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 deliver-cv-projectgit 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/deliver-cv-project)<a href="https://agentmods.dev/skills/borda/vision-delivery/deliver-cv-project"><img src="https://agentmods.dev/badge/skills/borda/vision-delivery/deliver-cv-project/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/deliver-cv-project"><img src="https://agentmods.dev/badge/skills/borda/vision-delivery/deliver-cv-project.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 | $0.00166 | $0.02028 |
| Opus 5 | $0.00083 | $0.01014 |
| Sonnet 5 | $0.00033 | $0.00406 |
| Haiku 4.5 | $0.00017 | $0.00203 |
Grade A, and why
deliver-cv-project 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.
How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deliver a previously evaluated CV capability as a replayable artifact and an explicit engineering handoff. The exit criterion is not “deployment requested.” It is a completed delivery contract whose artifact kind, acceptance evidence, commands, dependencies, data boundary, rollback, and remaining external checks are truthful and tested.
<entry_gate>
Read existing code, model metadata, .vision-delivery/eval-*.md, ledger rows, generated artifacts, and sample outputs before asking questions.
Require:
- a model/pipeline identity and output schema;
- a machine-readable acceptance artifact frozen before the candidate result, with its
acceptance_id, project-relative path, and SHA-256 digest; - independent acceptance evidence for the selected version;
- the intended consumer and runtime environment.
When the user says a hosted model works, verify its current entity/version and evaluation through the upstream platform resources. When the model is local, inspect its weights/config and rerun the recorded acceptance command. If acceptance evidence is absent or stale for the selected version, route back to the owning modality skill; do not turn an unmeasured model into production merely because it exists.
For a novice request such as “make this useful in my factory,” ask at most three plain questions:
- “What should happen when the model finds something?”
- “Where do the images come from: files, an application, or a live camera?”
- “Must data stay on this machine, or may it go to a hosted service?”
</entry_gate>
Platform execution boundary. Read ../../resources/roboflow-platform-lookup.md. Use installed official Roboflow skills or current MCP skill resources only for read-only discovery. For every platform-specific export, Workflow mutation, endpoint, device, deployment, telemetry mutation, active-learning action, paid action, or data movement, emit a sourced action brief and stop for execution through an external host/provider approval control. Sentinel never invokes those actions. Sentinel owns delivery selection, acceptance, artifact hardening, and the handoff record. If no upstream source is available, stop at a scaffold; do not guess an API, model ID, container tag, endpoint, or UI path.
Step 1 — Select the delivery contract
Classify the requested outcome:
| Outcome | Artifact kind | Required proof |
|---|---|---|
| Calls a hosted provider endpoint | hosted-client |
current upstream client shape, approved data movement, live request smoke |
| Runs exported weights on the user's machine | local-runtime |
current upstream export, dependency lock, offline inference smoke |
| Contract only; transport/model unavailable | scaffold |
deterministic self-test plus explicit missing live check |
| Managed service/device configuration | provider-managed handoff plus client kind | economic/spend consent, upstream status evidence, consumer smoke |
Never call a hosted client local inference. Never call exported weights a local runtime until they load and infer with networking disabled.
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 · 166 lines · 166 tokens per session scan A 559174b6f401
deliver-cv-project is a skill published in the GitHub repository Borda/vision-delivery (4 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 166 tokens to every session and 2,028 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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