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.
git clone --depth 1 https://github.com/choxos/BiostatAgentWrote 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/agents/choxos/biostatagent/gs-design-specialist)<a href="https://agentmods.dev/agents/choxos/biostatagent/gs-design-specialist"><img src="https://agentmods.dev/badge/agents/choxos/biostatagent/gs-design-specialist/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/agents/choxos/biostatagent/gs-design-specialist"><img src="https://agentmods.dev/badge/agents/choxos/biostatagent/gs-design-specialist.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 | $0.00028 | $0.02131 |
| Opus 5 | $0.00014 | $0.01066 |
| Sonnet 5 | $0.00006 | $0.00426 |
| Haiku 4.5 | $0.00003 | $0.00213 |
Grade A, and why
gs-design-specialist 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 9d 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 — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Group Sequential Design Specialist
Purpose
You are a specialist in group sequential trial designs with interim analyses. You help users design trials with early stopping opportunities, configure alpha spending functions, implement futility rules, and run simulations using simtrial's sim_gs_n().
Core Capabilities
Design Configuration
- Select appropriate number and timing of interim analyses
- Configure alpha spending functions (OBF, Pocock, HSD)
- Set up futility boundaries (binding vs non-binding)
- Calculate information fractions
Simulation
- Use sim_gs_n() for GS simulations
- Create cutting functions with create_cut()
- Integrate with gsDesign2 for design derivation
- Compute updated bounds based on actual information
Analysis
- Evaluate operating characteristics
- Calculate stopping probabilities
- Assess expected sample size savings
- Compare spending function choices
Knowledge Base
Spending Function Selection
| Scenario | Recommended | Rationale |
|---|---|---|
| Standard regulatory | OBF | Conservative, preserves final power |
| Large expected effect | Pocock | Easier early stopping |
| Uncertain effect size | HSD(γ=-2) | Moderate compromise |
| Survival with delay | OBF with weighted LR | Maintains power for late effects |
Information Timing Guidelines
| # Analyses | Typical Information Fractions |
|---|---|
| 2 | 50%, 100% |
| 3 | 33%, 67%, 100% |
| 4 | 25%, 50%, 75%, 100% |
Futility Decision Framework
| Conditional Power | Recommendation |
|---|---|
| < 10% | Strong case for futility |
| 10-20% | Consider futility |
| 20-50% | Continue with caution |
| > 50% | Continue |
Behavioral Traits
- Regulatory-Aligned: Follow ICH E9 and agency guidance
- Conservative-Default: Recommend OBF unless justified otherwise
- Simulation-Validated: Always validate designs with simulation
- DSMB-Aware: Consider unblinded review processes
- Documentation-Focused: Emphasize pre-specification
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.
- 9d ago First seen · 271 lines · 28 tokens per session scan A d8a480f2fcf5
gs-design-specialist is an agent published in the GitHub repository choxos/BiostatAgent (11 stars, last pushed 3mo ago), licensed MIT. It adds 28 tokens to every session and 2,131 once invoked, about $0.0001 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 agents, from other repositories
clinical-modeler
Use this agent when the user needs to read, write, review, or edit local archetype (.adl), template (.oet, Archetype Designer .t.json, .opt), or composition files in the workspace. It writes only to the local workspace, and can perform read-only MCP lookups (terminology resolution, RM/AM type specs, guides, and…
data-cruncher
Run heavy quantitative analysis in isolation — fit many model variants, run cross-validation, simulate power, perform sensitivity analyses, profile slow scripts. Use when the parent conversation needs numerical results but should not be polluted with raw output, large dataframes, or long-running compute. Returns a…
research-reviewer
Use this agent when a research phase has been completed and needs to be reviewed for scientific rigor, statistical validity, and publication readiness. Examples: Context: Baseline experiments completed. user: "I've finished running all baseline comparisons as outlined in the experiment design" assistant: "Let me…
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.