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/fridrichmethod/awesome-skills/acmg-classificationnpx skills add FridrichMethod/awesome-skills --skill acmg-classificationgit clone --depth 1 https://github.com/FridrichMethod/awesome-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/fridrichmethod/awesome-skills/acmg-classification)<a href="https://agentmods.dev/skills/fridrichmethod/awesome-skills/acmg-classification"><img src="https://agentmods.dev/badge/skills/fridrichmethod/awesome-skills/acmg-classification.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 | $0.00167 | $0.07988 |
| Opus 5 | $0.00084 | $0.03994 |
| Sonnet 5 | $0.00033 | $0.01598 |
| Haiku 4.5 | $0.00017 | $0.00799 |
Grade A, and why
bio-clinical-databases-acmg-classification 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
r = requests.get(f'https://api.genebe.net/cloud/api-public/v1/variant', The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
What ships with it
2 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 · 468 lines · 167 tokens per session scan A 398ed0fd765f
bio-clinical-databases-acmg-classification is a skill published in the GitHub repository FridrichMethod/awesome-skills (14 stars, last pushed 5d ago), with no licence file. It adds 167 tokens to every session and 7,988 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 2026-08-30.
Other skills, from other repositories
academic-paper-writer
Draft economics papers with proper structure and academic style.
bear-counter
给一句话或一段话，找出真实学术文献来反对它——相反结论、边界条件、替代解释、方法批评、复制失败。按威胁程度排序，每篇附一行"它如何威胁这个观点"和"怎么回应它"。底层走真实检索（scimaster-cli），绝不编造反例。 以下情况请主动触发本技能：用户想"提前挡住审稿人"、"找这个结论的反例"、"这个方向有没有争议"、"有没有跟这个相反的研究"、"帮我攻击这个论点"、"这个结论稳不稳"、"想知道有哪些反对意见"——即使用户没有说"bear-counter"，只要意图是为一个观点寻找学术反对证据，就使用本技能。bear-support 和 bear-counter 配对使用效果最好：对同一段话各跑一遍，就能同时看到正反两面。…
compute-env-setup
Set up and validate a reproducible Python or R environment on a Wisp execution context. Use for a selected local, WSL, or direct SSH context when installing scientific packages, configuring caches, recording interpreter activation, or producing an environment smoke test. Do not use for scheduler clusters or managed…
bio-clinical-biostatistics-survival-analysis
Performs time-to-event analysis for clinical trials including Cox proportional hazards regression with PH diagnostics, restricted mean survival time (RMST) under non-PH, competing risks via Fine-Gray vs cause-specific Cox, weighted log-rank and MaxCombo for non-proportional hazards, recurrent events (Andersen-Gill…
bio-clinical-biostatistics-bayesian-trials
Designs Bayesian clinical trials including Phase I dose-finding (BOIN, CRM, EWOC, mTPI-2), meta-analytic-predictive (MAP) priors with robust mixtures for external data borrowing, EXNEX for basket trials, hierarchical models for safety AE (Berry-Berry), Bayesian platform trials (I-SPY 2, GBM AGILE, REMAP-CAP), and…
bio-clip-seq-clip-peak-calling
Call protein-RNA binding sites from CLIP-seq BAM with CLIPper, PureCLIP, Skipper, Piranha, omniCLIP, CTK, CLAM, or Paraclu. Use when choosing between coverage-based, HMM-based, beta-binomial window-based, and crosslink-site-based peak callers; applying ENCODE eCLIP thresholds (log2 IP/SMInput >= 3, -log10 p >= 3)…