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 UCSC-VLAA/VisualClaw --skill evidence-grounded-outputgit clone --depth 1 https://github.com/UCSC-VLAA/VisualClawWrote 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/ucsc-vlaa/visualclaw/evidence-grounded-output)<a href="https://agentmods.dev/skills/ucsc-vlaa/visualclaw/evidence-grounded-output"><img src="https://agentmods.dev/badge/skills/ucsc-vlaa/visualclaw/evidence-grounded-output/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/ucsc-vlaa/visualclaw/evidence-grounded-output"><img src="https://agentmods.dev/badge/skills/ucsc-vlaa/visualclaw/evidence-grounded-output.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 | $0.00030 | $0.00232 |
| Opus 5 | $0.00015 | $0.00116 |
| Sonnet 5 | $0.00006 | $0.00046 |
| Haiku 4.5 | $0.00003 | $0.00023 |
Grade A, and why
evidence-grounded-output 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 10d 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
Ground Every Value in Cited Evidence
- Cite every fact: Each factual value or claim must trace to a source —
[clip @ MM:SS],[doc:...],[chat:...],[audio:...],[pdf:...], or[image:...]. - Use the citation format the task specifies: Match its conventions exactly; one valid citation form per fact.
- Do not invent: If a value is not supported by the workspace, the video, or the documents, do not state it — mark it unknown or escalate instead.
- Prefer the designated arbiter: When sources conflict, follow the source the task names as authoritative.
Example: An on-hand count must come from the document the task names as the arbiter, not from a guess.
Anti-pattern: Filling a required field with a plausible number that no cited source actually supports.
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.
- 10d ago First seen · 17 lines · 30 tokens per session scan A 273ec04fb66b
evidence-grounded-output is a skill published in the GitHub repository UCSC-VLAA/VisualClaw (55 stars, last pushed 2mo ago), licensed MIT. It adds 30 tokens to every session and 232 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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