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 chengkj99/kj-skills --skill wiki-intelligencegit 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/skills/chengkj99/kj-skills/wiki-intelligence)<a href="https://agentmods.dev/skills/chengkj99/kj-skills/wiki-intelligence"><img src="https://agentmods.dev/badge/skills/chengkj99/kj-skills/wiki-intelligence/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/skills/chengkj99/kj-skills/wiki-intelligence"><img src="https://agentmods.dev/badge/skills/chengkj99/kj-skills/wiki-intelligence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00061 | $0.01205 |
| Opus 5 | $0.00030 | $0.00602 |
| Sonnet 5 | $0.00012 | $0.00241 |
| Haiku 4.5 | $0.00006 | $0.00120 |
Grade A, and why
wiki-intelligence 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.
How it starts
The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wiki Intelligence
一套轻量 Claude Code hook，让每次对话都能为知识库增值。
功能
| 时机 | 行为 |
|---|---|
| 发送提示词前（UserPromptSubmit） | 识别高价值意图 → 调用 AI 评分 → 低分给出改进建议；高分静默收藏到 wiki |
| 回答结束后（Stop） | 分析对话价值 → 高分输出要点摘要 → 引导「确认沉淀」 |
| 会话开始（SessionStart） | 清理 24h 过期的会话状态文件 |
安装
# 1. 克隆 kj-skills（或已有则跳过）
git clone https://github.com/your-org/kj-skills.git
# 2. 一键安装
bash kj-skills/skills/wiki-intelligence/install.sh
# 3. 设置 wiki 路径
vim ~/.claude/wiki-intelligence.config.json
# 修改 "wiki_path" 为你的 wiki 绝对路径
# 4. 重启 Claude Code 生效
配置
唯一配置文件：~/.claude/wiki-intelligence.config.json
| 字段 | 默认值 | 说明 |
|---|---|---|
wiki_path |
(必填) | wiki 仓库根目录（支持 ~） |
quality_threshold |
7 |
提示词分数 ≥ 此值则收藏 |
knowledge_threshold |
6 |
对话分数 ≥ 此值则提示沉淀 |
high_value_intents |
见示例 | 触发质量检查的关键词列表 |
analysis_model |
claude-haiku-4-5-20251001 |
用于分析的模型（影响成本） |
enabled |
true |
全局开关 |
prompt_check_enabled |
true |
提示词质量检查开关 |
knowledge_capture_enabled |
true |
知识沉淀捕获开关 |
prompt_collection_enabled |
true |
好提示词自动收藏开关 |
prompt_collection_path |
wiki/playbooks/prompts |
wiki 内的提示词存储路径（相对） |
min_prompt_length |
20 |
短于此字符数的提示词跳过检查 |
Wiki 目录约定
好提示词写入 {wiki_path}/{prompt_collection_path}/ 下按意图分类：
wiki/playbooks/prompts/
├── design.md # 设计/架构类
├── analysis.md # 分析/研究类
├── planning.md # 规划/方案类
└── general.md # 其他
知识沉淀（「确认沉淀」触发）由 Claude 侧规则处理写入，hooks 只负责分析与提示。
运行测试
# 跳过需要 claude -p 的集成测试（在 Claude Code 内部运行时使用）
WI_SKIP_CLAUDE_TESTS=1 bash tests/test-wiki-intelligence.sh
# 完整测试（在 Claude Code 外部运行）
bash tests/test-wiki-intelligence.sh
文件结构
hooks/
├── prompt-quality.sh # UserPromptSubmit hook
├── knowledge-capture.sh # Stop hook
├── session-start-cleanup.sh # SessionStart hook
└── lib/
├── wiki-intelligence.sh # 分析引擎（共享库）
└── wiki-writer.sh # Wiki 写入工具
tests/
└── test-wiki-intelligence.sh
wiki-intelligence.config.example.json
install.sh
What ships with it
9 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.
- agents/openai.yaml 224 B
- hooks/knowledge-capture.sh 3.3 KB runs code
- hooks/lib/wiki-intelligence.sh 6.6 KB runs code
- hooks/lib/wiki-writer.sh 4.2 KB runs code
- hooks/prompt-quality.sh 2.3 KB runs code
- hooks/session-start-cleanup.sh 315 B runs code
- install.sh 3.5 KB runs code
- tests/test-wiki-intelligence.sh 4.1 KB runs code
- wiki-intelligence.config.example.json 706 B
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 · 108 lines · 61 tokens per session scan A d1ca3d84a33b
wiki-intelligence is a skill published in the GitHub repository chengkj99/kj-skills (14 stars, last pushed 10d ago), licensed MIT. It adds 61 tokens to every session and 1,205 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 2026-08-30.
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