Agent skill · Data & Analytics

tcp-skill

Use this skill whenever the user wants an end-to-end workflow for the Transdiagnostic Connectome Project (TCP) dataset, including BIDS validation, multimodal processing of sMRI, rs-fMRI, and dMRI, phenotype extraction, and QC integration. Triggers include: 'TCP', 'Transdiagnostic Connectome', 'process TCP data', 'TCP fMRI', or any request to run the TCP multimodal pipeline.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill tcp-skill --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 8 KB
Bundled scripts: none
Requires: - smri-skill - fmri-skill - dwi-skill - bids-organizer - claw-shell
Path: skills/neuroclaw/tcp-skill/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# TCP Skill (Dataset-Orchestration Layer) ## Overview `tcp-skill` is the NeuroClaw orchestration skill for the **Transdiagnostic Connectome Project (TCP)** dataset, collected at Washington University in St. Louis. It strictly follows the NeuroClaw hierarchical design principles: - This skill **only describes WHAT needs to be done** and **which tool skill to delegate to**. - It contains **no implementation code or concrete commands**. - All concrete execution is delegated to existing base/tool skills via `claw-shell`. - Companion scripts in `scripts/` provide reference implementations for BIDS validation, phenotype extraction, and QC. **Core workflow (never bypassed):** 1. Identify input TCP data and target modalities. 2. Generate a **numbered execution plan** clearly stating WHAT needs to be done and which tool skill will handle each step. 3. Present the full plan, estimated runtime, resource requirements, and risks to the user and wait for explicit confirmation ("YES" / "execute" / "proceed"). 4. On confirmation, delegate every step to the appropriate skill via `claw-shell`. 5. After execution, save all outputs in a clean directory structure (`tcp_output/`). **Research use only.**

What's inside
Steps it walks through
  1. Overview
  2. Quick Reference
  3. Dataset Characteristics
  4. Supported Modalities
  5. TCP Clinical Dimensions
  6. BIDS Preparation
  7. Script: scripts/validatetcp.py
  8. Core Workflow (Never Bypassed)
  9. Modality Processing Delegation
  10. Standard Output Layout
  11. Benchmark Adapter Guidance
  12. Safety and Execution Policy
  13. Important Notes and Limitations
  14. When to Call This Skill
Commands it runs
python skills/tcp-skill/scripts/validate_tcp.py \
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About this skill
What does the tcp-skill skill do?

Use this skill whenever the user wants an end-to-end workflow for the Transdiagnostic Connectome Project (TCP) dataset, including BIDS validation, multimodal processing of sMRI, rs-fMRI, and dMRI, phenotype extraction, and QC integration. Triggers include: 'TCP', 'Transdiagnostic Connectome', 'process TCP data', 'TCP fMRI', or any request to run the TCP multimodal pipeline.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill tcp-skill --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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