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 segment-and-analyzegit 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/segment-and-analyze)<a href="https://agentmods.dev/skills/borda/vision-delivery/segment-and-analyze"><img src="https://agentmods.dev/badge/skills/borda/vision-delivery/segment-and-analyze/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/segment-and-analyze"><img src="https://agentmods.dev/badge/skills/borda/vision-delivery/segment-and-analyze.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 | $0.00136 | $0.01116 |
| Opus 5 | $0.00068 | $0.00558 |
| Sonnet 5 | $0.00027 | $0.00223 |
| Haiku 4.5 | $0.00014 | $0.00112 |
Grade A, and why
segment-and-analyze 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Produce masks and derived measurements that clear an independently labeled acceptance gate. Pixel results are not physical measurements unless calibration, camera geometry, and uncertainty support that claim.
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. Sentinel retains the measurement contract and evidence.
Follow ../../resources/fde-methodology.md; apply these segmentation-specific requirements.
1. Define mask ownership and decision
Inspect images, masks, calibration artifacts, code, and intended action. Ask at most three missing questions:
- Is the business action driven by outline, area, maximum width, or presence?
- What independently produced masks or physical reference measurements exist?
- Must the answer be pixels/relative area, or real-world units?
Freeze before measuring a candidate:
Acceptance ID: <session/revision>
Business decision: <action enabled by mask/measurement>
Gold set: <independent masks or sensor measurements, split, adjudicator>
Primary metric and threshold: <IoU/Dice/area error/width error>
Secondary guardrails: <boundary error, false masks, latency, calibration uncertainty>
Frozen before baseline: <timestamp and confirmation>
Baseline result (diagnostic only): <not run yet>
Visual inspection without gold masks may guide diagnosis but cannot produce IoU or Dice.
2. Define the geometry contract
Record mask encoding, coordinate origin, image dimensions, empty-mask behavior, overlap ownership, and whether holes/disconnected components are retained. For derived values, define:
- area: mask pixel count and any conversion factor;
- perimeter/boundary: contour method and smoothing policy;
- width: the geometric definition, not merely a box width;
- physical units: calibration target, plane, camera setup, distortion correction, and propagated uncertainty.
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 · 94 lines · 136 tokens per session scan A c688ced05d11
segment-and-analyze is a skill published in the GitHub repository Borda/vision-delivery (4 stars, last pushed 28d ago), licensed Apache-2.0. It adds 136 tokens to every session and 1,116 once invoked, about $0.0007 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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