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/xiqin/loom/loom-using-loomnpx skills add xiqin/loom --skill loom-using-loomgit clone --depth 1 https://github.com/xiqin/loomWrote 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/xiqin/loom/loom-using-loom)<a href="https://agentmods.dev/skills/xiqin/loom/loom-using-loom"><img src="https://agentmods.dev/badge/skills/xiqin/loom/loom-using-loom.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 | $0.00059 | $0.01229 |
| Opus 5 | $0.00030 | $0.00615 |
| Sonnet 5 | $0.00012 | $0.00246 |
| Haiku 4.5 | $0.00006 | $0.00123 |
Grade A, and why
loom-using-loom 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 6d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Using loom — AI 工程化框架
loom 是一个 AI 工程化框架，把需求、规范、上下文、执行过程"织"成一套稳定工程流程。流水线由 .loom/workflow.yaml 集中定义。
严令禁止跳步
严令禁止跳过任何步骤。每个步骤完成后必须显式触发下一步，不可自行终止。
Skills 清单
所有 skills 通过 / 命令或 Skill 工具调用。详见 .loom/skills/ 目录（完整定义）
核心流水线 Skills：
| Skill | 输出 | 说明 |
|---|---|---|
| loom-brainstorming | specs/<date+feature>/spec.md |
需求头脑风暴, +可视化伴侣、设计自检、用户审查 Gate |
| loom-detail-expansion | specs/<date+feature>/requirements.json |
按 15 维度展开 Behavior Obligation，补齐 test_plan 与 applicability |
| loom-writing-plans | specs/<date+feature>/plan.md |
分层拆解 task, +模型选择、类型一致性检查 |
| loom-analyze-artifacts | specs/<date+feature>/artifact-analysis.json |
planning 后审批前跨产物一致性只读分析 |
| loom-using-git-worktrees | feature 分支 | 创建隔离分支, +测试基线验证 |
| loom-subagent-driven-development | 源码 + 测试报告 | Subagent 派发 + 双重审查,独立模板文件、4种状态处理 |
| loom-converge | specs/<date+feature>/convergence-report.json |
executing 后 verification 前对照意图清单，missing/partial 回流 executing |
| loom-omission-hunter | specs/<date+feature>/findings/omission-hunter.json |
只读对抗式审查，负空间检查（应存在但不存在） |
| loom-verification-before-completion | 验证报告 | 完成前验证, +Spec覆盖、类型一致性、编译测试 |
| loom-index-update | codegraph 同步 + 结构化记忆 | codegraph 同步 |
辅助 Skills：
| Skill | 说明 |
|---|---|
| loom-init-project | 项目初始化（扫描 + 生成宪章/记忆/入口） |
| loom-router | 轻量入口路由（分流到 skill 或 pipeline selector，不写流水线状态） |
| loom-pipeline-selector | 开发流水线步骤选择（确认后写入 dynamic_steps） |
| loom-using-loom | loom 框架使用指南（本 skill） |
通用 Skills：
| Skill | 说明 |
|---|---|
| loom-test-driven-development | TDD 测试驱动开发，+流程图、好/坏示例、常见借口表 |
| loom-systematic-debugging | 系统化调试, +4阶段流程图、条件等待、纵深防御 |
| loom-requesting-code-review | 请求代码审查, +预审查清单、审查模板 |
| loom-receiving-code-review | 接受代码审查, +响应模板、流程图 |
| loom-dispatching-parallel-agents | 并行 agent 派发, +模型选择、并发工作流图 |
| loom-writing-skills | 编写自定义 skills, +方法论深度、流程图 |
| loom-finishing-a-development-branch | 分支完成流程 , +选项展示（Merge/PR/Keep/Discard） |
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.
- 6d ago First seen · 82 lines · 59 tokens per session scan A 8950be2f177a
loom-using-loom is a skill published in the GitHub repository xiqin/loom (5 stars, last pushed 1mo ago), licensed MIT. It adds 59 tokens to every session and 1,229 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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