rewrite.
If state file is missing → mode = SKILL_GRAPH_NEW. Otherwise → mode = SKILL_GRAPH_OK.
2. Parse all inputs (explicit + derived)
Explicit edges:
aeon.yml→ per-skillenabled,schedule,var,model;chains:blocks (steps:,consume:,parallel:);reactive:blocks (trigger:,on:,when:)- Each
skills/*/SKILL.md→ frontmattername,tags,depends_on:array
Derived edges (this is the leverage):
- For each skill, grep
memory/topics/*.mdandmemory/state/*.jsonreferences. Classify as write if surrounding 3 lines match(write|save|append|>|update)\b.*(topics|state)/, else read. Awrite→topicfrom skill A and aread→same topicfrom skill B yields a shared-state edgeA -..-> B. - Skills tagged
researchwriting toarticles/*.md(or havingarticles/in their output description) → automatic content-pipeline edges tosyndicate-article,rss-feed,update-gallery. - Every skill writes
memory/cron-state.json— collapse this into a single legend note rather than 90 edges toheartbeat/skill-health/skill-repair.
3. Categorize via skills.json
Use skills.json as the canonical category map (research, dev, crypto, social, productivity). For skills not in skills.json, fall back to the first matching tag.
4. Lint before write
Before writing any Mermaid, validate:
- Every
[label]declaration has matching brackets - Every edge
A --> Breferences nodes declared in some subgraph - Every
click X "..."directive references a declared node and a path that exists on disk - Every subgraph block opens with
subgraphand closes withend
If any lint check fails → mode = SKILL_GRAPH_ERROR, abort write, notify with the failing rule, exit.
5. Generate the multi-diagram document
Write to docs/skill-graph.md (or ${var}). Structure:
- Header — title,
Auto-generated by skill-graph on ${today}, current mode - Verdict line — one of:
ARCHITECTURE_OK(no structural change) /NEW_SKILLS: a, b/RETIRED_SKILLS: c/NEW_DEPS: A→B, .../NEW_ENABLED: x - What changed since last run — diff against prior
docs/skill-graph.md: added/removed nodes, added/removed edges, enabled-state flips. Skip section onSKILL_GRAPH_NEW. - Overview diagram —
flowchart LRwith 5 category subgraph boxes (no inner nodes) + cross-category edges + edge counts as labels - Self-healing loop callout — small dedicated
flowchart LRshowingheartbeat → skill-health → skill-evals → skill-repair → self-improvewith the sharedcron-state.jsonas a labeled state node - Per-category mini-diagrams — one
flowchart LRper category. Inside: all nodes for that category, intra-category edges as solid/dashed/dotted, cross-category dependencies shown as faded:::externalghost nodes pointing into a side cluster - Click-through directives — every node in every diagram gets
click slug "../skills/slug/SKILL.md"(Mermaid renders as hyperlinks on github.com) - Enabled overlay — Mermaid classes:
class slug enabled(bold border, schedule annotation in label) for skills withenabled: true;class slug disabled(faded grey) for the rest. Class definitions:classDef enabled fill:#fff,stroke:#000,stroke-width:2px,color:#000 classDef disabled fill:#f5f5f5,stroke:#bbb,color:#888 classDef external fill:none,stroke:#bbb,stroke-dasharray:3 3,color:#888 - Legend — edge types (
-->depends_on,-.->consume,-..->reactive/shared-state); enabled vs disabled visual; click-to-source note - Summary table — total skills, by category, by status (enabled/disabled), edges by type
- Source-status footer —
skills parsed: N · depends_on: X · consume: Y · reactive: Z · shared-state derived: W · enabled: E/N · mode: SKILL_GRAPH_{OK,NEW,NO_CHANGE,ERROR}
6. Update README idempotently
if ! grep -q 'docs/skill-graph.md' README.md; then
# insert under "Skills" header if present, else append
...
fi
Never re-insert. Never reformat existing lines.
7. Persist state
Write memory/topics/skill-graph-state.json:
{
"generated_at": "${today}",
"input_fingerprint": "<sha1>",
"skills_total": 96,
"enabled_count": 1,
"edges": { "depends_on": 4, "consume": 4, "reactive": 1, "shared_state": 12 },
"node_list_sha": "<sha1 of sorted slugs>",
"edge_list_sha": "<sha1 of sorted edge tuples>"
}
Used next run for change detection (step 1).
8. Branch, commit, PR
git checkout -b skill-graph/${today} 2>/dev/null || git checkout skill-graph/${today}
git add docs/skill-graph.md memory/topics/skill-graph-state.json README.md
git commit -m "docs(skill-graph): regenerate map (${verdict_one_line})"
git push -u origin skill-graph/${today}
gh pr create --title "docs(skill-graph): ${verdict_one_line}" --body "..."
PR body includes: verdict line, what-changed diff, summary table, source-status footer.
9. Notify (gated)
SKILL_GRAPH_NO_CHANGE→ no notify (already exited at step 1)SKILL_GRAPH_NEW→ notify:*Skill Graph initialized* — ${N} skills mapped across 5 categories. PR: ${url}SKILL_GRAPH_OK→ notify only if verdict is notARCHITECTURE_OK:*Skill Graph updated* — ${verdict_one_line}. PR: ${url}SKILL_GRAPH_ERROR→ notify:*Skill Graph FAILED* — lint: ${rule}. No PR opened.
10. Log
Append to memory/logs/${today}.md:
### skill-graph
- Mode: SKILL_GRAPH_{OK|NEW|NO_CHANGE|ERROR}
- Verdict: ${verdict_one_line}
- Skills: ${N} (enabled: ${E})
- Edges: depends_on=${X}, consume=${Y}, reactive=${Z}, shared_state=${W}
- PR: ${url or "—"}
- Source-status: ${footer}
Sandbox note
No external APIs needed — all inputs come from local files. Standard git + gh CLI for branch/PR creation (already authenticated via GITHUB_TOKEN).
Constraints
- State file:
memory/topics/skill-graph-state.json— auto-created on first run; safe to delete to force a full regeneration (next run will fall through toSKILL_GRAPH_NEW). - Never silently regress an already-good output. If lint fails, abort with
SKILL_GRAPH_ERRORrather than commit a broken diagram. SKILL_GRAPH_NO_CHANGEis the most common path on a stable architecture and must be silent — no PR, no notify, just a log line. Operator trains to trust the silence.- Click-through paths must be relative from the output file's directory (e.g.
../skills/X/SKILL.mdfromdocs/skill-graph.md) so they resolve on github.com. - Enabled state comes from
aeon.ymlonly — never infer from cron-state or recent runs (a skill can be enabled but not yet run). - Do not expand
every skill writes cron-state.jsoninto N edges — collapse into one legend note. The graph is a map, not an audit log.
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