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/appletechie/perfect-goal/openclawnpx skills add appletechie/perfect-goal --skill openclawgit clone --depth 1 https://github.com/appletechie/perfect-goalWrote 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/appletechie/perfect-goal/openclaw)<a href="https://agentmods.dev/skills/appletechie/perfect-goal/openclaw"><img src="https://agentmods.dev/badge/skills/appletechie/perfect-goal/openclaw.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 | $0.00133 | $0.03499 |
| Opus 5 | $0.00067 | $0.01750 |
| Sonnet 5 | $0.00027 | $0.00700 |
| Haiku 4.5 | $0.00013 | $0.00350 |
Grade A, and why
openclaw 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 4d 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 — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenClaw — Working Knowledge
OpenClaw is a Node/TypeScript-based agent runtime that hosts multiple agents per gateway. It runs on both Linux (docker containers on ubuntu-root) and macOS (native installs on mac-studio + vm-1/turkules). This skill compresses the high-leverage knowledge for authoring openclaw plugins, navigating the Mac boot-headless trio, and avoiding the traps that cost real engineering time.
If you're filing a multi-step goal involving openclaw, invoke /perfect-goal after reading this skill. They compose.
Codebase layout
OpenClaw plugins live at the root of moltbot-infra:
moltbot-infra/
├── plugins/ # OpenClaw plugins (canonical location)
│ ├── mc-manifest/ # Posts gateway manifest → MC every 60s
│ ├── mc-worker/ # Pulls + executes MC tasks
│ ├── mc-remote/ # MC-side remote control
│ ├── workspace-api/ # Workspace introspection
│ └── anthropic-attribution-headers/ # PARKED — pending LiteLLM /v1/messages fix
├── openclaw/
│ ├── overlays/ # Per-gateway runtime overrides
│ │ ├── aurora.json
│ │ ├── sam.json
│ │ └── enduru.json
│ └── scripts/ # openclaw-setup, deploy-mc-manifest.sh, etc.
├── mac/ # Boot-headless installers (Macs only)
│ ├── install-mc-bridge-daemon.sh
│ ├── install-openclaw-gateway-daemon.sh
│ ├── migrate-to-official-tailscale-pkg.sh
│ ├── clean-tailscale-reinstall.sh
│ └── install-daily-restart-*.sh
└── scripts/
└── deploy-mc-manifest.sh
Topology — Mac vs Linux
Linux (ubuntu-root, dokploy-root): OpenClaw runs as docker containers. 3 customer gateways currently — aurora, sam, enduru. Reach via docker exec <name> NOT SSH (see [[reference_openclaw_gateways_topology]]).
Mac (mac-studio at 100.85.126.47, vm-1/turkules at 100.87.215.64): OpenClaw runs as a system LaunchDaemon. Native install. Each Mac runs one gateway with multiple agents:
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.
- 4d ago First seen · 226 lines · 133 tokens per session scan A 546e89757620
openclaw is a skill published in the GitHub repository appletechie/perfect-goal (2 stars, last pushed 3mo ago), licensed MIT. It adds 133 tokens to every session and 3,499 once invoked, about $0.0007 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…