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 majiang213/OpenClaw-MAS --skill ckgit clone --depth 1 https://github.com/majiang213/OpenClaw-MASWrote 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/majiang213/openclaw-mas/ck)<a href="https://agentmods.dev/skills/majiang213/openclaw-mas/ck"><img src="https://agentmods.dev/badge/skills/majiang213/openclaw-mas/ck.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 | $0.00045 | $0.01283 |
| Opus 5 | $0.00023 | $0.00642 |
| Sonnet 5 | $0.00009 | $0.00257 |
| Haiku 4.5 | $0.00005 | $0.00128 |
Grade B, and why
ck scanned grade B with 1 finding 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 8d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
`~/.claude/settings.json` to auto-load project context on session start: This is a copy
91% identical to ck — 29 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ck — Context Keeper
You are the Context Keeper assistant. When the user invokes any /ck:* command,
run the corresponding Node.js script and present its stdout to the user verbatim.
Scripts live at: ~/.claude/skills/ck/commands/ (expand ~ with $HOME).
Data Layout
~/.claude/ck/
├── projects.json ← path → {name, contextDir, lastUpdated}
└── contexts/<name>/
├── context.json ← SOURCE OF TRUTH (structured JSON, v2)
└── CONTEXT.md ← generated view — do not hand-edit
Commands
/ck:init — Register a Project
node "$HOME/.claude/skills/ck/commands/init.mjs"
The script outputs JSON with auto-detected info. Present it as a confirmation draft:
Here's what I found — confirm or edit anything:
Project: <name>
Description: <description>
Stack: <stack>
Goal: <goal>
Do-nots: <constraints or "None">
Repo: <repo or "none">
Wait for user approval. Apply any edits. Then pipe confirmed JSON to save.mjs --init:
echo '<confirmed-json>' | node "$HOME/.claude/skills/ck/commands/save.mjs" --init
Confirmed JSON schema: {"name":"...","path":"...","description":"...","stack":["..."],"goal":"...","constraints":["..."],"repo":"..." }
/ck:save — Save Session State
This is the only command requiring LLM analysis. Analyze the current conversation:
summary: one sentence, max 10 words, what was accomplishedleftOff: what was actively being worked on (specific file/feature/bug)nextSteps: ordered array of concrete next stepsdecisions: array of{what, why}for decisions made this sessionblockers: array of current blockers (empty array if none)goal: updated goal string only if it changed this session, else omit
Show a draft summary to the user: "Session: '<summary>' — save this? (yes / edit)"
Wait for confirmation. Then pipe to save.mjs:
echo '<json>' | node "$HOME/.claude/skills/ck/commands/save.mjs"
JSON schema (exact): {"summary":"...","leftOff":"...","nextSteps":["..."],"decisions":[{"what":"...","why":"..."}],"blockers":["..."]}
Display the script's stdout confirmation verbatim.
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.
- commands/forget.mjs 1.3 KB runs code
- commands/info.mjs 650 B runs code
- commands/init.mjs 6.0 KB runs code
- commands/list.mjs 1.1 KB runs code
- commands/migrate.mjs 7.1 KB runs code
- commands/resume.mjs 949 B runs code
- commands/save.mjs 7.4 KB runs code
- commands/shared.mjs 15 KB runs code
- hooks/session-start.mjs 8.6 KB runs code
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.
- 8d ago First seen · 148 lines · 45 tokens per session scan B b0eecbd9841e
ck is a skill published in the GitHub repository majiang213/OpenClaw-MAS (5 stars, last pushed 5mo ago), licensed MIT. It adds 45 tokens to every session and 1,283 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). It is 91% identical to ck, differing in 29 lines, and is treated as a copy.
Other skills, from other repositories
self-improve
Extract lessons from the current session, or sweep the project's past sessions when asked, and route them to the appropriate knowledge layer (project AGENTS.md, auto memory, existing skills, or new skills). Use when the user asks to "self-improve", "distill this session", "distill past sessions", "sweep past…
save-md
Saves a named source to Markdown with provenance and faithful extraction through direct export endpoints. Use when asked to "save this article", "get the markdown", "transcribe this", or "keep this source". A URL supplied as task context alone does not trigger conversion; a chat summary stays in chat.
knowledge-base
Retrieves and updates project-specific prompt knowledge from comparison evidence and user feedback. Use only for prompt analysis or post-comparison learning within a Rashomon evaluation.
swarmclaw
AI agent runtime and multi-agent orchestration platform. Teaches agents how to use SwarmClaw's 6 primitive tools, persistent memory, dreaming, delegation, connectors, credentials, and the skill system. Use when an agent is running on SwarmClaw and needs to understand the platform's capabilities.
obs-memory
Persistent Obsidian-based memory for coding agents. Use at session start to orient from a knowledge vault, during work to look up architecture/component/pattern notes, and when discoveries are made to write them back. Activate when the user mentions obsidian memory, obsidian vault, obsidian notes, or /obs commands.…
apply
Use when a staged proposal has been reviewed and signed off — REVIEW.md Step 3 ticked reviewed or provisional — and is ready to promote into the live contextualizer.