Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/taxueseek/skill-optimizernpx agentmods add skills/taxueseek/skill-optimizer/grok-skill-creatorWrote 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/taxueseek/skill-optimizer/grok-skill-creator)<a href="https://agentmods.dev/skills/taxueseek/skill-optimizer/grok-skill-creator"><img src="https://agentmods.dev/badge/skills/taxueseek/skill-optimizer/grok-skill-creator/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/taxueseek/skill-optimizer/grok-skill-creator"><img src="https://agentmods.dev/badge/skills/taxueseek/skill-optimizer/grok-skill-creator.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 | $0.00116 | $0.02845 |
| Opus 5 | $0.00058 | $0.01422 |
| Sonnet 5 | $0.00023 | $0.00569 |
| Haiku 4.5 | $0.00012 | $0.00284 |
Grade A, and why
grok-skill-creator 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Creator — Grok
Create skills that extend Grok with specialized workflows. Leverages Grok's native subagent spawning, bash, read, write, edit tools.
Three Gates (Pre-flight)
All must pass. If any is no → stop.
- Grok can't already do this well? → Skill is overhead.
- User will use it 5+ times? → One-shot → direct prompt.
- Model has it built-in? → Skill adds complexity, not value.
Skill Anatomy
skill-name/
├── SKILL.md # Required — frontmatter + instructions
├── scripts/ # Optional — executable code
├── references/ # Optional — loaded on demand
└── assets/ # Optional — templates, icons, fonts
Frontmatter:
name: kebab-case # Required. Letters, digits, hyphens. Max 64 chars. Verb-led.
description: > # Required. Triggering conditions + what it does. Slightly "pushy".
Use when [trigger], [trigger], or [symptom].
paths: # Optional. Glob patterns for auto-discovery.
- "src/**/*.tsx"
Discovery — Grok finds SKILL.md from:
- Project:
./.grok/skills/(walked up to repo root) - User:
~/.grok/skills/ - Plugins: any enabled plugin's
skills/directory - Config:
[skills] pathsin~/.grok/config.toml - Claude Code compat:
.claude/skills/,~/.agents/skills/,AGENTS.md
Invocation: User-invocable skills appear as slash commands /<skill-name>.
The #1 Mistake: Description Trap
When description summarizes the workflow, the model follows the description and skips the body.
# ❌ BAD: Summarizes workflow → model takes shortcut
description: Use for TDD — write test first, watch it fail, write minimal code
# ✅ GOOD: Triggering conditions only → forces model to read the body
description: Use when implementing features or bugfixes, before writing code
Formula: [Action verb] + [value]. Use when [trigger 1], [trigger 2], ...
Include 5+ triggers. Add exclusions. Be slightly "pushy" to combat undertriggering.
Creation: 7 Steps
What ships with it
12 files 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.
- agents/analyzer.md 10 KB
- agents/comparator.md 7.1 KB
- agents/grader.md 8.8 KB
- assets/eval_review.html 6.9 KB
- eval-viewer/generate_review.py 16 KB runs code
- eval-viewer/viewer.html 44 KB
- references/schemas.md 12 KB
- scripts/aggregate_benchmark.py 14 KB runs code
- scripts/generate_report.py 13 KB runs code
- scripts/package_skill.py 4.1 KB runs code
- scripts/quick_validate.py 3.9 KB runs code
- scripts/utils.py 1.6 KB runs code
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.
- 9d ago First seen · 306 lines · 116 tokens per session scan A 9f7f7269e085
grok-skill-creator is a skill published in the GitHub repository taxueseek/skill-optimizer (6 stars, last pushed 21d ago), licensed MIT. It adds 116 tokens to every session and 2,845 once invoked, about $0.0006 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…