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Alphafold Database

Listed
drshailesh88·vlatest·database

Access and query Dr. Shailesh's AlphaFold protein structure prediction database for research and analysis.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add drshailesh88/integrated_content_os --skill alphafold-database -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

drshailesh88

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 3 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 2 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: alphafold.ebi.ac.uk, sdk.cloud.google.com.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    alphafold.ebi.ac.ukundeclaredsdk.cloud.google.comundeclared

    What it found

    • skills/scientific/alphafold-database/references/api_reference.md:39contacts alphafold.ebi.ac.uk
      curl https://alphafold.ebi.ac.uk/api/prediction/P00520
    • skills/scientific/alphafold-database/references/api_reference.md:304contacts sdk.cloud.google.com
      curl https://sdk.cloud.google.com | bash

  • No obfuscated payloads: failed

    Contains 1 obfuscated or encoded payload pattern.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

    What it found

    • skills/scientific/alphafold-database/references/api_reference.md:551130-character base64 literal
      "uniprotSequence": "MLEICLKLVGCKSKKGLSSSSSCYLEEALQRPVASDFEPQGLSEAARWNSKENLLAGPSENDPNLFVALYDFVASGDNTLSITKGEKLRVLGYNHNGEWCEAQTKNGQGWVPSNYITPVNSLEKHSWYHGPVSRNAAEY…

  • No pipe-to-shell installers: failed

    Runs code fetched at install time in 1 place.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

    What it found

    • skills/scientific/alphafold-database/references/api_reference.md:304remote script piped into a shell
      curl https://sdk.cloud.google.com | bash

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • Pinned to a commit: passed

    Scanned drshailesh88/integrated_content_os at 9e61937ad2.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
9e61937ad2
Manifest
skills/scientific/alphafold-database/SKILL.md
Scanned
2 files, 857 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill provides access to the AlphaFold Protein Structure Database. It allows users to query and retrieve protein structure information, including predicted 3D structures and related data. The database contains structural predictions for a vast number of proteins across many species.

When to use it

  • Researching protein structures for a specific organism or gene.
  • Identifying potential drug targets based on protein shape and properties.
  • Analyzing evolutionary relationships between proteins by comparing their structures.
  • Generating visualizations of protein models for educational purposes.

Key capabilities

  • Access to AlphaFold Protein Structure Database data.
  • Protein structure retrieval.
  • Data includes predicted 3D structures.
  • Supports queries based on various identifiers (e.g., UniProt accession).

Example prompts

  • "Get the protein structure for UniProt ID Q9Y261."
  • "Show me the AlphaFold prediction for human BRCA1."
  • “What is the predicted 3D structure of SARS-CoV-2 spike protein?”

Tips & gotchas

The database contains predictions, not experimentally determined structures. Accuracy can vary depending on the protein and data availability; always check confidence scores provided by AlphaFold.