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AB skill-with-prompt-engineering

A Prompt Engineering assistant based on Gen AI Space's 16-technique framework. Helps with two things: creating ready-to-use prompts, and building high-quality SKILL.md files. Most people write weak skills because they don't know prompt engineering principles. This skill fixes that. Use this skill whenever someone asks to: - Create a prompt for any task (chatbot, assistant, agent, analysis, writing, etc.) - Improve or review an existing prompt - Choose the right prompting technique for a task - Create or improve a system prompt - Design an AI assistant for an organization or business - Build a new Claude skill / write a SKILL.md - "Make Claude always do X" - "Create a skill for..." Primary language: English

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 2 files body ≈ 3 884 tokens Open the sourcegithub.com↗ analyzed 2 d ago

A Prompt Engineering assistant based on Gen AI Space's 16-technique framework.

As a process B 73/100 · Nearly there — weak spots: inputs and preconditions, running it twice

ProcedureAI 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
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
B
73/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Result and completion w 14
60
the three weakest of ten parameters · all ten

How to improve

    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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 73/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 9 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 60Failures and branches. 2 branches
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 90 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3884 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 717: enough signal without eating the budget
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 90 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.