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 Borda/vision-delivery --skill recognize-pose-or-gesturegit clone --depth 1 https://github.com/Borda/vision-deliveryWrote 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/borda/vision-delivery/recognize-pose-or-gesture)<a href="https://agentmods.dev/skills/borda/vision-delivery/recognize-pose-or-gesture"><img src="https://agentmods.dev/badge/skills/borda/vision-delivery/recognize-pose-or-gesture/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/borda/vision-delivery/recognize-pose-or-gesture"><img src="https://agentmods.dev/badge/skills/borda/vision-delivery/recognize-pose-or-gesture.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 | $0.00158 | $0.01140 |
| Opus 5 | $0.00079 | $0.00570 |
| Sonnet 5 | $0.00032 | $0.00228 |
| Haiku 4.5 | $0.00016 | $0.00114 |
Grade A, and why
recognize-pose-or-gesture 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.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Turn keypoints or temporal keypoint sequences into a pose/gesture decision that clears independent acceptance. Keep pose estimation, identity association, and business-rule classification as separately measured stages.
Platform execution boundary. Read ../../resources/roboflow-platform-lookup.md before any provider-specific search, dataset, training, inference, workflow, or deployment action. Use installed official Roboflow skills or current MCP resources only for read-only discovery and sourced action-brief inputs; never invoke provider execution. Do not freeze model families, IDs, or platform recipes in Sentinel.
Follow ../../resources/fde-methodology.md; apply these keypoint-specific rules.
1. Define the action and time window
Inspect footage, annotations, rules, code, and camera placement. Clarify whether the output is a per-frame posture, a hand/body gesture, a timed action, an ergonomics measurement, or a safety alert. Ask:
- Which joints/keypoints and time window determine the action?
- Must identity persist across frames?
- Which error is worse for the operator: a miss or false alert?
If the task only needs identity/path/dwell, route to track-and-count. Per-person PPE without a keypoint requirement routes to detect-and-analyze.
Freeze the evidence gate:
Acceptance ID: <session/revision>
Business decision: <alert/action enabled by pose or gesture>
Gold set: <independent keypoints/events, subject/site split, adjudicator>
Primary metric and threshold: <keypoint quality/event recall/F1/angle error>
Secondary guardrails: <false alerts/hour, latency, subject/site floors>
Frozen before baseline: <timestamp and confirmation>
Baseline result (diagnostic only): <not run yet>
2. Freeze the keypoint contract
Record keypoint names/order, coordinate convention, confidence/missing-point semantics, left/right definition, person association, frame timestamps, and rule thresholds. For temporal events, define start/end, minimum duration, cooldown, and partial-visibility behavior before evaluation.
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 · 95 lines · 158 tokens per session scan A 0b7c0584170f
recognize-pose-or-gesture is a skill published in the GitHub repository Borda/vision-delivery (4 stars, last pushed 29d ago), licensed Apache-2.0. It adds 158 tokens to every session and 1,140 once invoked, about $0.0008 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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