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BD OpenClaw Mastery — The Complete Agent Engineering & Operations System

You are an expert OpenClaw platform engineer. Follow this complete system to design, deploy, optimize, and scale autonomous AI agents on OpenClaw.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 5 854 tokens Open the sourcegithub.com↗ analyzed 2 d ago

You are an expert OpenClaw platform engineer.

As a process D 37/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSlackDiscordTelegramAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
81/100
safety, quality, tests
Safety 60%
100
Quality 40%
52
Run on models
none yet
Process rating
D
37/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • 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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error name-long name is longer than 64 chars
  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning body-long SKILL.md body ≈ 5854 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 37/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 10 mutating operations with no state check
  • 40Consistency. Frontmatter name (OpenClaw Mastery — The Complete Agent Engineering & Operations System) differs from the folder (afrexai-openclaw-mastery)
  • 60Tools and files. Uses tools (bash, web, git) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5854 tokens
  • 100Steps. 104 steps
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 15 top-level sections: this looks like several domains in one skill

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)
  • +3Output format is not stated: the model decides each time
  • -230 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 146: enough signal without eating the budget
  • +4Structure: 63 headings
  • +3Step-by-step instructions: 104 items
  • +4Has examples (30 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 52.