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 commands/linfee/spec-kit-cn/checklistgit clone --depth 1 https://github.com/Linfee/spec-kit-cnWhat 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 | $0.00014 | $0.04225 |
| Opus 5 | $0.00007 | $0.02112 |
| Sonnet 5 | $0.00003 | $0.00845 |
| Haiku 4.5 | $0.00001 | $0.00422 |
Grade A, and why
checklist 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 2d 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 — 291 lines — stays where its author put it; the contents beside it link to each section on GitHub.
清单目的: "需求编写的单元测试"
CRITICAL CONCEPT: 清单是需求编写的单元测试 - 它们验证特定领域中需求的质量, 清晰度和完整性.
不用于验证/测试:
- ❌ 不是"验证按钮点击正确"
- ❌ 不是"测试错误处理有效"
- ❌ 不是"确认 API 返回 200"
- ❌ 不是检查代码/实现是否符合规范
用于需求质量验证:
- ✅ "是否为所有卡片类型定义了视觉层次需求? "(完整性)
- ✅ "'突出显示'是否通过具体尺寸/位置进行了量化? "(清晰度)
- ✅ "所有交互元素的悬停状态需求是否一致? "(一致性)
- ✅ "是否为键盘导航定义了可访问性需求? "(覆盖度)
- ✅ "规范是否定义了 logo 图像加载失败时的处理? "(边缘情况)
比喻: 如果你的规范是用英文编写的代码, 那么清单就是它的单元测试套件. 你测试的是需求是否编写良好, 完整, 明确并准备好实施 - 而不是实现是否有效.
用户输入
$ARGUMENTS
在继续之前, 你必须考虑用户输入(如果不为空).
执行步骤
-
设置: 从仓库根目录运行
{SCRIPT}并解析JSON以获取FEATURE_DIR和AVAILABLE_DOCS列表.- 所有文件路径必须是绝对路径.
- 对于参数中的单引号如"I'm Groot", 使用转义语法: 例如 'I'''m Groot'(或者尽可能使用双引号: "I'm Groot").
-
澄清意图(动态): 推导最多三个初始上下文澄清问题(无预编目录). 它们必须:
- 从用户的表述 + 从规范/计划/任务中提取的信号生成
- 只询问实质上改变清单内容的信息
- 如果在
$ARGUMENTS中已经明确, 则单独跳过 - 优先考虑精确性而非广度
Generation algorithm:
- Extract signals: feature domain keywords (e.g., auth, latency, UX, API), risk indicators ("critical", "must", "compliance"), stakeholder hints ("QA", "review", "security team"), and explicit deliverables ("a11y", "rollback", "contracts").
- Cluster signals into candidate focus areas (max 4) ranked by relevance.
- Identify probable audience & timing (author, reviewer, QA, release) if not explicit.
- Detect missing dimensions: scope breadth, depth/rigor, risk emphasis, exclusion boundaries, measurable acceptance criteria.
- Formulate questions chosen from these archetypes:
- Scope refinement (e.g., "Should this include integration touchpoints with X and Y or stay limited to local module correctness?")
- Risk prioritization (e.g., "Which of these potential risk areas should receive mandatory gating checks?")
- Depth calibration (e.g., "Is this a lightweight pre-commit sanity list or a formal release gate?")
- Audience framing (e.g., "Will this be used by the author only or peers during PR review?")
- Boundary exclusion (e.g., "Should we explicitly exclude performance tuning items this round?")
- Scenario class gap (e.g., "No recovery flows detected—are rollback / partial failure paths in scope?")
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.
- 2d ago First seen · 291 lines · 14 tokens per session scan A 24eb2d338ead
checklist is a command published in the GitHub repository Linfee/spec-kit-cn (695 stars, last pushed 1mo ago), licensed MIT. It adds 14 tokens to every session and 4,225 once invoked, about $0.0001 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.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.