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 beita6969/ScienceClaw --skill clinical-trialgit clone --depth 1 https://github.com/beita6969/ScienceClawWrote 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/beita6969/scienceclaw/clinical-trial)<a href="https://agentmods.dev/skills/beita6969/scienceclaw/clinical-trial"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/clinical-trial/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/beita6969/scienceclaw/clinical-trial"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/clinical-trial.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 | $0.00050 | $0.00702 |
| Opus 5 | $0.00025 | $0.00351 |
| Sonnet 5 | $0.00010 | $0.00140 |
| Haiku 4.5 | $0.00005 | $0.00070 |
Grade A, and why
clinical-trial 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to Trigger
Activate this skill when the user mentions:
- Clinical trial design, RCT, randomized controlled trial
- Sample size calculation, power analysis for trials
- CONSORT, STROBE, SPIRIT guidelines
- Phase I, II, III, IV trials
- Primary/secondary endpoints, composite endpoints
- Interim analysis, adaptive trial design, futility
- Blinding, randomization, allocation concealment
- Intention-to-treat (ITT), per-protocol analysis
Step-by-Step Methodology
- Define the research question - Specify PICO (Population, Intervention, Comparator, Outcome). Determine if superiority, non-inferiority, or equivalence design is appropriate.
- Select trial phase and design - Choose phase (I: safety/dose, II: efficacy signal, III: confirmatory, IV: post-market). Consider parallel, crossover, factorial, or adaptive designs.
- Primary endpoint selection - Define primary outcome (must be clinically meaningful). Specify measurement timing and minimal clinically important difference (MCID).
- Sample size calculation - Specify alpha (typically 0.05, two-sided), power (typically 80-90%), expected effect size, and dropout rate. Use appropriate formula for the endpoint type (continuous, binary, time-to-event).
- Randomization and blinding - Recommend randomization method (simple, block, stratified, minimization). Specify blinding level (open-label, single, double, triple).
- Statistical analysis plan - Pre-specify primary analysis method (t-test, chi-square, log-rank, mixed models). Define interim analysis schedule with alpha-spending function (O'Brien-Fleming, Lan-DeMets).
- Reporting - Follow CONSORT for RCTs, STROBE for observational, SPIRIT for protocols. Include flow diagram, enrollment numbers, and all pre-specified analyses.
Key Databases and Tools
- ClinicalTrials.gov - Trial registration and results
- Cochrane Library - Systematic reviews of trials
- FDA / EMA guidance documents - Regulatory requirements
- nQuery / PASS / G*Power - Sample size software
- CONSORT / SPIRIT checklists - Reporting standards
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 · 54 lines · 50 tokens per session scan A 5c30feaf0633
clinical-trial is a skill published in the GitHub repository beita6969/ScienceClaw (898 stars, last pushed 3mo ago), licensed MIT. It adds 50 tokens to every session and 702 once invoked, about $0.0003 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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