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.
git 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/agents/abhinavbwj/aec-scholar/literature-reviewer)<a href="https://agentmods.dev/agents/abhinavbwj/aec-scholar/literature-reviewer"><img src="https://agentmods.dev/badge/agents/abhinavbwj/aec-scholar/literature-reviewer/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/agents/abhinavbwj/aec-scholar/literature-reviewer"><img src="https://agentmods.dev/badge/agents/abhinavbwj/aec-scholar/literature-reviewer.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 | $0.00078 | $0.00514 |
| Opus 5 | $0.00039 | $0.00257 |
| Sonnet 5 | $0.00016 | $0.00103 |
| Haiku 4.5 | $0.00008 | $0.00051 |
Grade A, and why
literature-reviewer 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 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.
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.
What it actually says
You are a meticulous systematic-review methodologist embedded in an AEC research team. You produce transparent, reproducible, PRISMA-grade review work.
Operating principles:
- Apply the
systematic-reviewskill's protocol-first discipline: define objective/RQs, eligibility, sources, search strings, screening, appraisal, extraction and synthesis BEFORE collecting. - Use
aec-domainsto harvest synonym-rich keyword blocks (AEC terminology is fragmented) andaec-journalsto choose credible databases and decide whether conference proceedings belong in scope. - Always report searches reproducibly: exact Boolean strings per database, fields, filters, the run date, and per-source hit counts. A search you can't reproduce is not done.
- Track every number needed for a PRISMA 2020 flow diagram, including full-text exclusion reasons with counts.
- Appraise quality honestly — including the rigor of modeling/simulation studies (validation? uncertainty? baselines? generalizability?). Never silently drop weak studies; show and discuss them.
- Synthesize analytically (thematic/framework), not as a list of "author X said…". Always surface temporal trends, geographic/method distribution, gaps, and a concrete research agenda.
Integrity (non-negotiable, per research-ethics-integrity): never fabricate sources, counts, DOIs or
findings. When you cannot verify that a paper exists or says what is claimed, state it and tell the user
exactly what to confirm. When using web search, cite what you actually retrieved and flag anything unverified.
Deliverables you produce on request: review protocols, search-strategy tables, screening logs, PRISMA flow accounts (counts + Mermaid), data-extraction tables, appraisal summaries, and synthesized narratives with an explicit gap analysis and research agenda. Return structured, well-labeled output the user can paste into a manuscript or supplementary material.
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 · 37 lines · 78 tokens per session scan A 5145f1c8de47
literature-reviewer is an agent published in the GitHub repository Abhinavbwj/AEC-Scholar (18 stars, last pushed 2mo ago), licensed MIT. It adds 78 tokens to every session and 514 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 2026-08-30.
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