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 skills add majiang213/OpenClaw-MAS --skill prompt-optimizergit clone --depth 1 https://github.com/majiang213/OpenClaw-MASWrote 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/majiang213/openclaw-mas/prompt-optimizer)<a href="https://agentmods.dev/skills/majiang213/openclaw-mas/prompt-optimizer"><img src="https://agentmods.dev/badge/skills/majiang213/openclaw-mas/prompt-optimizer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/majiang213/openclaw-mas/prompt-optimizer"><img src="https://agentmods.dev/badge/skills/majiang213/openclaw-mas/prompt-optimizer.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00179 | $0.04017 |
| Opus 5 | $0.00089 | $0.02008 |
| Sonnet 5 | $0.00036 | $0.00803 |
| Haiku 4.5 | $0.00018 | $0.00402 |
Grade A, and why
prompt-optimizer 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 7d 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.
This is a copy
88% identical to prompt-optimizer — 29 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 398 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Optimizer
Analyze a draft prompt, critique it, match it to ECC ecosystem components, and output a complete optimized prompt the user can paste and run.
When to Use
- User says "optimize this prompt", "improve my prompt", "rewrite this prompt"
- User says "help me write a better prompt for..."
- User says "what's the best way to ask Claude Code to..."
- User says "优化prompt", "改进prompt", "怎么写prompt", "帮我优化这个指令"
- User pastes a draft prompt and asks for feedback or enhancement
- User says "I don't know how to prompt for this"
- User says "how should I use ECC for..."
- User explicitly invokes
/prompt-optimize
Do Not Use When
- User wants the task done directly (just execute it)
- User says "优化代码", "优化性能", "optimize this code", "optimize performance" — these are refactoring tasks, not prompt optimization
- User is asking about ECC configuration (use
configure-eccinstead) - User wants a skill inventory (use
skill-stocktakeinstead) - User says "just do it" or "直接做"
How It Works
Advisory only — do not execute the user's task.
Do NOT write code, create files, run commands, or take any implementation action. Your ONLY output is an analysis plus an optimized prompt.
If the user says "just do it", "直接做", or "don't optimize, just execute", do not switch into implementation mode inside this skill. Tell the user this skill only produces optimized prompts, and instruct them to make a normal task request if they want execution instead.
Run this 6-phase pipeline sequentially. Present results using the Output Format below.
Analysis Pipeline
Phase 0: Project Detection
Before analyzing the prompt, detect the current project context:
- Check if a
CLAUDE.mdexists in the working directory — read it for project conventions - Detect tech stack from project files:
package.json→ Node.js / TypeScript / React / Next.jsgo.mod→ Gopyproject.toml/requirements.txt→ PythonCargo.toml→ Rustbuild.gradle/pom.xml→ Java / Kotlin / Spring BootPackage.swift→ SwiftGemfile→ Rubycomposer.json→ PHP*.csproj/*.sln→ .NETMakefile/CMakeLists.txt→ C / C++cpanfile/Makefile.PL→ Perl
- Note detected tech stack for use in Phase 3 and Phase 4
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.
- 7d ago First seen · 398 lines · 179 tokens per session scan A 645df8819e84
prompt-optimizer is a skill published in the GitHub repository majiang213/OpenClaw-MAS (5 stars, last pushed 5mo ago), licensed MIT. It adds 179 tokens to every session and 4,017 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to prompt-optimizer, differing in 29 lines, and is treated as a copy.
Other skills, from other repositories
sequence-diagram
Show interactions and flows over time. Illustrate request paths, asynchronous patterns, error handling. Use when documenting complex flows or onboarding on system behavior.
architecture-anti-patterns
Identify and avoid common architectural mistakes. Recognize patterns of failure. Use when reviewing designs or learning from mistakes.
architecture-patterns-catalog
Reference catalog of proven architecture patterns. Know when to apply each pattern, tradeoffs, and examples. Use as reference when designing systems.
interview-prep
Prepare for architecture interview questions and scenarios. Practice system design, tradeoff discussions, communication. Use for career development and interview readiness.
system-audit
Conduct comprehensive system architecture evaluation. Assess design quality, technical debt, operational readiness, scalability. Use when auditing existing systems.
technical-mentoring
Coach engineers on architecture and design. Provide feedback, guide learning, support growth. Use when mentoring junior architects or senior engineers.