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 skills add 001TMF/blatant-why --skill by-screeninggit 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-screening)<a href="https://agentmods.dev/skills/001tmf/blatant-why/by-screening"><img src="https://agentmods.dev/badge/skills/001tmf/blatant-why/by-screening/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/001tmf/blatant-why/by-screening"><img src="https://agentmods.dev/badge/skills/001tmf/blatant-why/by-screening.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.09840 |
| Opus 5.5 | $0.00001 | $0.03936 |
| Sonnet 5.5 | $0.00001 | $0.01968 |
| Haiku 4.5 | $0.00000 | $0.00984 |
Grade A, and why
by-screening 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 1mo 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 — 812 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BY Screening Skill
Comprehensive screening battery for evaluating protein binder and antibody designs produced by PXDesign and BoltzGen. This skill encodes all quality filters, scoring thresholds, liability checks, and developability assessments used to triage designs before experimental validation.
Always run the full screening pipeline before presenting final candidates to the user. Never present unscreened designs as ready for validation.
When to Use This Skill
Use by-screening when you have:
- ✅ Raw design outputs from BoltzGen or PXDesign with refolding predictions (Protenix NPZ + scores)
- ✅ A set of candidate sequences that need PASS/FAIL classification before lab submission
- ✅ A campaign nearing the
/by:approve-labgate — screening MUST run first - ✅ Designs that need PTM liability and developability triage prior to ranking
- ✅ A need to diagnose batch-level failures (all FAIL ipTM, all FAIL RMSD, etc.)
- ✅ The need to apply diversity clustering before presenting top-N candidates
Don't use this skill for:
- ❌ Computing raw scoring metrics → use by-scoring (ipSAE NPZ math, composite formula derivation, multi-seed aggregation)
- ❌ Diagnosing root cause of a failed campaign at the strategy level → use by-failure-diagnosis (modality choice, scaffold selection, target druggability)
- ❌ Generating designs → use boltzgen or pxdesign
- ❌ Selecting which designs to advance to lab AFTER screening — that is the by-design-workflow orchestration step
- ❌ Looking up reference epitopes or target biology → use by-research
Cross-skill hand-off:
| Situation | Skill to call |
|---|---|
| Need raw ipSAE/ipTM numbers from NPZ | by-scoring first, then this skill |
| Need to apply PASS/FAIL filters to a batch | by-screening (this skill) |
| Whole batch fails screening (>80% FAIL) | by-failure-diagnosis for strategy correction |
| Designs pass screening, need rank/select | by-screening Stage 2 + 3, then by-design-workflow |
What ships with it
6 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.
- 1mo ago First seen · 812 lines · 3 tokens per session scan A 66644a94a85b
by-screening is a skill published in the GitHub repository 001TMF/blatant-why (119 stars, last pushed 9d ago), licensed MIT. It adds 3 tokens to every session and 9,840 once invoked, about $0.0000 per session on Opus 5.5. 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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