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 KhaledSaeed18/dotclaude --skill citation-graphgit clone --depth 1 https://github.com/KhaledSaeed18/dotclaudeWrote 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/khaledsaeed18/dotclaude/citation-graph)<a href="https://agentmods.dev/skills/khaledsaeed18/dotclaude/citation-graph"><img src="https://agentmods.dev/badge/skills/khaledsaeed18/dotclaude/citation-graph/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/khaledsaeed18/dotclaude/citation-graph"><img src="https://agentmods.dev/badge/skills/khaledsaeed18/dotclaude/citation-graph.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 | $0.00105 | $0.00942 |
| Opus 5.5 | $0.00042 | $0.00377 |
| Sonnet 5.5 | $0.00021 | $0.00188 |
| Haiku 4.5 | $0.00011 | $0.00094 |
Grade A, and why
citation-graph 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 25d 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.
`curl -s "https://api.semanticscholar.org/graph/v1/paper/DOI:<doi>?fields=paperId,title,year,citationCount"`. How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Keyword search finds papers that use your words; the citation graph finds papers that share your problem. Starting from a few papers known to be central, the works they cite and the works that cite them, weighted by how many seeds agree, surface the field's structure and its recent edge.
Inputs
Seeds: DOIs, arXiv ids, Semantic Scholar ids, or .bib keys (resolved through references.bib). Three to eight seeds work best; one seed gives a star, not a graph. Options: --depth (1: neighbours of seeds; 2: neighbours of the strongest first-degree candidates; default 1), --min-links (minimum seed connections to keep a candidate; default 2), --since YEAR for the forward direction.
Procedure
- Resolve seeds to Semantic Scholar paper ids:
curl -s "https://api.semanticscholar.org/graph/v1/paper/DOI:<doi>?fields=paperId,title,year,citationCount". - Backward: for each seed,
/paper/<id>/references?fields=paperId,title,year,externalIds,citationCount,influentialCitationCount&limit=500. Tally each referenced paper's seed count. - Forward: for each seed,
/paper/<id>/citations?fields=...&limit=1000(page withoffsetwhen over 1000; apply--since). Tally. - Co-citation (optional, strong signal): for the top forward candidates, fetch their references and count how often two seeds appear together; candidates cited alongside the seeds by many papers belong to the same conversation.
- Score each candidate:
links(distinct seeds connected),influential(Semantic Scholar's influential-citation flag counts double), citations normalised by age, and recency for the forward set. Show the formula. - Depth 2: take the top ten candidates by score, treat them as seeds, repeat steps 2 and 3, and keep only candidates linked to at least two of the original seeds.
- Cross-check each kept candidate with OpenAlex (
api.openalex.org/works/doi:<doi>) for the DOI, venue, and open-access link; drop anything that does not resolve. - Rate-limit: one request per second; on 429 wait and retry. Cache responses under
research/.graph-cache/keyed by paper id.
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.
- 25d ago First seen · 60 lines · 105 tokens per session scan A f7e81db732f1
citation-graph is a skill published in the GitHub repository KhaledSaeed18/dotclaude (5 stars, last pushed 2d ago), licensed MIT. It adds 105 tokens to every session and 942 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-22.
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