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 skills add jianchen08/Agent-os-open --skill skill-task-chain-viewergit clone --depth 1 https://github.com/jianchen08/Agent-os-openWrote 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/jianchen08/agent-os-open/skill-task-chain-viewer)<a href="https://agentmods.dev/skills/jianchen08/agent-os-open/skill-task-chain-viewer"><img src="https://agentmods.dev/badge/skills/jianchen08/agent-os-open/skill-task-chain-viewer.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 5.1 | $0.00066 | $0.00686 |
| Opus 5 | $0.00033 | $0.00343 |
| Sonnet 5 | $0.00013 | $0.00137 |
| Haiku 4.5 | $0.00007 | $0.00069 |
Grade A, and why
任务链可视化 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 3d 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.
What it actually says
任务链可视化
本技能是流程指引，不是逐条打勾清单：按场景判断使用，遇不适用情况保持裁量，不机械执行。
描述
读取方案规划阶段产出的任务文件（docs/tasks/task_XX_*.md，含 YAML frontmatter）
和项目文档（.project/*.md），生成一个自包含的交互式 HTML 页面（所有
CSS/JS 内联，无外部依赖，可离线打开），供用户在方案确认前审阅：
- 任务全貌与状态分布
- 任务间依赖拓扑（可点击节点跳转详情）
- AC 规模概览（正文里出现的 AC 编号总数、其中带 traces_to 追溯的条目数）， 用于快速感知覆盖规模。注意：本工具不读取方案文档的「方案级 AC 列表」， 无法判断某条方案级 AC 是否无人覆盖——AC 死角分析需人工对照方案文档。
脚本
generate_task_chain_html.py
主脚本。解析任务文件 frontmatter，渲染 HTML。
调用方式：
python skills/skill-task-chain-viewer/scripts/generate_task_chain_html.py --title "项目名称"
参数：
| 参数 | 必填 | 说明 |
|---|---|---|
--title |
否 | 页面标题，默认「项目任务链」 |
--tasks-dir |
否 | 任务文件目录，默认 docs/tasks/ |
--project-dir |
否 | 项目文档目录，默认 .project/ |
--output |
否 | 输出路径，默认 docs/working/{title}_task_chain.html |
使用场景
- 方案规划完成后，提交给用户确认前，生成可视化让用户一眼看清任务结构和 AC 覆盖规模
- 执行过程中重新生成，查看任务状态进展
- 感知 AC 追溯规模（带 traces_to 的 AC 数占比）。AC 死角分析需人工对照方案文档
注意
- 任务文件应包含 YAML frontmatter（
task_id/task_name/executor/depends_on/status）； 缺失字段时以默认值（空串 / pending）兜底，任务仍会渲染，但元信息不完整 - 无法读取的任务文件（编码错误等）会在 stderr 输出警告并跳过，不影响其他任务渲染
- 依赖拓扑用 SVG 内联绘制，不依赖任何 CDN 或外部库；检测到依赖环会在 stderr 报警
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago Changed · +2 lines 893d5b11a271
- 8d ago First seen · 53 lines · 66 tokens per session scan A ff8c8c757981
任务链可视化 is a skill published in the GitHub repository jianchen08/Agent-os-open (5 stars, last pushed 4d ago), licensed Apache-2.0. It adds 66 tokens to every session and 686 once invoked, about $0.0003 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 2026-08-31.
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