llms.txt@docs git:20260627.0e9a9bbA

Immutable. This exact content never changes and is served at /api/v1/blob/bae1da6211d18516.

# vision-delivery

> Eval-first Codex and Claude Code plugin for turning vague computer-vision requests into measured Roboflow proofs, local artifacts, paid-action guardrails, and CV economics decisions.

Use this file to orient LLMs and coding agents. Prefer the docs and repository links below over inferred behavior. The project is a plugin, not a model. Its claim is process discipline: define the eval first, measure a baseline before training, confirm before paid actions, and record provenance.

## Primary Docs

- [Documentation home](https://borda.github.io/vision-delivery/): Value proposition, quick start, features, workflow, use cases, economics, security, and agent map.
- [Quick start](https://borda.github.io/vision-delivery/quickstart/): Codex and Claude Code install, key setup, first prompt, and expected first-session behavior.
- [Use cases](https://borda.github.io/vision-delivery/use-cases/): Route selection for detection, classification, tracking, OCR, segmentation, pose, pipelines, and economics.
- [Workflow](https://borda.github.io/vision-delivery/workflow/): Eval-first sequence from context reading through baseline, proof artifacts, economics, and ledger records.
- [CV economics](https://borda.github.io/vision-delivery/economics/): Annotation, training, deployment, and managed-vs-DIY economics with assumption boundaries.
- [Roboflow skills integration](https://borda.github.io/vision-delivery/roboflow-skills/): When to use vision-delivery, Roboflow MCP tools, Roboflow's official computer-vision-skills plugin, or MCP skill resources, and why platform recipes should not be copied here.
- [Trust and safety](https://borda.github.io/vision-delivery/trust/): API keys, prose-enforced paid-action gates, local ledger behavior, pricing provenance, and evidence boundaries.
- [FAQ](https://borda.github.io/vision-delivery/faq/): Short answers for humans, search engines, and agents.
- [Benchmark overview](https://borda.github.io/vision-delivery/benchmarks/): Evidence matrix and claim boundaries.
- [B1 measured benchmark](https://borda.github.io/vision-delivery/benchmarks/b1-conveyor-detect/): Measured object detection/counting path with post-train result and caveats.
- [Repository](https://github.com/Borda/vision-delivery): Source code, plugin manifests, skills, hooks, scripts, and evals.

## Install

- [Codex plugin source](https://github.com/Borda/vision-delivery/tree/main/.codex-plugin): Codex plugin manifest.
- [Claude plugin source](https://github.com/Borda/vision-delivery/tree/main/.claude-plugin): Claude Code plugin manifest.
- [Roboflow MCP config](https://github.com/Borda/vision-delivery/blob/main/.mcp.json): MCP server configuration; requires `ROBOFLOW_API_KEY` in the host environment.
- [Roboflow official skills](https://github.com/roboflow/computer-vision-skills): Use installed local skills first for product/API truth, platform navigation, Workflows, model IDs, inference modes, training options, plans, and pricing references. If not installed, use Roboflow MCP skill resources such as `roboflow://skills/...` when the client exposes them.

## Canonical Skills

- [solve-cv-task](https://github.com/Borda/vision-delivery/tree/main/skills/solve-cv-task): Canonical CV task router and orchestrator.
- [estimate-economics](https://github.com/Borda/vision-delivery/tree/main/skills/estimate-economics): CV economics recipe for annotation, training, deployment run-rate, and managed-vs-DIY decisions.
- [detect-and-analyze](https://github.com/Borda/vision-delivery/tree/main/skills/detect-and-analyze): Object detection, counting, per-class metrics, and local proof artifacts.
- [classify-or-flag](https://github.com/Borda/vision-delivery/tree/main/skills/classify-or-flag): Image-level pass/fail and compliance workflows.
- [track-and-count](https://github.com/Borda/vision-delivery/tree/main/skills/track-and-count): Video tracking, dwell time, and line-cross counts.
- [read-text](https://github.com/Borda/vision-delivery/tree/main/skills/read-text): OCR and structured text extraction.
- [segment-and-analyze](https://github.com/Borda/vision-delivery/tree/main/skills/segment-and-analyze): Masks, contours, and area/width measurement.
- [recognize-pose-or-gesture](https://github.com/Borda/vision-delivery/tree/main/skills/recognize-pose-or-gesture): Keypoints, posture, gesture, and action recognition.

## Evidence Boundaries

- B1 has measured evidence.
- B2-B5 are fixture-defined and pending live measurements.
- Plugin-vs-plain-agent comparison is a process-efficiency claim, not a model-quality claim.
- vision-delivery can replace delivery-workflow guidance, but it should defer to installed Roboflow skills or MCP skill resources for platform-reference details.
- Deployment run-rate comes from `scripts/cost_model.py` and committed pricing snapshots; annotation and training costs must be project-backed or explicitly marked as assumptions.

## Optional

- [Full LLM context](https://borda.github.io/vision-delivery/llms-full.txt): Longer project-convention context file for agents with larger context windows.
- [Security policy](https://github.com/Borda/vision-delivery/blob/main/SECURITY.md): Vulnerability reporting and key-handling expectations.
- [Trigger evals](https://github.com/Borda/vision-delivery/tree/main/evals/trigger): Structural trigger coverage for skill frontmatter.