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 funding-landscapegit 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/funding-landscape)<a href="https://agentmods.dev/skills/abhinavbwj/aec-scholar/funding-landscape"><img src="https://agentmods.dev/badge/skills/abhinavbwj/aec-scholar/funding-landscape/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/funding-landscape"><img src="https://agentmods.dev/badge/skills/abhinavbwj/aec-scholar/funding-landscape.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 | $0.00085 | $0.01098 |
| Opus 5 | $0.00043 | $0.00549 |
| Sonnet 5 | $0.00017 | $0.00220 |
| Haiku 4.5 | $0.00009 | $0.00110 |
Grade A, and why
funding-landscape 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 12d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Funding Landscape (AEC) — Reference
Help researchers target the right funder and align proposals to how they are actually scored. Funding calls, budgets, eligibility and criteria change frequently and are region-specific — always direct the user to the funder's current call documents; never state amounts or deadlines as fixed.
1. Major funders & scheme families (orientation, verify currency)
European Union
- Horizon Europe — collaborative R&I (Pillar II clusters incl. Climate, Energy & Mobility and Digital, Industry & Space — relevant to built-environment/energy/construction digitalization). Large consortia, strong impact/implementation emphasis.
- ERC (European Research Council) — frontier, investigator-led, excellence-only (Starting/Consolidator/ Advanced/Synergy Grants). Bottom-up; ambition and novelty are everything.
- MSCA (Marie Skłodowska-Curie Actions) — fellowships & training networks (mobility, career development).
- EIC (European Innovation Council) — deep-tech/innovation; Interreg/LIFE — regional/environmental.
United Kingdom — UKRI councils, esp. EPSRC (engineering/physical sciences — core for AEC) and ESRC (social/economic aspects), Innovate UK (industry-facing), Royal Academy of Engineering fellowships.
United States — NSF (esp. Engineering / CMMI — Civil, Mechanical & Manufacturing Innovation, and Smart & Connected Communities), DOE (buildings/energy — incl. national labs like NREL/LBNL/ORNL), NIST, DOT/FHWA (infrastructure). NSF uses Intellectual Merit + Broader Impacts.
Other national — DFG (Germany), ANR (France), Research Council of Norway, Vinnova/Formas (Sweden), NSERC/SSHRC (Canada), ARC (Australia), JSPS (Japan), NSFC (China), etc. Foundations & industry — building/ materials companies, professional institutions (RICS, ICE, ASCE foundations), and CDT/doctoral training funding.
2. Typical proposal components
Title & abstract · problem & significance · state of the art & gap · aim, objectives & RQs · methodology/work plan (work packages, tasks, milestones, deliverables, Gantt) · novelty · impact & dissemination (academic, industry, policy, standards, training, open data) · feasibility & resources · team/consortium & roles · risk register & mitigation · ethics & data protection · Data Management Plan (FAIR) · budget & justification · references · CVs/track record · letters of support.
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.
- 12d ago First seen · 69 lines · 85 tokens per session scan A 1337ee77364a
funding-landscape is a skill published in the GitHub repository Abhinavbwj/AEC-Scholar (18 stars, last pushed 2mo ago), licensed MIT. It adds 85 tokens to every session and 1,098 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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