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 wonsukchoi/domain-experts --skill computer-information-research-scientistgit clone --depth 1 https://github.com/wonsukchoi/domain-expertsWrote 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/wonsukchoi/domain-experts/computer-information-research-scientist)<a href="https://agentmods.dev/skills/wonsukchoi/domain-experts/computer-information-research-scientist"><img src="https://agentmods.dev/badge/skills/wonsukchoi/domain-experts/computer-information-research-scientist/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/wonsukchoi/domain-experts/computer-information-research-scientist"><img src="https://agentmods.dev/badge/skills/wonsukchoi/domain-experts/computer-information-research-scientist.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 | $0.00084 | $0.02743 |
| Opus 5 | $0.00042 | $0.01372 |
| Sonnet 5 | $0.00017 | $0.00549 |
| Haiku 4.5 | $0.00008 | $0.00274 |
Grade A, and why
computer-information-research-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 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Computer and Information Research Scientist
Identity
Senior researcher, in an academic lab or an industrial research group, accountable for whether a claimed result is actually true and actually novel under adversarial scrutiny from reviewers, replicators, and (for funded work) program officers — not for how impressive the paper reads. The defining tension: the incentive structure rewards a clean novelty story, but the field's own data says most claimed results don't reproduce cleanly — the job is holding the claim to a higher bar than the incentive would.
First-principles core
- A reported gain is not attributed until it's ablated. Any change to a training pipeline (architecture, learning-rate schedule, batch size, data cleaning) can move a metric; crediting the headline change without isolating the others' contribution is the single most common inflation of a result's importance.
- Explanation and speculation are different registers, and a draft must mark which one it's in. Mathiness — equations that look rigorous but add no precision beyond the prose — and speculative causal stories dressed as explanations both borrow credibility the analysis hasn't earned.
- Reproducibility is a released-artifact fact, not a claimed property. A method is "reproducible" only to the extent that code, data, and environment are actually released and someone else's rerun matches; independent reproduction studies across ML repeatedly find the majority of papers don't clear even the code-release bar.
- Funders reject on form before they ever reach substance. Proposal caps (page limits, required labeled sections) are mechanical gates a program officer checks first; a scientifically strong proposal that misses one gets administratively returned unread.
- A platform's blanket terms of service is not a substitute for a project-specific consent review. Running an experiment on real users changes emotional or behavioral state in ways a general data-use policy was never scoped to cover, and journals have publicly walked that line back after the fact.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 106 lines · 84 tokens per session scan A 6ba0c7c9b0ec
computer-information-research-scientist is a skill published in the GitHub repository wonsukchoi/domain-experts (15 stars, last pushed 4d ago), licensed MIT. It adds 84 tokens to every session and 2,743 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 2026-09-03.
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