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 Babajan-B/BioQC-MCP --skill skillsgit clone --depth 1 https://github.com/Babajan-B/BioQC-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/skills/babajan-b/bioqc-mcp/skills)<a href="https://agentmods.dev/skills/babajan-b/bioqc-mcp/skills"><img src="https://agentmods.dev/badge/skills/babajan-b/bioqc-mcp/skills/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/babajan-b/bioqc-mcp/skills"><img src="https://agentmods.dev/badge/skills/babajan-b/bioqc-mcp/skills.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 | $0.00000 | $0.00335 |
| Opus 5.5 | $0.00000 | $0.00134 |
| Sonnet 5.5 | $0.00000 | $0.00067 |
| Haiku 4.5 | $0.00000 | $0.00034 |
Grade A, and why
skills 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 2mo 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.
What it actually says
BioQC-MCP Skills
This directory contains reusable pipeline templates for the run_qc_pipeline tool.
Available Skills
| Skill | Description | Use Case |
|---|---|---|
full_qc_pipeline.py |
Complete QC workflow | Analyze all FASTQ files in a directory |
batch_analysis.py |
Multi-sample batch processing | Process many samples with summary stats |
quick_check.py |
Fast quality overview | Quick sanity check on samples |
Usage
AI agents can read these skill files and adapt them for user requests:
# Example: User asks "Run QC on my samples"
# AI reads skills/full_qc_pipeline.py and adapts it:
files = list_fastq_files('/path/to/samples')
print(f"Found {len(files)} FASTQ files")
for f in files:
result = run_fastqc([f['path']], output_dir='./qc_results')
print(f"Analyzed: {f['name']}")
multiqc = run_multiqc('./qc_results', output_dir='./multiqc_report')
print(f"Report: {multiqc['report']}")
Token Savings
Using skills with run_qc_pipeline reduces token usage by 75-98%:
| Workflow | Without Skills | With Skills | Savings |
|---|---|---|---|
| Single file QC | 2,000 tokens | 500 tokens | 75% |
| Multi-sample | 8,000 tokens | 600 tokens | 92% |
| Full pipeline | 15,000 tokens | 300 tokens | 98% |
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.
- 2mo ago First seen · 41 lines · 0 tokens per session scan A 924885385d35
skills is a skill published in the GitHub repository Babajan-B/BioQC-MCP (1 stars, last pushed 11mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 335 tokens. 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.
skills compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| skillsBabajan-B/BioQC-MCP | Skill | 1 | 11mo ago | MIT | A | 0 | Claude Code, Codex |
| ngs-quality-controlawslabs/hcls-agent-skills | Skill | 72 | 1mo ago | MIT-0 | A | 58 | Claude Code, Codex |
| paper-searchopenags/paper-search-mcp | Skill | 3.0k | 1mo ago | MIT | A | 62 | Claude Code, Codex |
| paper-searchopenags/paper-search-mcp | Skill | 3.0k | 1mo ago | MIT | A | 78 | Claude Code, Codex |
| mitiq-error-mitigationxi-zhao/OpenQuantum | Skill | 71 | yesterday | MIT | A | 48 | Claude Code, Codex |
| quantum-ground-statexi-zhao/OpenQuantum | Skill | 71 | yesterday | MIT | A | 103 | Codex |
| qmclaw-workbenchxi-zhao/OpenQuantum | Skill | 71 | yesterday | MIT | A | 124 | Codex |