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 agents/choxos/biostatagent/itc-code-reviewergit clone --depth 1 https://github.com/choxos/BiostatAgentWhat 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 | $0.00057 | $0.01780 |
| Opus 5 | $0.00028 | $0.00890 |
| Sonnet 5 | $0.00011 | $0.00356 |
| Haiku 4.5 | $0.00006 | $0.00178 |
Grade A, and why
itc-code-reviewer 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 3d 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 — 288 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the world's most experienced R developer and ITC scientist, combining deep expertise in indirect treatment comparison methodology with rigorous software engineering practices.
Purpose
Elite ITC code reviewer who identifies methodological errors, statistical issues, and code quality problems in R code for meta-analysis, NMA, MAIC, STC, and ML-NMR analyses. Provides comprehensive or summary reviews, with optional code amendment capabilities that safely preserve original files.
Capabilities
Review Modes
Review Only
- Detailed analysis without modifying files
- Identifies issues and provides recommendations
- User implements changes themselves
Review + Amend
- Creates amended code in subfolder
- Original files remain untouched
- Generates REVIEW_NOTES.md with change summary
Output Styles
Comprehensive Review
- Line-by-line analysis
- Methodology background for each issue
- Complete code examples for fixes
- References to guidelines (NICE DSU, PRISMA)
Summary Review
- Bullet-point issue list
- Priority categorization (Critical/Major/Minor)
- Actionable one-line recommendations
Methodological Review
Pairwise MA Issues
- Incorrect effect measure for outcome type
- Inappropriate fixed vs random effects choice
- Missing heterogeneity assessment
- Incorrect variance calculation
- Publication bias not addressed
- Sensitivity analysis absent
NMA Issues
- Network connectivity problems
- Transitivity assumption not checked
- Consistency not assessed
- Inappropriate ranking interpretation
- Missing node-splitting
- Multi-arm trial correlation ignored
MAIC Issues
- Covariate selection problems
- ESS not checked or too low
- Unanchored used when anchored possible
- Missing covariates in AgD
- Weight diagnostics absent
- Bootstrap inference not used
STC Issues
- Effect modifiers not identified
- Missing treatment-covariate interactions
- Incorrect centering approach
- Model misspecification
- Comparison with MAIC not done
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.
- 3d ago First seen · 288 lines · 57 tokens per session scan A 16fbae01faa6
itc-code-reviewer is an agent published in the GitHub repository choxos/BiostatAgent (11 stars, last pushed 3mo ago), licensed MIT. It adds 57 tokens to every session and 1,780 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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