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/commands/abhinavbwj/aec-scholar/journal-match)<a href="https://agentmods.dev/commands/abhinavbwj/aec-scholar/journal-match"><img src="https://agentmods.dev/badge/commands/abhinavbwj/aec-scholar/journal-match/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/commands/abhinavbwj/aec-scholar/journal-match"><img src="https://agentmods.dev/badge/commands/abhinavbwj/aec-scholar/journal-match.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 | $0.00015 | $0.00423 |
| Opus 5 | $0.00008 | $0.00211 |
| Sonnet 5 | $0.00003 | $0.00085 |
| Haiku 4.5 | $0.00002 | $0.00042 |
Grade A, and why
journal-match 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 9d 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
Recommend publication venues for: $ARGUMENTS
Use the aec-domain-expert agent and the aec-journals skill.
-
Characterize the manuscript. Topic + subfield (
aec-domains), method/contribution type (technical method vs empirical/management vs performance/energy vs review), intended audience (methodological / practitioner / policy), and the authors' ambition/career stage if stated. -
Recommend venues. Provide a primary recommendation + 2–3 alternates spanning ambition levels. For each, give: the venue name and publisher/society, why it fits (scope match to the manuscript), the audience, typical selectivity, and whether it's the right "altitude". Map technical-method work to Automation in Construction / Advanced Engineering Informatics / J. Computing in Civil Eng.; management/ empirical to JCEM / Construction Management & Economics / ECAM; performance/energy to Energy and Buildings / Building and Environment; reviews to high-impact review-friendly venues; and note relevant conferences (ISARC, CIB W78, ASCE CRC, IBPSA) where appropriate.
-
Practical factors. Note open-access options/APCs, typical turnaround, and any scope caveats — and tell the user to verify current scope, impact metrics, APC and policy on the publisher's site (these change yearly; don't state them as fixed).
-
Fit check & next steps. Briefly assess whether the manuscript is ready for the primary target or needs strengthening first, and offer a pre-submission peer review (
/aec-scholar:peer-review).
Integrity: don't fabricate impact factors or acceptance rates; describe relative standing qualitatively and direct the user to authoritative current sources (JCR/CiteScore/Scopus).
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.
- 9d ago First seen · 31 lines · 15 tokens per session scan A e4ce8b0f522b
journal-match is a command published in the GitHub repository Abhinavbwj/AEC-Scholar (18 stars, last pushed 2mo ago), licensed MIT. It adds 15 tokens to every session and 423 once invoked, about $0.0001 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.