by-database

by-database is a skill for Claude Code, Codex from 001TMF/blatant-why. It costs 3 tokens per session (4,990 once invoked), scanned A, original, MIT.

A database lookup skill for protein and antibody design. It searches PDB structures, UniProt protein records, and SAbDab antibody–protein records.

In plain words
What is it for?
Use it to characterize a protein target, check its chains and residue numbering, find antibody–target complexes, choose antibody scaffolds, and compare binding interfaces.
Why use it?
It gathers structural details, protein sequences, and known antibody examples in one workflow, reducing manual cross-checking before a design starts.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/001tmf/blatant-why/by-database
Any agent
npx skills add 001TMF/blatant-why --skill by-database
Clone the repo
git clone --depth 1 https://github.com/001TMF/blatant-why

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 by-database

README.md
[![agentmods](https://agentmods.dev/badge/skills/001tmf/blatant-why/by-database.svg)](https://agentmods.dev/skills/001tmf/blatant-why/by-database)
Your own site
<a href="https://agentmods.dev/skills/001tmf/blatant-why/by-database"><img src="https://agentmods.dev/badge/skills/001tmf/blatant-why/by-database.svg" alt="Measured on agentmods" height="20"></a>
Per session 3 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,990 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00003 $0.04990
Opus 5 $0.00002 $0.02495
Sonnet 5 $0.00001 $0.00998
Haiku 4.5 $0.00000 $0.00499

Measured 5d ago against content hash bf0956da6380, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

by-database 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 5d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/batch_pdb_lookup.py, scripts/find_similar_targets.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

templates/.claude/skills/by-database/SKILL.md · 374 lines

How it starts

The opening of the file, as written. The whole thing — 374 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: by-database

Use the BY MCP database tools to query PDB, UniProt, and SAbDab for target characterization, antibody scaffold selection, and competition analysis.


When to Use This Skill

Use this skill when you need:

  • ✅ Structural metadata for a target (resolution, method, organism, chains)
  • ✅ Interface residue lists for hotspot selection in PXDesign / BoltzGen
  • ✅ Canonical UniProt sequence, domain boundaries, or known variants
  • ✅ Existing antibody-antigen complexes for scaffold selection or competition analysis
  • ✅ Cross-referencing PDB residue numbering with UniProt positions
  • ✅ Verifying chain composition before generating a design spec

Don't use this skill for:

  • ❌ Full target research narrative or literature review → use by-research
  • ❌ Epitope hotspot scoring or surface analysis → use by-epitope-analysis
  • ❌ Scoring designs (ipSAE, ipTM, liabilities) → use by-scoring / by-screening
  • ❌ Web search or PubMed lookups → fall back to PubMed/bioRxiv tools then WebSearch
  • ❌ Submitting compute jobs → use boltzgen, pxdesign, protenix skills

Quick Start

Look up a target end-to-end in three calls:

mcp__by-pdb__pdb_search(query="PD-L1", max_results=10)
mcp__by-uniprot__uniprot_search(query="CD274 human", max_results=5)
mcp__by-sabdab__sabdab_search_by_antigen(antigen_name="PD-L1", max_results=20)

For batch enrichment of a known list of PDB IDs without an MCP loop:

python scripts/batch_pdb_lookup.py --ids 7S4S 6XWG 5JDS --out enriched.csv

VERIFICATION: Expect ✓ batch_pdb_lookup completed: 3 rows -> enriched.csv.


Inputs

Required (at least one of):

  • PDB ID — 4-character RCSB identifier (e.g. 7S4S). Source: mcp__by-pdb__pdb_search.
  • UniProt accession — e.g. Q9NZQ7. Source: mcp__by-uniprot__uniprot_search.
  • Target name / gene symbol — e.g. "PD-L1", "CD274". Used as free-text query.
  • Antigen name — for SAbDab antibody lookups (e.g. "HER2").

Read the full file on GitHub · 374 lines

Files

What ships with it

5 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.

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. 5d ago First seen · 374 lines · 3 tokens per session scan A bf0956da6380

Subscribe to this mod's changes

by-database is a skill published in the GitHub repository 001TMF/blatant-why (114 stars, last pushed 19d ago), licensed MIT. It adds 3 tokens to every session and 4,990 once invoked, about $0.0000 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 2026-08-30.

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