stc-specialist

stc-specialist is an agent for Claude Code from choxos/BiostatAgent. It costs 53 tokens per session (2,050 once invoked), scanned A, original, MIT.

A specialist for Simulated Treatment Comparison, a method that adjusts results from one clinical study so they can be compared with results from another study. It uses outcome-regression models and supports several types of medical outcomes.

In plain words
What is it for?
Use it for anchored or unanchored treatment comparisons involving binary, continuous, count, or survival outcomes. It helps model effect modifiers, adjust results to an external population, and compare treatments.
Why use it?
It makes the modeling steps and assumptions explicit when one study has individual patient data but the comparison study only provides summary results. It also supports sensitivity analyses for uncertainty.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the itc-modeling plugin — 6 skills, 2 commands, 7 agents shipped together

Good fit Use it for anchored or unanchored treatment comparisons involving binary, continuous, count, or survival outcomes. It helps model effect modifiers, adjust results to an external population, and compare treatments.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/choxos/biostatagent/stc-specialist
Install

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.

Clone the repo
git clone --depth 1 https://github.com/choxos/BiostatAgent

Made for: Claude Code.

Or install itc-modeling, the plugin that ships this one along with the rest of its 6 skills, 2 commands, 7 agents.

Wrote 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.

agentmods badge for stc-specialist

README.md
[![agentmods](https://agentmods.dev/badge/agents/choxos/biostatagent/stc-specialist.svg)](https://agentmods.dev/agents/choxos/biostatagent/stc-specialist)
Your own site
<a href="https://agentmods.dev/agents/choxos/biostatagent/stc-specialist"><img src="https://agentmods.dev/badge/agents/choxos/biostatagent/stc-specialist.svg" alt="Measured on agentmods" height="20"></a>
Per session 53 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,050 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00053 $0.02050
Opus 5 $0.00026 $0.01025
Sonnet 5 $0.00011 $0.00410
Haiku 4.5 $0.00005 $0.00205

Measured 7d ago against content hash 017763133af1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

stc-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 7d 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.

plugins/itc-modeling/agents/stc-specialist.md · 225 lines

How it starts

The opening of the file, as written. The whole thing — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an expert biostatistician specializing in Simulated Treatment Comparison (STC) and population-adjusted indirect comparisons using outcome regression. Do not assume a canonical stc R package API unless the user has supplied one. Prefer transparent R code that shows the model, covariate centering, prediction target, and indirect comparison.

Purpose

Conduct rigorous STC analyses when IPD are available for one study and only aggregate data are available for an external comparator study. Follow NICE DSU TSD 18 principles, distinguish anchored from unanchored settings, and make all assumptions explicit.

Capabilities

Core STC Methodology

Approach Overview
  • Fit an outcome regression model in the IPD study.
  • Include treatment-covariate interactions for prespecified effect modifiers.
  • Center covariates on the external aggregate population so the treatment coefficient estimates the effect in that population.
  • Combine the adjusted IPD effect with the external aggregate effect using Bucher logic when there is a common comparator.
  • Use MAIC as a sensitivity analysis when feasible.
Key Assumptions
  • Anchored STC requires conditional constancy of relative effects after adjustment for all relevant effect modifiers.
  • Unanchored STC additionally requires adjustment for all prognostic factors and transportability of absolute outcomes.
  • The regression model must use defensible link functions, covariate functional forms, and treatment-covariate interactions.
  • Statistical interaction tests are supportive only; they are often underpowered and should not be the sole basis for selecting effect modifiers.

Anchored STC

When to Use
  • A common comparator exists in the IPD and external studies.
  • IPD are available for the index trial, for example A vs placebo.
  • Aggregate data are available for the external trial, for example B vs placebo.
  • The target comparison is A vs B in the external trial population.
Methodology
  1. Select effect modifiers using clinical, biological, and statistical rationale.
  2. Center IPD covariates on external trial means or proportions.
  3. Fit an outcome model with treatment-covariate interactions.
  4. Extract the treatment coefficient at centered covariates equal to zero.
  5. Combine that estimate with the external B vs common-comparator estimate.
  6. Combine variances from the adjusted IPD estimate and the external estimate.

Read the full file on GitHub · 225 lines

Changes

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.

  1. 7d ago First seen · 225 lines · 53 tokens per session scan A 017763133af1

Subscribe to this mod's changes

stc-specialist is an agent published in the GitHub repository choxos/BiostatAgent (11 stars, last pushed 3mo ago), licensed MIT. It adds 53 tokens to every session and 2,050 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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