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AB prompt-optimizer

Analyze draft prompts, detect intent and missing context, match ECC commands, skills, and agents, and output a ready-to-paste optimized prompt with diagnosis and rationale — advisory only, never executes the task. Use when the user says 'optimize prompt', 'improve my prompt', 'rewrite this prompt', 'help me prompt', 优化prompt, 改进prompt, 怎么写prompt, or 帮我优化这个指令; not for requests to optimize code or performance.

affaan-m/everything-claude-code Agent Skills author: affaan-m MIT 1 file body ≈ 3 665 tokens Open the sourcegithub.com↗ analyzed 19 h ago

Analyze draft prompts, detect intent and missing context, match ECC commands, skills, and agents, and output a ready-to-paste optimized prompt with diagnosis…

As a process B 78/100 · Nearly there — weak spots: inputs and preconditions

AnalyzerDockerAI and agentstype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
B
78/100
Nearly there
Inputs and preconditions w 11
0
Tools and files w 18
60
Failures and branches w 10
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: 1. 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 78/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Failures and branches. 2 branches
    • 100Steps. 52 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3665 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    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
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 411: enough signal without eating the budget
    • +4Structure: 26 headings
    • +3Step-by-step instructions: 52 items
    • +3Output format is stated explicitly
    • +4Has examples (7 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.