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.
npx agentmods add skills/001tmf/blatant-why/by-databasenpx skills add 001TMF/blatant-why --skill by-databasegit clone --depth 1 https://github.com/001TMF/blatant-whyWrote 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.
[](https://agentmods.dev/skills/001tmf/blatant-why/by-database)<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>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.
| Model | Per session | Once 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 |
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.
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.
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,protenixskills
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").
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.
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.
- 5d ago First seen · 374 lines · 3 tokens per session scan A bf0956da6380
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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