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 ShaishavMaisuria/research-paper-lifecycle-skills --skill literature-reviewgit clone --depth 1 https://github.com/ShaishavMaisuria/research-paper-lifecycle-skillsWrote 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/shaishavmaisuria/research-paper-lifecycle-skills/literature-review)<a href="https://agentmods.dev/skills/shaishavmaisuria/research-paper-lifecycle-skills/literature-review"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/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/shaishavmaisuria/research-paper-lifecycle-skills/literature-review"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/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 | $0.00165 | $0.03071 |
| Opus 5 | $0.00082 | $0.01536 |
| Sonnet 5 | $0.00033 | $0.00614 |
| Haiku 4.5 | $0.00016 | $0.00307 |
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 12d 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.
Never reimplement these inline (no ad-hoc `curl` against scholarly APIs); How it starts
The opening of the file, as written. The whole thing — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature Review
Produce a themed, citation-grounded review document from a research question. This skill is the orchestrator: searching, fetching, and citation verification are delegated to sibling skills; this skill owns the workspace, the screening corpus, claim extraction, thematic synthesis, and the final coverage gate.
When to use
- "Do a literature review on X" / "survey recent work on X"
- "What's the state of the art in X since 2023?"
- "Read these N papers and synthesize them by theme"
- A standalone survey is wanted. For a paper's Related Work section,
do the corpus-building phases here, then hand off to
draft-related-work.
Inputs
- A research question or topic, ideally with year range and (optionally) target venues.
CONTACT_EMAILexported for the sibling skills' API politeness contract.- Optional: an existing list of papers/DOIs the user already has.
Sibling skills this skill delegates to
| Stage | Delegate to | What it provides |
|---|---|---|
| Search | find-papers |
dblp_search.py, crossref_search.py, s2_search.py, arxiv_search.py (in that skill's script dir) — key-free, rate-limited, cached |
| Full text | fetch-paper |
resolve_oa.py — one DOI/arXiv ID → legal OA copy, transient |
| Reference check | verify-citations |
validates every BibTeX entry against Crossref/DBLP/S2, flags retractions |
Never reimplement these inline (no ad-hoc curl against scholarly APIs);
the sibling scripts carry the rate-limit, backoff, caching, and User-Agent
contract.
Process
Phase 1 — Scope
- Pin down with the user: research question, year range, inclusion and exclusion criteria (2–4 each), target size (10–15 papers is a solid default; >30 needs explicit user buy-in).
- Run
python3 scripts/init_review.py "TOPIC"— createslit-review/<slug>/withcorpus.json,themes.yml,notes/, and areview.mdskeleton. - Write the agreed criteria into
corpus.jsonundercriteria.
Phase 2 — Search (delegate to find-papers)
What ships with it
7 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.
- 12d ago First seen · 223 lines · 165 tokens per session scan A 91fe73f99224
literature-review is a skill published in the GitHub repository ShaishavMaisuria/research-paper-lifecycle-skills (42 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 165 tokens to every session and 3,071 once invoked, about $0.0008 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 2026-08-30.
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