技能 Dependency Gr
- 作者仓库星标 430
- 作者仓库 aeon
<!-- autoresearch: variation B — sharper output via change detection + per-category diagrams + enabled overlay + click-through + diff-vs-prior -->${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: ${footer}
Sandbox note
No external APIs needed — all inputs come from local files. Standard git + gh CLI for branch/PR creation (already authenticated via GITHUB_TOKEN).
Constraints
- State file:
memory/topics/skill-graph-state.json— auto-created on first run; safe to delete to force a full regeneration (next run will fall through toSKILL_GRAPH_NEW). - Never silently regress an already-good output. If lint fails, abort with
SKILL_GRAPH_ERRORrather than commit a broken diagram. SKILL_GRAPH_NO_CHANGEis the most common path on a stable architecture and must be silent — no PR, no notify, just a log line. Operator trains to trust the silence.- Click-through paths must be relative from the output file's directory (e.g.
../skills/X/SKILL.mdfromdocs/skill-graph.md) so they resolve on github.com. - Enabled state comes from
aeon.ymlonly — never infer from cron-state or recent runs (a skill can be enabled but not yet run). - Do not expand
every skill writes cron-state.jsoninto N edges — collapse into one legend note. The graph is a map, not an audit log.
- 流狐分类
- 通用 · meta · dev
- 作者声明 Agent
- 未找到明确声明;不据此推断已兼容或已测试
- 静态检查
- 94 / 100 · 启发式扫描,不代表运行安全
- 作者 / 版本 / 许可
- @aaronjmars · 未声明 license
- 流狐 Token 估算
- 低消耗
- 流狐接入估算
- 需简单配置
- 是否需要外部 API Key
- 需要 · GitHub
- 检测到的系统要求
- macOS · Linux · Windows
- 底层运行要求
- Node.js
- 检测到的文件与系统行为
-
- 只读
- 允许写入 / 修改
- 检测到的网络行为
- 允许外网请求
- 安装命令数
- 无(仅作为资料)
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
作者没有在当前 SKILL.md 中定义固定输出样例。 Steps
Build an input fingerprint: Compare against memory/topics/skill-graph-state.json (key inputfingerprint). If identical: Append skill-graph block to memory/logs/${today}.md: SKILLGRAPHNOCHANGE — N skills, identical fingerprint
Explicit edges: aeon.yml → per-skill enabled, schedule, var, model; chains: blocks (steps:, consume:, parallel:); reactive: blocks (trigger:, on:, when:) Each skills//SKILL.md → frontmatter name, tags, dependson: array
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.
Before writing any Mermaid, validate: Every [label] declaration has matching brackets Every edge A --> B references nodes declared in some subgraph
Write to docs/skill-graph.md (or ${var}). Structure: Header — title, Auto-generated by skill-graph on ${today}, current mode Verdict line — one of: ARCHITECTUREOK (no structural change) / NEWSKILLS: a, b / RETIREDSKILLS: c / NEWDEPS: A→B, ... / NEWENABLED: x
> **${var}** — Output path override. If empty, writes to `docs/skill-graph.md`.
<!-- autoresearch: variation B — sharper output via change detection + per-category diagrams + enabled overlay + click-through + diff-vs-prior -->
Today is ${today}. Generate a navigable, decision-ready Mermaid map of all Aeon skills. Skip notify and PR when nothing changed.
## Steps
### 1. Fingerprint inputs and check for change
Build an input fingerprint:
```bash
{
sha1sum aeon.yml skills.json
for f in skills/*/SKILL.md; do
awk '/^---$/{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-graph` block to `memory/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-skill `enabled`, `schedule`, `var`, `model`; `chains:` blocks (`steps:`, `consume:`, `parallel:`); `reactive:` blocks (`trigger:`, `on:`, `when:`)
- Each `skills/*/SKILL.md` → frontmatter `name`, `tags`, `depends_on:` array
**Derived edges (this is the leverage):**
… 作者原文负责流程事实;流狐只索引当前章节、要点、文件与命令。
章节 -> Steps → 1. Fingerprint inputs and check for change → 2. Parse all inputs (explicit + derived) → 3. Categorize via skills.json → 4. Lint before write → 5. Generate the multi-diagram document
要点 -> ${var} · Exit silently. No notify. No PR. No file rewrite. · Explicit edges · Derived edges (this is the leverage) · write · read · Header · Verdict line
文件/命令 -> docs/skill-graph.md · memory/topics/skill-graph-state.json · inputfingerprint · ## skill-graph · memory/logs/${today}.md · SKILLGRAPHNOCHANGE — N skills, identical fingerprint · SKILLGRAPHNEW · SKILLGRAPHOK
内容 SHA-256 -> da719a14473e
方法与流程
适用与边界
原文中的明确线索
docs/skill-graph.md、memory/topics/skill-graph-state.json、inputfingerprint、## skill-graph、memory/logs/${today}.md、SKILLGRAPHNOCHANGE — N skills, identical fingerprint、SKILLGRAPHNEW、SKILLGRAPHOK