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 Abhinavbwj/AEC-Scholar --skill bibliometric-analysisgit clone --depth 1 https://github.com/Abhinavbwj/AEC-ScholarWrote 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/abhinavbwj/aec-scholar/bibliometric-analysis)<a href="https://agentmods.dev/skills/abhinavbwj/aec-scholar/bibliometric-analysis"><img src="https://agentmods.dev/badge/skills/abhinavbwj/aec-scholar/bibliometric-analysis/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/abhinavbwj/aec-scholar/bibliometric-analysis"><img src="https://agentmods.dev/badge/skills/abhinavbwj/aec-scholar/bibliometric-analysis.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 | $0.00116 | $0.01472 |
| Opus 5 | $0.00058 | $0.00736 |
| Sonnet 5 | $0.00023 | $0.00294 |
| Haiku 4.5 | $0.00012 | $0.00147 |
Grade A, and why
bibliometric-analysis 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 10d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bibliometric & Scientometric Analysis — Method Guide
Bibliometrics quantitatively maps a field's structure and evolution. In AEC it is widely used to frame review papers. Used well it is rigorous; used badly it is "descriptive statistics dressed as insight" — push for interpretation, not just colourful network pictures.
1. Two complementary analysis families
Performance analysis (productivity & impact): publications per year, most-productive/most-cited authors, institutions, countries, journals; citation counts; h/g-index; Bradford's law (core journals); Lotka's law (author productivity). Science mapping (structure & dynamics):
- Co-citation (of references/authors/journals) → intellectual base / foundational works.
- Bibliographic coupling (shared references) → current research fronts / active clusters.
- Co-word / keyword co-occurrence → conceptual/thematic structure & trends.
- Co-authorship → social/collaboration structure (authors, institutions, countries).
- Thematic evolution / overlay timelines → how themes rise, merge, fade (CiteSpace bursts; Bibliometrix thematic map quadrants: motor / niche / emerging-declining / basic themes).
2. Workflow
- Define scope & query (same rigor as a systematic search — see
systematic-review). Bibliometrics is only as good as the export. Document the database, exact query, filters, and export date. - Choose ONE primary database for the structured analysis (Scopus or Web of Science) because citation/ reference metadata is not mergeable cleanly across them; you may report coverage from both. OpenAlex/ Dimensions are open alternatives. Note coverage limits (conferences, books, non-English under-indexed).
- Export full records + cited references (Scopus: CSV/RIS/BibTeX with references; WoS: tab-delimited/ plain text "Full Record and Cited References").
- Clean the data — this is where credibility is won or lost:
- Disambiguate author names (initials collisions), unify institution/country variants.
- Merge keyword synonyms & spelling variants (BIM / "building information modeling" / "building information modelling"; "life cycle assessment" / LCA) via a thesaurus file (VOSviewer supports one).
- Remove stop-words / overly generic terms.
- Analyze with a tool (below). Choose the analysis to the question — don't run all of them by reflex.
- Interpret — name and explain clusters, link to the narrative, identify gaps and a research agenda.
Validate clusters against domain knowledge (
aec-domains); a cluster the field wouldn't recognize is a data-cleaning artifact.
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.
- 10d ago First seen · 90 lines · 116 tokens per session scan A f079ec1113ec
bibliometric-analysis is a skill published in the GitHub repository Abhinavbwj/AEC-Scholar (18 stars, last pushed 2mo ago), licensed MIT. It adds 116 tokens to every session and 1,472 once invoked, about $0.0006 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 2026-08-30.
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