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 zongtingwei/Bioclaw_Skills_Hub --skill protein-design-qcgit clone --depth 1 https://github.com/zongtingwei/Bioclaw_Skills_HubWrote 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/zongtingwei/bioclaw_skills_hub/protein-design-qc)<a href="https://agentmods.dev/skills/zongtingwei/bioclaw_skills_hub/protein-design-qc"><img src="https://agentmods.dev/badge/skills/zongtingwei/bioclaw_skills_hub/protein-design-qc/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/zongtingwei/bioclaw_skills_hub/protein-design-qc"><img src="https://agentmods.dev/badge/skills/zongtingwei/bioclaw_skills_hub/protein-design-qc.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00143 | $0.02989 |
| Opus 5 | $0.00072 | $0.01494 |
| Sonnet 5 | $0.00029 | $0.00598 |
| Haiku 4.5 | $0.00014 | $0.00299 |
Grade A, and why
protein-design-qc 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 12d 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 — 324 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Protein Design Quality Control And Ranking
Plain-language role: Use this skill to decide which designs pass QC and which ones should move forward.
Critical Limitation
Individual metrics have weak predictive power for binding. Research shows:
- Individual metric ROC AUC: 0.64-0.66 (slightly better than random)
- Metrics are pre-screening filters, not affinity predictors
- Composite scoring is essential for meaningful ranking
These thresholds filter out poor designs but do NOT predict binding affinity.
QC Organization
QC is organized by purpose and level:
| Purpose | What it assesses | Key metrics |
|---|---|---|
| Binding | Interface quality, binding geometry | ipTM, PAE, SC, dG, dSASA |
| Expression | Manufacturability, solubility | Instability, GRAVY, pI, cysteines |
| Structural | Fold confidence, consistency | pLDDT, pTM, scRMSD |
Each category has two levels:
- Metric-level: Calculated values with thresholds (pLDDT > 0.85)
- Design-level: Pattern/motif detection (odd cysteines, NG sites)
Quick Reference: All Thresholds
| Category | Metric | Standard | Stringent | Source |
|---|---|---|---|---|
| Structural | pLDDT | > 0.85 | > 0.90 | AF2/Chai/Boltz |
| pTM | > 0.70 | > 0.80 | AF2/Chai/Boltz | |
| scRMSD | < 2.0 Å | < 1.5 Å | Design vs pred | |
| Binding | ipTM | > 0.50 | > 0.60 | AF2/Chai/Boltz |
| PAE_interaction | < 12 Å | < 10 Å | AF2/Chai/Boltz | |
| Shape Comp (SC) | > 0.50 | > 0.60 | PyRosetta | |
| interface_dG | < -10 | < -15 | PyRosetta | |
| Expression | Instability | < 40 | < 30 | BioPython |
| GRAVY | < 0.4 | < 0.2 | BioPython | |
| ESM2 PLL | > 0.0 | > 0.2 | ESM2 |
Design-Level Checks (Expression)
| Pattern | Risk | Action |
|---|---|---|
| Odd cysteine count | Unpaired disulfides | Redesign |
| NG/NS/NT motifs | Deamidation | Flag/avoid |
| K/R >= 3 consecutive | Proteolysis | Flag |
| >= 6 hydrophobic run | Aggregation | Redesign |
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.
- 12d ago First seen · 324 lines · 143 tokens per session scan A b3a2eb11b081
protein-design-qc is a skill published in the GitHub repository zongtingwei/Bioclaw_Skills_Hub (26 stars, last pushed 5mo ago), licensed MIT. It adds 143 tokens to every session and 2,989 once invoked, about $0.0007 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.
Other skills, from other repositories
protein-design-qc
Protein design quality control, filtering thresholds, and ranking guidance. Use this skill when: (1) Evaluating design quality for binding, expression, or structure, (2) Setting filtering thresholds for pLDDT, ipTM, PAE, (3) Checking sequence liabilities (cysteines, deamidation, polybasic clusters), (4) Creating…
protein-qc
Quality control metrics and filtering thresholds for protein design. Use this skill when: (1) Evaluating design quality for binding, expression, or structure, (2) Setting filtering thresholds for pLDDT, ipTM, PAE, (3) Checking sequence liabilities (cysteines, deamidation, polybasic clusters), (4) Creating multi-stage…
protein-qc
Quality control metrics and filtering thresholds for protein design. Use this skill when: (1) Evaluating design quality for binding, expression, or structure, (2) Setting filtering thresholds for pLDDT, ipTM, PAE, (3) Checking sequence liabilities (cysteines, deamidation, polybasic clusters), (4) Creating multi-stage…
protein-qc
Quality control metrics and filtering thresholds for protein design. Use this skill when: (1) Evaluating design quality for binding, expression, or structure, (2) Setting filtering thresholds for pLDDT, ipTM, PAE, (3) Checking sequence liabilities (cysteines, deamidation, polybasic clusters), (4) Creating multi-stage…
academic-paper-to-chinese-insight-pdf
Turn an academic paper PDF into a high-quality Chinese insight report and export it as a polished Chinese PDF. Use when asked to read a paper, translate or summarize a paper into Chinese, extract the paper's core ideas, produce original insights/opinions, explain the paper in simpler language, or deliver a Chinese PDF…
chinese-pdf-document-workflows
Class-level workflow for extracting, converting, editing, and producing polished Chinese PDFs and document reports from PDFs, papers, webpages, markdown, and video transcripts. Use when asked to create Chinese PDF reports, fix Chinese font/glyph rendering, summarize academic papers into Chinese insight reports…