BC openclaw-administrator
Administration guide for the OpenClaw CLI. Use this skill whenever the user asks how to run, configure, or troubleshoot any openclaw command or concept, including: gateway and daemon lifecycle, setup and onboarding (interactive and headless/VPS), multi-agent setup and routing bindings, sub-agent spawning and delegation, workspace and bootstrap file management (AGENTS.md, SOUL.md, IDENTITY.md, USER.md, TOOLS.md), adding and configuring AI model providers, setting primary and fallback models, per-agent model overrides, the model allowlist, local models (Ollama/vLLM/LM Studio), custom providers via models.providers, the OpenAI-compatible HTTP endpoint (Open WebUI, LobeChat, LibreChat integration), channel login and connectivity, messaging, memory and wiki, plugins and skills, MCP servers, cron, tasks, flows, sandbox, browser automation, nodes, security audits, backups, and diagnostics. Also use for global flags (--dev, --profile, --container), command family routing, and any question about how openclaw subcommands work.
As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- Shorten the description to 1024 characters.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1032 chars, limit 1024 - warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Administration guide for the OpenClaw CLI. Use this skill whenever… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 61/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 5 mutating operations with no state check
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 70Execution cost. Instruction body is 4834 tokens
- 100Steps. 69 steps
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 2 branches, has a failure section
- 100Consistency. Name and required fields are in place
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 14 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (8 tags): a typed call is more reliable
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 1032: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +4Structure: 19 headings
- +3Step-by-step instructions: 69 items
- +4Has examples (20 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 48.