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 critical-action-identification-and-rankinggit 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/critical-action-identification-and-ranking)<a href="https://agentmods.dev/skills/ucsc-vlaa/visualclaw/critical-action-identification-and-ranking"><img src="https://agentmods.dev/badge/skills/ucsc-vlaa/visualclaw/critical-action-identification-and-ranking/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/critical-action-identification-and-ranking"><img src="https://agentmods.dev/badge/skills/ucsc-vlaa/visualclaw/critical-action-identification-and-ranking.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 | $0.00325 |
| Opus 5 | $0.00022 | $0.00162 |
| Sonnet 5 | $0.00009 | $0.00065 |
| Haiku 4.5 | $0.00004 | $0.00032 |
Grade A, and why
critical-action-identification-and-ranking 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.
What it actually says
Identify and Rank Actions by Contribution to Main Goal
- Define the end goal: Determine what the person is ultimately trying to achieve (e.g., plant seedlings, fix a frame, complete a wood project).
- Map all visible actions: List every action performed in sequence.
- Classify each action:
- Core actions: Directly move toward the end goal (e.g., picking up seedlings, dropping them in soil)
- Support actions: Enable core actions but are not themselves the goal (e.g., picking up a trowel, holding a sack)
- Select critical actions: Choose the core actions that most directly achieve the objective, not the preparatory steps.
- Verify importance: Ask: "If this action were skipped, would the main goal still be accomplished?" Core actions fail this test; support actions pass it.
Example: In Failure 5, the assistant focused on "picking the trowel" and "holding the sack," which are preparatory. The critical actions were "picking up seedlings" and "dropping them in the container"—the actions that actually plant them.
Anti-pattern: Confusing preparatory or support actions with the core actions that achieve the primary objective.
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 · 20 lines · 44 tokens per session scan A 0a10477d9558
critical-action-identification-and-ranking is a skill published in the GitHub repository UCSC-VLAA/VisualClaw (55 stars, last pushed 2mo ago), licensed MIT. It adds 44 tokens to every session and 325 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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