Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/jokull/icelandic-datanpx agentmods add skills/jokull/icelandic-data/hafogvatnWrote 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/jokull/icelandic-data/hafogvatn)<a href="https://agentmods.dev/skills/jokull/icelandic-data/hafogvatn"><img src="https://agentmods.dev/badge/skills/jokull/icelandic-data/hafogvatn/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/jokull/icelandic-data/hafogvatn"><img src="https://agentmods.dev/badge/skills/jokull/icelandic-data/hafogvatn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00033 | $0.00243 |
| Opus 5 | $0.00016 | $0.00121 |
| Sonnet 5 | $0.00007 | $0.00049 |
| Haiku 4.5 | $0.00003 | $0.00024 |
Grade A, and why
hafogvatn 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
Hafrannsóknastofnun — Marine and Freshwater Research Institute
MFRI publishes annual stock advice with current assessment tables embedded as JSON inside static HTML pages.
Data
Catalogue: https://www.hafogvatn.is/en/moya/extras/categories/radgjof
The current cod table has assessment summaries, landings, advice/TAC history,
catch-at-age and survey series. Its stable pattern is
/static/extras/images/1_cod_{year}_1_tables_en.html.
Usage
uv run python scripts/hafogvatn.py list
uv run python scripts/hafogvatn.py fetch --stock cod --year 2026
Caveats
- Assessment vintages revise historic estimates: retain publication year.
- The per-stock table schemas and assessment methods differ.
- The old
data.hafro.isCSV archive is useful historically but is not the current annual publication channel.
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 · 32 lines · 33 tokens per session scan A c4b4071e3583
hafogvatn is a skill published in the GitHub repository jokull/icelandic-data (52 stars, last pushed yesterday), licensed MIT. It adds 33 tokens to every session and 243 once invoked, about $0.0002 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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