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 gioviat/research-toolkit --skill literature-reviewgit clone --depth 1 https://github.com/gioviat/research-toolkitWrote 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/gioviat/research-toolkit/literature-review)<a href="https://agentmods.dev/skills/gioviat/research-toolkit/literature-review"><img src="https://agentmods.dev/badge/skills/gioviat/research-toolkit/literature-review/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/gioviat/research-toolkit/literature-review"><img src="https://agentmods.dev/badge/skills/gioviat/research-toolkit/literature-review.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 | $0.00068 | $0.00595 |
| Opus 5 | $0.00034 | $0.00298 |
| Sonnet 5 | $0.00014 | $0.00119 |
| Haiku 4.5 | $0.00007 | $0.00060 |
Grade A, and why
literature-review scanned grade A with 1 finding 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 11d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- arXiv: `curl -sL "https://export.arxiv.org/api/query?search_query=all:%22<terms>%22&max_results=20"` How it starts
The opening of the file, as written. The whole thing — 33 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature review
Before searching
- State the exact question the survey answers: task, setting, constraints ("parameter-efficient finetuning of sub-1B LLMs", not "efficient finetuning").
- State the recency window and why (e.g. "2023 onward; earlier work covered by survey X").
- State the inclusion criteria, so omissions are auditable.
Search procedure
- Query multiple sources, not one: web search where available, plus direct API queries —
- arXiv:
curl -sL "https://export.arxiv.org/api/query?search_query=all:%22<terms>%22&max_results=20" - Semantic Scholar:
curl -s "https://api.semanticscholar.org/graph/v1/paper/search?query=<terms>&fields=title,year,venue,abstract,citationCount,externalIds"— works without a key but rate-limits (HTTP 429); back off and retry, don't drop the source silently.
- arXiv:
- Use several distinct query formulations; different communities name the same idea differently.
- Snowball: for the 2–3 most relevant papers found, follow their references and their citing papers (Semantic Scholar
/paper/<id>/referencesand/citations). - Record every query run; the survey reports them so coverage can be audited.
Citation rules (non-negotiable)
- Never cite from memory. A paper appears in the survey only after its record (arXiv page, Semantic Scholar entry, or venue page) was fetched in this session. A paper that is remembered but cannot be found is reported as "recalled but unverified", not cited.
- Report what each paper shows, not what it claims: the dataset, metric, and number from its experiments, precise enough to be checked.
- Mark each entry as peer-reviewed (with venue) or preprint.
- Do not rank results that are not comparable (different datasets, metrics, or compute); say why they aren't.
Output
Save to papers/related-work/<topic>.md:
- Question, scope, recency window, inclusion criteria.
- Comparison table: method | venue+year (or preprint) | setting | metric | result | code available.
- Gaps and open problems: what no surveyed paper addresses, stated specifically enough to seed a research question (input to the research-ideation skill).
- Coverage limits: queries run, sources searched, where the survey may be incomplete.
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.
- 11d ago First seen · 33 lines · 68 tokens per session scan A 158041c01822
literature-review is a skill published in the GitHub repository gioviat/research-toolkit (2 stars, last pushed 2mo ago), licensed MIT. It adds 68 tokens to every session and 595 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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