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/vanessamarely/ai-playbook-repositoWrote 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/commands/vanessamarely/ai-playbook-reposito/scan-workspace)<a href="https://agentmods.dev/commands/vanessamarely/ai-playbook-reposito/scan-workspace"><img src="https://agentmods.dev/badge/commands/vanessamarely/ai-playbook-reposito/scan-workspace/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/commands/vanessamarely/ai-playbook-reposito/scan-workspace"><img src="https://agentmods.dev/badge/commands/vanessamarely/ai-playbook-reposito/scan-workspace.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 | $0.00777 |
| Opus 5 | $0.00000 | $0.00388 |
| Sonnet 5 | $0.00000 | $0.00155 |
| Haiku 4.5 | $0.00000 | $0.00078 |
Grade A, and why
scan-workspace 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 10d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scan Workspace
Identify the project type within a target folder, determine which rules/commands apply, and verify that AI tool instruction files (GitHub Copilot, Claude Code, Cursor, OpenAI Codex CLI) are present and up to date.
Inputs
targetFolder: absolute or relative path to the project root.
Outputs
A structured report containing:
projectType: detected type (e.g.,react,node-typescript,java-spring,python-fastapi).rules/commands: applicable Cursor rules and commands for this project type.aiTools: presence/absence of each AI tool's instruction files.warnings: issues detected (missing dependencies, inconsistent configuration, missing AI tool files).
Procedure
-
Validate the target folder — verify it exists and is readable. If validation fails, report the error and stop.
-
Detect the project type — inspect the folder for
package.json(+tsconfig.jsonfor TypeScript, and dependencies for React/Express/Nest/Fastify),pom.xml/build.gradle(Java),pyproject.toml/setup.py/requirements.txt(Python). ExtractprojectType,framework,language. -
Map to rules and commands:
Project Type Auto-loaded rules Relevant commands reactreact-components,a11y-automation,frontend-policy/react-component-builder,/a11y-audit-react,/figma-component-buildernode-typescriptnode-typescript-service,backend-policy/node-microservice-builderjava-spring/python-fastapibackend-policyonly (no dedicated rule yet)— unknown— fall back to manual inspection -
Check AI tool instruction files in
targetFolder:AI Tool File(s) GitHub Copilot .github/copilot-instructions.md,.github/instructions/*.instructions.mdClaude Code CLAUDE.md,.claude/Cursor .cursor/rules/*.mdcOpenAI Codex CLI AGENTS.md,.agents/skills/For each missing file, add a warning, e.g.
.cursor/rules/ not found or empty. Run /ai-tool-setup to generate it.
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.
- 10d ago First seen · 62 lines · 0 tokens per session scan A 4fcbd25cec58
scan-workspace is a command published in the GitHub repository vanessamarely/ai-playbook-reposito (2 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 777 tokens. 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.