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 AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-adaptyvgit clone --depth 1 https://github.com/AlterLab-IEU/AlterLab-Academic-SkillsWrote 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/alterlab-ieu/alterlab-academic-skills/alterlab-adaptyv)<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-adaptyv"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-adaptyv/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/alterlab-ieu/alterlab-academic-skills/alterlab-adaptyv"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-adaptyv.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 70 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00162 | $0.01649 |
| Opus 5 | $0.00081 | $0.00825 |
| Sonnet 5 | $0.00032 | $0.00330 |
| Haiku 4.5 | $0.00016 | $0.00165 |
Grade A, and why
alterlab-adaptyv scanned grade A with 1 finding 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 6d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
resp = requests.post( How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adaptyv
Adaptyv Bio runs the Foundry cloud lab: submit protein sequences and a target, the lab runs the assay, and you retrieve experimental data (binding/affinity, thermostability, expression, fluorescence). The public Foundry API drives the full lifecycle programmatically. Turnaround is on the order of weeks; confirm the current estimate from the per-experiment quote rather than assuming a fixed number.
The exact request/response shapes evolve. This skill captures the verified API contract and conventions; for the authoritative spec see the OpenAPI doc at
https://foundry-api-public.adaptyvbio.com/api/v1/openapi.jsonandhttps://docs.adaptyvbio.com.
Prefer the official tooling first
Adaptyv ships its own integrations - reach for them before hand-rolling requests:
- Official Python SDK —
github.com/adaptyvbio/adaptyv-sdk(MIT). Decorator-based: wrap a design function with@lab.experiment(target=...); readsADAPTYV_API_KEY/ADAPTYV_API_URL(and optionalADAPTYV_ORGANIZATION_ID) from the environment. Install from source (pip install -e .after cloning — no PyPI release confirmed; verify before pinning). - Adaptyv's own Claude Code skills —
github.com/adaptyvbio/protein-design-skills. Useful prior art for protein-design + Foundry workflows.
Use this skill's raw-requests recipes when the SDK is unavailable or you need fine control over the lifecycle.
Quick Start
Authentication Setup
- Create a token in the Foundry portal:
https://foundry.adaptyvbio.com/→ Organization → Settings → Tokens (pick a role: Member = read/write, Viewer = read-only; set an expiry). The token value is shown only once — copy it immediately. - Set it in your environment (never commit it):
export ADAPTYV_API_KEY="your_token_here"
Or put it in a gitignored .env:
ADAPTYV_API_KEY=your_token_here
Installation
If using the raw API directly:
uv pip install requests python-dotenv
Basic Usage
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.
- 6d ago First seen · 134 lines · 162 tokens per session scan A 40781b3c99ad
alterlab-adaptyv is a skill published in the GitHub repository AlterLab-IEU/AlterLab-Academic-Skills (66 stars, last pushed 6d ago), licensed MIT. It adds 162 tokens to every session and 1,649 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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