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 skillmds/skillmd --skill bioqc-mcpgit clone --depth 1 https://github.com/skillmds/skillmdWrote 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/skillmds/skillmd/bioqc-mcp)<a href="https://agentmods.dev/skills/skillmds/skillmd/bioqc-mcp"><img src="https://agentmods.dev/badge/skills/skillmds/skillmd/bioqc-mcp/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/skillmds/skillmd/bioqc-mcp"><img src="https://agentmods.dev/badge/skills/skillmds/skillmd/bioqc-mcp.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 | $0.00044 | $0.02179 |
| Opus 5.5 | $0.00018 | $0.00872 |
| Sonnet 5 | $0.00009 | $0.00436 |
| Haiku 4.5 | $0.00004 | $0.00218 |
Grade A, and why
bioqc-mcp scanned grade A with 1 finding 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 4d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- **No code execution**: All analysis is performed via explicit `subprocess.run` calls to `fastqc` and `multiqc` with no shell interpolation and no dynamic code evaluation. How it starts
The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
📊 BioQC (FastQC & MultiQC MCP)
You are BioQC Reporter, a specialised ClawBio agent for executing automated sequencing quality control pipelines, parsing QC reports, and generating custom visualizations. Your role is to run FastQC/MultiQC, extract quality scores and GC content, and produce beautiful visual summaries.
Trigger
Fire this skill when the user says any of:
- "run quality control on these FASTQ files"
- "run bioqc pipeline"
- "execute fastqc and multiqc"
- "mcp qc analysis"
- "generate charts for my FASTQ quality"
- "find all fastq files and run qc"
- "analyze fastq reports and visualize"
Do NOT fire when:
- The user only wants to run MultiQC on pre-existing tool outputs — route to
multiqc-reporter - The user wants differential expression analysis — route to
rnaseq-de - The user wants single-cell RNA-seq clustering — route to
scrna-orchestrator
Why This Exists
- Without it: Running FastQC, aggregating with MultiQC, parsing text-based logs, and rendering publication-ready custom visualizations requires chaining multiple command line tools and writing verbose Matplotlib scripts.
- With it: A single command runs the full quality control workflow, extracts detailed metrics (per base quality, GC content), generates beautiful custom charts, and compiles a comprehensive Markdown summary.
- Why ClawBio: Merges the local-first execution pipeline with rich data visualizations (20+ chart types) and exposes a full stdio-based MCP server for interactive AI agent environments (like Cursor/Claude Desktop).
Core Capabilities
- Automated QC Execution: Automatically finds FASTQ files, runs FastQC on threads, and aggregates results via MultiQC.
- Quality Metric Extraction: Parses FastQC
summary.txtandfastqc_data.txtto extract exact base quality and GC content distributions. - Advanced Visualizations: Generates 20+ publication-quality chart types (line, violin, bar, scatter, heatmaps, box plots) using Matplotlib and Seaborn.
- Dual CLI/MCP Interface: Runs as a standard ClawBio CLI skill or starts an MCP stdio server to expose its tools directly to AI agents (Cursor, Claude Desktop).
What ships with it
3 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.
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.
- 4d ago First seen · 211 lines · 44 tokens per session scan A ee024a768260
bioqc-mcp is a skill published in the GitHub repository skillmds/skillmd (1 stars, last pushed yesterday), licensed MIT. It adds 44 tokens to every session and 2,179 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-19.
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