Agent skill

String Ppi Enrichment

by InternScience in InternScience/scp

Analyze protein-protein interaction enrichment using STRING database to identify functional networks and pathway associations.

MITAuto-check passed

Install String Ppi Enrichment

skills CLI
$ npx skills add InternScience/scp --skill string-ppi-enrichment -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install InternScience/scp string-ppi-enrichment --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/string-ppi-enrichment .claude/skills/string-ppi-enrichment && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
string-ppi-enrichment
GitHub stars
169
Used in
1 other repo
Token cost
~635 tokens
SKILL.md length
35 words
Files
1
Skills in repo
73
Repo updated
First seen
Licence
MIT

At a glance

Analyze protein-protein interaction enrichment using STRING database to identify functional networks and pathway associations.

  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

String Ppi Enrichment is an agent skill from InternScience/scp. Analyze protein-protein interaction enrichment using STRING database to identify functional networks and pathway associations.

Its SKILL.md is about 640 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The licence is MIT.

Example prompts

  • “/string-ppi-enrichment”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit cea5398. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

String Ppi Enrichment loads about 635 tokens when it runs. Until then it costs about 37 tokens; SKILL.md has 35 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~37
When it runs · the whole SKILL.md, loaded when a task matches
~635

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from InternScience/scp at commit cea5398, republished under its MIT licence (© InternScience). 35 words, ~635 tokens.

Download SKILL.mdSave it as .claude/skills/string-ppi-enrichment/SKILL.md (or your agent's skills folder).
name
string-ppi-enrichment
description
Analyze protein-protein interaction enrichment using STRING database to identify functional networks and pathway associations.
license
MIT license
metadata.skill-author
PJLab

STRING Protein-Protein Interaction Enrichment

Usage

python
import asyncio
import json
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession

class OrigeneClient:
    def __init__(self, server_url: str, api_key: str):
        self.server_url = server_url
        self.api_key = api_key
        self.session = None

    async def connect(self):
        try:
            self.transport = streamablehttp_client(url=self.server_url, headers={"SCP-HUB-API-KEY": self.api_key})
            self.read, self.write, self.get_session_id = await self.transport.__aenter__()
            self.session_ctx = ClientSession(self.read, self.write)
            self.session = await self.session_ctx.__aenter__()
            await self.session.initialize()
            return True
        except Exception as e:
            return False

    async def disconnect(self):
        if self.session:
            await self.session_ctx.__aexit__(None, None, None)
        if hasattr(self, 'transport'):
            await self.transport.__aexit__(None, None, None)

    def parse_result(self, result):
        if isinstance(result, dict):
            content_list = result.get("content") or []
        else:
            content_list = getattr(result, "content", []) or []
        texts = []
        for item in content_list:
            if isinstance(item, dict):
                if item.get("type") == "text":
                    texts.append(item.get("text") or "")
            else:
                if getattr(item, "type", None) == "text":
                    texts.append(getattr(item, "text", "") or "")
        return "".join(texts)

## Initialize and use
client = OrigeneClient("https://scp.intern-ai.org.cn/api/v1/mcp/6/Origene-STRING", "<your-api-key>")
await client.connect()

result = await client.session.call_tool("get_ppi_enrichment", arguments={"identifiers": ["Pax6", "Sox2", "Nanog"], "species": 10090})
print(client.parse_result(result))

await client.disconnect()
Tool: get_ppi_enrichment
  • Args: identifiers (list) - Gene/protein identifiers, species (int) - NCBI taxonomy ID
  • Returns: Network statistics including edges, clustering coefficient, p-value
Use Cases
  • Protein network analysis, functional module identification, pathway enrichment

© InternScience, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/string-ppi-enrichment of InternScience/scp.

Open the folder on GitHubat commit cea5398

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in InternScience/scp, which our catalogue first saw on October 7, 2026.

Compare with similar skills

String Ppi Enrichment next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

String Ppi Enrichment compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
String Ppi Enrichment this skillInternScience/scp1691 repos~635Automated safety check: PassMIT
String Protein Interaction Analysis With Omicversemajiayu000/claude-skill-registry6662 repos~749Automated safety check: PassMIT
String Databasedavila7/claude-code-templates32k11 repos~4.5kAutomated safety check: PassMIT
Protein Interaction Network AnalysisFreedomIntelligence/OpenClaw-Medical-Skills3.1k2 repos~3.7kAutomated safety check: NotesNone
String Databaseaipoch/medical-research-skills2k—~928Automated safety check: PassMIT
String Databasegoogle-deepmind/science-skills3.2k2 repos~731Automated safety check: PassApache-2.0

Similar skills

  • Help Claude query STRING for protein interactions, build PPI graphs with pyPPI, and render styled network figures for bulk gene lists.

    666 GitHub starsUsed in 2 repos~749 tokens
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  • String Database

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  • Protein Interaction Network Analysis

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    Analyze protein-protein interaction networks using STRING, BioGRID, and SASBDB databases.

    3.1k GitHub starsUsed in 2 repos~3.7k tokens
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  • String Database

    aipoch/medical-research-skills

    Access the STRING database to map identifiers, retrieve protein–protein interaction networks, and run functional/PPI enrichment when you need interaction context for a gene/protein set.

    2k GitHub stars~928 tokensUpdated 21 days ago
    Research & ScienceAuto-check passed
  • String Database

    google-deepmind/science-skills

    Query the STRING database for protein-protein interactions (PPIs), functional enrichment, and homology.

    3.2k GitHub starsUsed in 2 repos~731 tokens
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  • String Database Ppi

    jaechang-hits/SciAgent-Skills

    Query STRING REST API for PPIs (59M proteins, 20B interactions, 5000+ species).

    370 GitHub starsUsed in 1 repo~4.2k tokens
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Questions about String Ppi Enrichment

What does String Ppi Enrichment do?

Analyze protein-protein interaction enrichment using STRING database to identify functional networks and pathway associations. String Ppi Enrichment is an agent skill from InternScience/scp. Analyze protein-protein interaction enrichment using STRING database to identify functional networks and pathway associations.

How do I install String Ppi Enrichment in Claude Code?

Run `npx skills add InternScience/scp --skill string-ppi-enrichment -a claude-code`. Or copy the skill folder (skills/string-ppi-enrichment in InternScience/scp) into .claude/skills/string-ppi-enrichment in your project. Claude Code loads it when a task matches its description.

How do I install String Ppi Enrichment in Codex?

Run `npx skills add InternScience/scp --skill string-ppi-enrichment -a codex`. Or copy the skill folder (skills/string-ppi-enrichment in InternScience/scp) into .agents/skills/string-ppi-enrichment in your project. Codex loads it when a task matches its description.

Can I use String Ppi Enrichment in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add InternScience/scp --skill string-ppi-enrichment -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/string-ppi-enrichment, .gemini/skills/string-ppi-enrichment, .github/skills/string-ppi-enrichment and .opencode/skills/string-ppi-enrichment in your project.

What does String Ppi Enrichment need to run?

SKILL.md names no scripts, command-line tools or credentials: String Ppi Enrichment is instructions for the agent only. Our summary lists: Python 3.

Does String Ppi Enrichment access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is String Ppi Enrichment safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does String Ppi Enrichment use?

String Ppi Enrichment is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does String Ppi Enrichment use?

About 635 tokens (SKILL.md is roughly 2.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to String Ppi Enrichment?

Skills that share tags, products or a category with String Ppi Enrichment: String Protein Interaction Analysis With Omicverse (majiayu000/claude-skill-registry, 666 stars), String Database (davila7/claude-code-templates, 32k stars), Protein Interaction Network Analysis (FreedomIntelligence/OpenClaw-Medical-Skills, 3.1k stars) and String Database (aipoch/medical-research-skills, 2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains String Ppi Enrichment?

InternScience (a GitHub organization) maintains it in InternScience/scp, which has 169 GitHub stars. The repository holds 73 skills in this directory. The repository was last updated on June 3, 2026.

Source: InternScience/scp on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.