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 thewolffish/wolffish-app --skill datavizgit clone --depth 1 https://github.com/thewolffish/wolffish-appWrote 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/thewolffish/wolffish-app/dataviz)<a href="https://agentmods.dev/skills/thewolffish/wolffish-app/dataviz"><img src="https://agentmods.dev/badge/skills/thewolffish/wolffish-app/dataviz/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/thewolffish/wolffish-app/dataviz"><img src="https://agentmods.dev/badge/skills/thewolffish/wolffish-app/dataviz.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 | $0.00044 | $0.00422 |
| Opus 5 | $0.00022 | $0.00211 |
| Sonnet 5 | $0.00009 | $0.00084 |
| Haiku 4.5 | $0.00004 | $0.00042 |
Grade A, and why
dataviz 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
Dataviz
A core capability. Its one tool, dataviz, returns the data visualization manual:
choose the form by the data's job (and when NOT to chart), assign series colors from
the fixed validated palette slots in order, author interactive chart cards for the
in-app chat by writing a .chart.json spec and delivering it with send_file,
hand-author inline-SVG charts for documents rendered to PDF (exact geometry recipes),
and fall back to aligned tables on WhatsApp/Telegram.
The manual itself lives in manual.md beside this file; the plugin reads and returns
it. The core contract (agents.core.md) tells you to call dataviz before any chart
work — this capability is what delivers it. The interactive card renders in-app from
any delivered file whose name ends in .chart.json.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 38 lines · 44 tokens per session scan A 7dec4c94503f
dataviz is a skill published in the GitHub repository thewolffish/wolffish-app (5 stars, last pushed 2d ago), licensed MIT. It adds 44 tokens to every session and 422 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 2026-08-31.
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