Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/lync-cyber/cataforge/task-dep-analysisnpx skills add lync-cyber/CataForge --skill task-dep-analysisgit clone --depth 1 https://github.com/lync-cyber/CataForgeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lync-cyber/cataforge/task-dep-analysis)<a href="https://agentmods.dev/skills/lync-cyber/cataforge/task-dep-analysis"><img src="https://agentmods.dev/badge/skills/lync-cyber/cataforge/task-dep-analysis.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00045 | $0.01364 |
| Opus 5 | $0.00023 | $0.00682 |
| Sonnet 5 | $0.00009 | $0.00273 |
| Haiku 4.5 | $0.00005 | $0.00136 |
Grade A, and why
task-dep-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
任务依赖分析 (task-dep-analysis)
能力边界
- 能做: 任务间依赖关系建模、拓扑排序、关键路径计算、循环依赖检测、Sprint分组建议
- 不做: 任务内容定义、代码实现、代码模块依赖图(→ code-review scan --focus coupling)
输入规范
- dev-plan#§1 Sprint任务表(任务ID + 依赖列)
- dev-plan#§2 依赖图(文本DAG关系)
- 任务卡的depends_on字段(如存在)
输出规范
- 环检测结果(通过/失败 + 循环路径)
- 拓扑排序(有效执行顺序)
- 关键路径(基于复杂度权重)
- Sprint分组建议(按拓扑层级和并行度)
- 落盘: 上述产物经 §执行流程写入 dev-plan 文档对应章节(依赖图 Mermaid → dev-plan#§2、关键路径与 Sprint 分组 → dev-plan#§4)
执行流程
Step 1: 提取依赖数据
数据源(自动):
- 优先经图谱取依赖边 — 用 context 的 query 分支把"列出所有任务依赖边(T→T)"翻译为只读追溯查询并执行,返回的 src→dst 对直接拼成
--edges "T-001→T-002,...",无需再读 Markdown。 - 回退读文档 — 追溯后端不可用时,从 dev-plan#§1 Sprint 任务表(任务 ID + 依赖列)、§2 依赖图(文本 DAG,T-001 ─→ T-002)、任务卡
depends_on字段提取,合并去重成边列表。
任一路径都必须输出边列表((src, dst) 元组),交给 Step 2 的脚本。
Step 2: 运行依赖分析脚本
调用约定(单一入口): 一律通过 cataforge skill run <skill-id> -- <args> 触发,由框架解析 SKILL.md 元数据并派发到内置脚本或项目覆写脚本。不得直接 python .cataforge/skills/.../scripts/*.py——该路径为框架内部实现细节,不保证存在。
使用Bash执行:
cataforge skill run task-dep-analysis -- \
--edges "T-001→T-002,T-002→T-003,..." \
[--weights "T-001:S,T-002:M,T-003:L,..."] \
[--format json]
脚本功能:
- 环检测(DFS): 输出循环路径或PASS
- 拓扑排序(Kahn算法): 输出有效执行顺序
- 关键路径计算: 基于复杂度权重(S=1,M=2,L=3,XL=5)
- Sprint分组建议: 按拓扑层级和并行度分组
输出: --format json(默认且唯一)输出 JSON 结构化分析数据。依赖图的 Mermaid 可视化由 cataforge viz tasks --format mermaid --edges "..." 产出(同一图算法、同一关键路径高亮)。
JSON输出示例:
{
"cycle_detected": false,
"cycles": [],
"topological_order": ["T-001","T-002"],
"critical_path": ["T-001","T-003"],
"critical_path_weight": 7,
"sprint_groups": [["T-001","T-004"],["T-002","T-005"]]
}
cataforge viz tasks --format mermaid 输出示例:
graph LR
T-001 --> T-002
T-001 --> T-003
T-003 --> T-005
style T-001,T-003,T-005 fill:#f96,stroke:#333,stroke-width:2px
Step 3: 应用分析结果
- 有环 → 报告环路径,建议打破方式,status=blocked
- 无环 → 执行以下操作:
- 使用
cataforge viz tasks --format mermaid --edges "..."获取 Mermaid 依赖图 - 通过
cataforge context write-narrative将 Mermaid 图写入 dev-plan §2(包裹在```mermaid代码块中) - 使用
cataforge skill run task-dep-analysis -- --format json获取关键路径和 Sprint 分组数据 - 将关键路径信息写入 dev-plan#§4
- 使用
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 97 lines · 45 tokens per session scan A 4deea412793a
task-dep-analysis is a skill published in the GitHub repository lync-cyber/CataForge (128 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 1,364 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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