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.
git clone --depth 1 https://github.com/mikeysrecipes/mcp-openvisionWrote 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/rules/mikeysrecipes/mcp-openvision/workflow-agile-manual)<a href="https://agentmods.dev/rules/mikeysrecipes/mcp-openvision/workflow-agile-manual"><img src="https://agentmods.dev/badge/rules/mikeysrecipes/mcp-openvision/workflow-agile-manual/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/rules/mikeysrecipes/mcp-openvision/workflow-agile-manual"><img src="https://agentmods.dev/badge/rules/mikeysrecipes/mcp-openvision/workflow-agile-manual.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 | $0.00000 | $0.00782 |
| Opus 5 | $0.00000 | $0.00391 |
| Sonnet 5 | $0.00000 | $0.00156 |
| Haiku 4.5 | $0.00000 | $0.00078 |
Grade A, and why
workflow-agile-manual 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.
This is a copy
100% identical to workflow-agile-manual — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agile Workflow and core memory procedure RULES that MUST be followed EXACTLY!
- When coming online, you will first check if a .ai/prd.md file exists, if not, work with the user to create one to you know what the project is about.
- If the PRD is not
status: approved, you will ONLY have the goal of helping improve the .ai/prd.md file as needed and getting it approved by the user to ensure it is the best possible document including the following:- Very Detailed Purpose, problems solved, and task sequence.
- Very Detailed Architecture patterns and key technical decisions, mermaid diagrams to help visualize the architecture.
- Very Detailed Technologies, setup, and constraints.
- Unknowns, assumptions, and risks.
- It must be formatted and include at least everything outlined in the
.cursor/templates/template-prd.md
- Once the .ai/prd.md file is created and the status is approved, you will generate the architecture document .ai/arch.md draft - which also needs to be approved.
- The template for this must be used and include all sections from the template at a minimum:
.cursor/templates/template-arch.md
- The template for this must be used and include all sections from the template at a minimum:
- Once the
.ai/arch.mdis approved, create the draft of the first story in the .ai folder. - Always use the
.cursor/templates/template-story.mdfile as a template for the story. The story will be named .story.md added to the .ai folder- Example: .ai/story-1.story.md or .ai/task-1.story.md
- You will ALWAYS wait for approval of the story before proceeding to do any coding or work on the story.
- You are a TDD Master, so you will run tests and ensure tests pass before going to the next subtask or story.
- You will update the story file as subtasks are completed.
- Once a Story is complete, you will generate a draft of the next story and wait on approval before proceeding.
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 · 49 lines · 0 tokens per session scan A b18ca3ed02e6
workflow-agile-manual is a cursor rule published in the GitHub repository mikeysrecipes/mcp-openvision (1 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 782 tokens. A static security scan graded it A with 0 findings. It is 100% identical to workflow-agile-manual, differing in 0 lines, and is treated as a copy.
Other cursor rules, from other repositories
slice-tasks
PLANNING SPINE STEP 2 of 3 — Slice the work: break a scoped PRD into vertical-slice stories in specs/epics/. Use after scope-work (step 1), before plan-work (step 3). Not a substitute for scope-work or plan-work.
iris
GitHub operations specialist — branches, pull requests, issues, releases, tags. Called by zeus after review. Never pushes or merges without explicit human approval. Integrates with VS Code GitHub Pull Requests extension.
elite-orchestrator
Elite orchestrator for mission-critical, enterprise-scale tasks requiring strategic coordination of 7+ agents across all domains. Makes architectural decisions, manages risk, ensures business continuity, and delivers enterprise-grade outcomes. Use for platform migrations, security incidents, multi-system integrations…
feedback-enhanced
Rules for an interactive feedback system that lets users and an AI agent discuss complex development work in real time. It includes guidance for recording decisions, tracking progress and handling detailed inputs such as code and diagrams.
project-onboarding-rule
Automatically onboards existing projects into the AI-driven development workflow.
linear-in-review
After finishing a Linear issue, set its status to In Review (never Done).