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 OmidZamani/dspy-skills --skill skills-skill-perfectiongit clone --depth 1 https://github.com/OmidZamani/dspy-skillsWrote 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/omidzamani/dspy-skills/skills-skill-perfection)<a href="https://agentmods.dev/skills/omidzamani/dspy-skills/skills-skill-perfection"><img src="https://agentmods.dev/badge/skills/omidzamani/dspy-skills/skills-skill-perfection/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/omidzamani/dspy-skills/skills-skill-perfection"><img src="https://agentmods.dev/badge/skills/omidzamani/dspy-skills/skills-skill-perfection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00041 | $0.01613 |
| Opus 5 | $0.00020 | $0.00807 |
| Sonnet 5 | $0.00008 | $0.00323 |
| Haiku 4.5 | $0.00004 | $0.00161 |
Grade A, and why
skill-perfection 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 13d 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- skill-perfection — 100% identical, 0 lines differ
- skill-perfection — 88% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Perfection
A systematic process for auditing and fixing plugin skills in a single pass.
Core Principle
Audit + Fix in One Pass: When you find an issue, fix it immediately, then continue. This eliminates redundant research and multiple iterations.
Process Overview
[Optional Preflight] → Audit+Fix (single pass) → Verify (spot-check) → Report
Phase 1: Preflight (Optional, Advisory)
A Python-based preflight script is bundled for Python-heavy skills only.
When to Use Preflight
| Skill Content | Use Preflight? |
|---|---|
| Mostly Python code blocks | ✅ Yes |
| Mixed Python + other languages | ⚠️ Optional (Python blocks only) |
| Non-Python (JS, Rust, Go, etc.) | ❌ Skip, go to Phase 2 |
| Skill about the preflight script itself | ❌ Skip (conflict of interest) |
Running Preflight
uv run python ${SKILL_DIR}/scripts/preflight.py <path-to-skill.md> --no-urls
Interpreting Results
| Result | Action |
|---|---|
✅ PASSED |
Good signal. Proceed to Phase 2, trust syntax is valid. |
❌ FAILED with clear errors (syntax error at line X) |
Fix those specific issues, then proceed to Phase 2. |
❌ FAILED with confusing/many errors |
Ignore preflight entirely. Proceed to Phase 2, let LLM verify. |
| Script crashes or hangs | Ignore preflight entirely. Proceed to Phase 2. |
Key Rule: Preflight is Advisory
The preflight script is a helper, not a gatekeeper. If it produces confusing output, skip it. The LLM-based Phase 2 is always authoritative.
Signs to ignore preflight:
- More than 10 errors on a skill that "looks fine"
- Errors that don't make sense (line numbers don't match)
- Python tracebacks from the script itself
- Timeouts or hanging
When in doubt, skip preflight and let the LLM verify everything.
Phase 2: Audit + Fix (Single Pass) - THE CORE
This is the main phase. Work through the skill file section by section.
2.1 Identify the Technology
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 13d ago First seen · 215 lines · 41 tokens per session scan A 27b948e832b6
skill-perfection is a skill published in the GitHub repository OmidZamani/dspy-skills (123 stars, last pushed 2mo ago), licensed MIT. It adds 41 tokens to every session and 1,613 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
evolving-ai-agents
Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation loops.
prompt-master
Generates optimized prompts for AI tools. Activates only when the user explicitly asks to write, fix, improve, or adapt a prompt for a specific AI tool (LLM, Cursor, Midjourney, image AI, video AI, coding agents, etc.). Does not activate for general conversation, coding tasks, document writing, or other…
recursive-decomposition
Decompose dense codebase-wide, multi-document, PDF, and aggregation work even when the input fits the context window, following Recursive Language Models (Zhang, Kraska, Khattab, 2025). Use when the user asks to analyse all files, a whole repo, all docs, large PDFs, or to aggregate or multi-hop across scattered…
edge-tts
Text-to-speech conversion using uvx edge-tts for generating audio from text. Use when (1) User requests audio/voice output with the "tts" trigger or keyword. (2) Content needs to be spoken rather than read (multitasking, accessibility, driving, cooking). (3) User wants a specific voice, speed, pitch, or format for TTS…
mcp-deepwiki
Skills for accessing and searching docs in DeepWiki/GitHub’s public code repositories can help users understand open-source project source codes, and users can also ask questions directly about the code docs.
tianqi
A weather-lookup workflow for Chinese locations, covering forecasts, hourly conditions, weather warnings, and daily-life indexes.