Borrowing it
Nothing to install: this file belongs to chengkj99/kj-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/chengkj99/kj-skills/main/.claude/commands/kj-help.mdgit clone --depth 1 https://github.com/chengkj99/kj-skillsWrote 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/commands/chengkj99/kj-skills/kj-help)<a href="https://agentmods.dev/commands/chengkj99/kj-skills/kj-help"><img src="https://agentmods.dev/badge/commands/chengkj99/kj-skills/kj-help/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/chengkj99/kj-skills/kj-help"><img src="https://agentmods.dev/badge/commands/chengkj99/kj-skills/kj-help.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00021 | $0.00345 |
| Opus 5 | $0.00010 | $0.00172 |
| Sonnet 5 | $0.00004 | $0.00069 |
| Haiku 4.5 | $0.00002 | $0.00034 |
Grade A, and why
kj-help scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
扫描本插件 skills/ 目录下的所有 skill,动态生成清单(不要使用任何写死的列表)。
执行步骤:
-
运行以下命令,逐个读取每个 skill 的
description:for f in skills/*/SKILL.md; do d=$(basename "$(dirname "$f")") desc=$(awk '/^description:/{flag=1; sub(/^description:[ ]*/,""); print; next} flag&&/^[a-zA-Z_-]+:/{exit} flag{print}' "$f" | tr '\n' ' ' | sed 's/^[">|-]*[ ]*//') echo "$d :: $desc" done -
把结果整理成 Markdown 表格,按目录名排序,
用途取 description 的核心意图,精简到一句话(约 30–40 字):目录 用途 -
表格下方追加一行提示:「请用 Read 打开对应目录的
SKILL.md再执行;若某 skill 带disable-model-invocation,需用户显式 @ 才会触发,以各 SKILL frontmatter 为准。」 -
若发现异常(某目录缺
SKILL.md、name与目录名不一致、描述为空),在表格后用一行 ⚠️ 单独指出,便于维护。
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.
- 11d ago First seen · 27 lines · 21 tokens per session scan A b1b49c16b2cf
kj-help is a command published in the GitHub repository chengkj99/kj-skills (14 stars, last pushed 10d ago), licensed MIT. It adds 21 tokens to every session and 345 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
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.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.