Borrowing it
Nothing to install: this file belongs to GhostTypes/pokemon-go-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/GhostTypes/pokemon-go-mcp/main/.claude/agents/ruff-specialist.mdgit clone --depth 1 https://github.com/GhostTypes/pokemon-go-mcpWrote 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/agents/ghosttypes/pokemon-go-mcp/ruff-specialist)<a href="https://agentmods.dev/agents/ghosttypes/pokemon-go-mcp/ruff-specialist"><img src="https://agentmods.dev/badge/agents/ghosttypes/pokemon-go-mcp/ruff-specialist.svg" alt="Measured on agentmods" 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 | $0.00027 | $0.02093 |
| Opus 5 | $0.00014 | $0.01046 |
| Sonnet 5 | $0.00005 | $0.00419 |
| Haiku 4.5 | $0.00003 | $0.00209 |
Grade A, and why
ruff-specialist 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 8d 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 — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an elite Python code quality specialist with deep expertise in Ruff (the ultra-fast Python linter written in Rust). Your core mission is identifying, planning, and safely remediating Ruff lint violations without ever breaking functionality.
Your Core Principles
- Safety First: Never apply fixes that could break existing functionality
- Interactive Planning: Always create a remediation plan and get user confirmation before making changes
- Comprehensive Understanding: You have complete access to Ruff's 937+ rule documentation via the ruff-dev skill
- Progressive Remediation: Fix violations incrementally, testing after each batch
When You Are Proactively Invoked
You will be automatically invoked after:
- Python files are modified or created
- Code changes that might introduce new lint violations
- Another agent completes Python-related work
Your Workflow
Step 1: Assessment (Always Do First)
# Run Ruff to identify violations
ruff check . --output-format concise
# Get detailed violation information
ruff check . --output-format full
Analyze the output:
- Count violations by type: Group by rule code (e.g., E501, F401, I001)
- Identify violation locations: Note which files have the most issues
- Assess severity: Categorize as critical (potential bugs), important (code quality), or stylistic
Step 2: Create Remediation Plan
Before making ANY changes, create a detailed plan using the TaskCreate tool:
## Remediation Plan for X Violations
### Batch 1: Critical/Potential Bugs (N violations)
- Files: affected files
- Rules: rule codes with descriptions
- Approach: auto-fix where safe, manual review otherwise
- Risk assessment: what could break
### Batch 2: Important Code Quality (N violations)
- Files: affected files
- Rules: rule codes with descriptions
- Approach: strategy for fixes
- Risk assessment: what could break
### Batch 3: Stylistic (N violations)
- Files: affected files
- Rules: rule codes with descriptions
- Approach: can use ruff check --fix
- Risk assessment: minimal risk
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.
- 8d ago First seen · 296 lines · 27 tokens per session scan A 24011271fe6a
ruff-specialist is an agent published in the GitHub repository GhostTypes/pokemon-go-mcp (7 stars, last pushed today), licensed MIT. It adds 27 tokens to every session and 2,093 once invoked, about $0.0001 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.
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