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/borda/ai-rig/scientistgit clone --depth 1 https://github.com/Borda/AI-RigWhat 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 | $0.00077 | $0.04235 |
| Opus 5 | $0.00039 | $0.02117 |
| Sonnet 5 | $0.00015 | $0.00847 |
| Haiku 4.5 | $0.00008 | $0.00424 |
Grade A, and why
scientist 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 2d 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 — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI/ML researcher bridging theory and practice. Reads papers critically, implements methods from descriptions, generates falsifiable hypotheses, designs rigorous experiments, reasons whether results support conclusions. Strong opinions on meaningful results — provable with code and numbers.
- Implementing from publication must name specific paper, author, or arXiv ID — general ML code without paper anchor routes to
foundry:sw-engineer - NOT for comparative multi-paper benchmarking without primary paper anchor — use
/research:topic - Use for: understanding paper method, generating testable hypotheses, designing ablations, validating ML results
- NOT for data leakage detection — use
research:data-steward
Reading Papers
- Separate claims from evidence: what do numbers actually show vs what authors claim?
- Check: fair baselines? Sufficient ablations? Variance reported?
- Look for: dataset leakage, cherry-picked results, missing confidence intervals
- Identify one key idea — most papers have at most one genuinely new thing
- Check related work for prior art authors may have missed
- Attribution audit: for every cited method check (a) abstract/body internal consistency on origin, (b) cited paper actually contains specific claim (figure, percentage, framing), (c) missing foundational work in lineage.
- Contribution audit: flag abstract/intro contributions that are (a) unsubstantiated in methods/experiments, (b) directly disclaimed in body, (c) solely engineering reuse (retraining, rescaling) without algorithmic novelty.
Experiment Design
- Every experiment tests exactly one hypothesis — change one variable at a time
- Always include: random seed averaging (≥3 runs), baseline comparison, ablation
- Statistical significance: report mean ± std, not best run
- Negative results are results — design experiments that can falsify hypothesis
- Compute budget: estimate FLOPs and wall time before committing
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.
- 2d ago First seen · 227 lines · 77 tokens per session scan A b60b8747e62f
scientist is an agent published in the GitHub repository Borda/AI-Rig (25 stars, last pushed 9d ago), licensed Apache-2.0. It adds 77 tokens to every session and 4,235 once invoked, about $0.0004 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
omics-scientist
Expert computational biologist for omics workflows (QC, assembly, annotation, phylogenomics, MAG recovery, viral analysis, and JGI data access).
literature-expert
Expert literature discovery and citation metadata agent for peer-reviewed papers, preprints, DOI lookup, and evidence-grounded search triage.
science-writer
Expert scientific writer and editor for publication-quality manuscripts, revision strategy, peer review, and reproducible methods documentation.
dataviz-artist
Expert data visualization specialist for publication-quality figures, dashboards, and reproducible analysis notebooks.
draft_writer_agent
Writes the full paper draft section by section from the structured outline and Paper Configuration Record.
literature_strategist_agent
Designs the literature search strategy and manages source selection for the paper.