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 chgagne/claude-skills-research --skill surveying-literaturegit clone --depth 1 https://github.com/chgagne/claude-skills-researchWrote 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/chgagne/claude-skills-research/surveying-literature)<a href="https://agentmods.dev/skills/chgagne/claude-skills-research/surveying-literature"><img src="https://agentmods.dev/badge/skills/chgagne/claude-skills-research/surveying-literature/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/chgagne/claude-skills-research/surveying-literature"><img src="https://agentmods.dev/badge/skills/chgagne/claude-skills-research/surveying-literature.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 | $0.00081 | $0.02115 |
| Opus 5 | $0.00041 | $0.01058 |
| Sonnet 5 | $0.00016 | $0.00423 |
| Haiku 4.5 | $0.00008 | $0.00212 |
Grade A, and why
surveying-literature 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 7d 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 — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Surveying Literature
Overview
Two modes over one retrieval layer.
Gap sweep — from a draft, find work it should have cited. Expands outward from the bibliography through the citation graph and searches the draft's own topic directly, then grades each candidate by how much it threatens the novelty claim.
Field map — from a topic, cluster the area into lines of work and order them chronologically.
The gap sweep is the one that changes papers. A reviewer who knows the area will name the omission in the first paragraph of their review; this finds it first.
Run it
# gap sweep
python3 ~/.claude/skills/surveying-literature/assets/run-survey.py . \
--out review-assets/
# what the draft yields, without spending any API budget
python3 ~/.claude/skills/surveying-literature/assets/run-survey.py . --seeds-only
# field map
python3 ~/.claude/skills/surveying-literature/assets/run-survey.py . \
--field-map "symbolic regression" --out review-assets/
Run by absolute path from the paper directory. Stdlib only — no install, no dependencies.
--max-per-seed N(default 20) results per lookup;--max-angles N(default 10) topical queries. Both bound cost.--min-shared N(default 3) references two papers must share to cluster in field-map mode.- Exit code
2means source coverage was degraded — see When a source is down.
Writes related-work-gaps-<date>.md + candidates.json, or lit-review-<date>.md.
Always run --seeds-only first. It makes no requests and shows exactly what the sweep
will search for. If the angles look wrong, the results will be wrong, and you will have
spent budget finding that out.
Where candidates come from
Four discovery paths, and the report names which one found each candidate:
| Path | What it reaches |
|---|---|
backward |
what the cited papers cite — intellectual ancestors |
forward |
what cites them — descendants |
related |
the index's own similarity edge |
topical |
direct search on the draft's title, abstract concepts and contributions |
What ships with it
15 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.
- assets/run-survey.py 627 B runs code
- assets/survey/__init__.py 0 B runs code
- assets/survey/__main__.py 4.8 KB runs code
- assets/survey/fieldmap.py 3.0 KB runs code
- assets/survey/rank.py 3.4 KB runs code
- assets/survey/report.py 3.6 KB runs code
- assets/survey/seeds.py 7.8 KB runs code
- assets/survey/traverse.py 17 KB runs code
- assets/tests/test_fieldmap.py 3.1 KB runs code
- assets/tests/test_rank.py 4.5 KB runs code
- assets/tests/test_report.py 3.2 KB runs code
- assets/tests/test_seeds.py 9.0 KB runs code
- assets/tests/test_stdlib_only.py 888 B runs code
- assets/tests/test_traverse.py 14 KB runs code
- reference/reading-a-gap-report.md 4.4 KB
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.
- 7d ago Changed · +10 lines c6c0890bb9fa
- 12d ago First seen · 161 lines · 81 tokens per session scan A ef5529befc56
surveying-literature is a skill published in the GitHub repository chgagne/claude-skills-research (4 stars, last pushed 7d ago), licensed MIT. It adds 81 tokens to every session and 2,115 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 2026-08-31.
Other skills, from other repositories
literaturverzeichnispruefung
Verify academic references and bibliographies for citation errors and AI hallucinations using live database APIs (OpenAlex, OpenAIRE, K10plus, lobid, DNB, Crossref, Semantic Scholar, ZBW EconBiz, Open Library, arXiv, Library of Congress, GESIS). Trigger whenever a user wants to check, verify, or validate ANY…
secure-auth
Secure authentication patterns (OWASP, NIST). Use for login, registration, password reset, sessions, JWT, OAuth, MFA, passkeys.
academic-writing
Scholarly writing and research compliance. Use for CRediT, preregistration, Plan S, Nelson Memo, preprints, ORCID, LLM disclosure.
page-monitoring
Web page change detection, availability tracking, and RSS feed generation. Use to monitor changes, downtime, or make a feed.
web-archiving
Web archiving and retrieval via Wayback Machine and Archive.today. Use to preserve content, reach dead pages, or save evidence.
accessibility-compliance
Web accessibility patterns for news and academic sites. Use for WCAG audits, alt text, accessible data viz, and assistive tech.