bio-workflows-clip-pipeline

bio-workflows-clip-pipeline is a skill for Claude Code, Codex from thesecondfox/skill. It costs 39 tokens per session (2,285 once invoked), scanned A, original, MIT.

A workflow for CLIP-seq analysis, a method for finding where RNA-binding proteins attach to RNA. It processes sequencing reads to identify binding sites and enriched sequence motifs.

In plain words
What is it for?
Use it to analyze HITS-CLIP, PAR-CLIP, iCLIP, or eCLIP data from FASTQ files and produce annotated binding sites and motif-enrichment results.
Why use it?
It coordinates specialized steps such as adapter removal, UMI handling, duplicate removal, and peak detection that are easy to apply inconsistently by hand.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to analyze HITS-CLIP, PAR-CLIP, iCLIP, or eCLIP data from FASTQ files and produce annotated binding sites and motif-enrichment results.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/thesecondfox/skill/bio-workflows-clip-pipeline
Install

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.

Any agent
npx skills add thesecondfox/skill --skill bio-workflows-clip-pipeline
Clone the repo
git clone --depth 1 https://github.com/thesecondfox/skill

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for bio-workflows-clip-pipeline

README.md
[![agentmods](https://agentmods.dev/badge/skills/thesecondfox/skill/bio-workflows-clip-pipeline.svg)](https://agentmods.dev/skills/thesecondfox/skill/bio-workflows-clip-pipeline)
Your own site
<a href="https://agentmods.dev/skills/thesecondfox/skill/bio-workflows-clip-pipeline"><img src="https://agentmods.dev/badge/skills/thesecondfox/skill/bio-workflows-clip-pipeline.svg" alt="Measured on agentmods" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,285 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00039 $0.02285
Opus 5 $0.00019 $0.01143
Sonnet 5 $0.00008 $0.00457
Haiku 4.5 $0.00004 $0.00229

Measured 4d ago against content hash 97aa400f8cbb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

bio-workflows-clip-pipeline 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 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.

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.

Common_Skills/bio-workflows-clip-pipeline/SKILL.md · 261 lines

How it starts

The opening of the file, as written. The whole thing — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Version Compatibility

Reference examples tested with: FastQC 0.12+, STAR 2.7.11+, bedtools 2.31+, cutadapt 4.4+, samtools 1.19+

Before using code patterns, verify installed versions match. If versions differ:

  • CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

CLIP-seq Pipeline

"Analyze my CLIP-seq data from FASTQ to binding sites and motifs" → Orchestrate UMI extraction, adapter trimming, STAR alignment, PCR deduplication, CLIPper/PureCLIP peak calling, binding site annotation, and HOMER motif enrichment.

Pipeline Overview

FASTQ → QC → UMI extract → Trim adapters → Align → Filter → Dedup → Peak call → Annotate → Motifs

CLIP Method Variants

Method UMI Crosslink Site Adapter
HITS-CLIP Optional Deletions 3' adapter
PAR-CLIP Optional T→C mutations 3' adapter
iCLIP Required 5' of read 3' adapter
eCLIP Required 5' of read 3' adapter

Step 1: Quality Control

# Initial QC
fastqc reads.fastq.gz -o qc_pre/

# Check for adapter contamination and UMI structure
# For eCLIP: expect 10nt UMI at read start
zcat reads.fastq.gz | head -n 100 | cut -c1-15

Step 2: UMI Extraction

# eCLIP (10nt UMI at 5' end)
umi_tools extract \
    --stdin=reads.fastq.gz \
    --bc-pattern=NNNNNNNNNN \
    --stdout=extracted.fastq.gz \
    --log=umi_extract.log

# iCLIP (5nt experimental barcode + 5nt UMI)
umi_tools extract \
    --stdin=reads.fastq.gz \
    --bc-pattern=NNNNNXXXXX \
    --stdout=extracted.fastq.gz

Step 3: Adapter Trimming

# Trim 3' adapter (common eCLIP adapter)
cutadapt -a AGATCGGAAGAGCACACGTCTGAACTCCAGTCA \
    --minimum-length 20 \
    --quality-cutoff 20 \
    -o trimmed.fastq.gz \
    extracted.fastq.gz

# For paired UMI adapters
cutadapt -a AGATCGGAAGAGCACACGTCT \
    -A AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT \
    --minimum-length 20 \
    -o trimmed_R1.fq.gz -p trimmed_R2.fq.gz \
    extracted_R1.fq.gz extracted_R2.fq.gz

Read the full file on GitHub · 261 lines

Files

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.

Changes

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.

  1. 4d ago First seen · 261 lines · 39 tokens per session scan A 97aa400f8cbb

Subscribe to this mod's changes

bio-workflows-clip-pipeline is a skill published in the GitHub repository thesecondfox/skill (3 stars, last pushed 5mo ago), licensed MIT. It adds 39 tokens to every session and 2,285 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 2026-09-03.

Related

Other skills, from other repositories

instrument-data-to-allotrope

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…

anthropics/knowledge-work-plugins · 123 tokens

exploratory-data-analysis

Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…

K-Dense-AI/scientific-agent-skills · 83 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

phylogenetics

Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.

K-Dense-AI/scientific-agent-skills · 68 tokens

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

mapping-to-snomed

Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…

maziyarpanahi/openmed · 205 tokens