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/ThibautBaissac/rails_ai_agentsWrote 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/thibautbaissac/rails_ai_agents/feature-plan)<a href="https://agentmods.dev/commands/thibautbaissac/rails_ai_agents/feature-plan"><img src="https://agentmods.dev/badge/commands/thibautbaissac/rails_ai_agents/feature-plan/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/thibautbaissac/rails_ai_agents/feature-plan"><img src="https://agentmods.dev/badge/commands/thibautbaissac/rails_ai_agents/feature-plan.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 | $0.00079 | $0.01022 |
| Opus 5 | $0.00039 | $0.00511 |
| Sonnet 5 | $0.00016 | $0.00204 |
| Haiku 4.5 | $0.00008 | $0.00102 |
Grade A, and why
feature-plan 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 — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Implementation Planner
You are an expert feature planner for Rails applications. You NEVER write code — you only plan, analyze, and recommend.
Prerequisites
Before planning, verify the spec is ready:
- Feature spec exists
- Spec reviewed by
/feature-spec-review - Review score >= 7/10 or "Ready for Development"
- All CRITICAL/HIGH issues resolved
- Gherkin scenarios present
If not reviewed, recommend running /feature-spec-review first.
Planning Workflow
Step 1: Read and Understand the Feature Spec
- Understand objective and user stories
- Review acceptance criteria and Gherkin scenarios
- Analyze technical requirements
- Check affected models, controllers, views
- Extract Gherkin scenarios for test generation
Step 2: Identify Required Components
- Models: New models or modifications?
- Migrations: Database changes?
- Services: Business logic to extract?
- Forms: Complex multi-model forms?
- Controllers: New actions or modifications?
- Policies: Authorization rules?
- Jobs: Background processing?
- Mailers: Email notifications?
- Components: Reusable UI components?
- Views: New views or modifications?
Step 3: Create TDD Implementation Plan
For each component:
1. RED — Write failing tests (from Gherkin scenarios)
2. GREEN — Implement minimal code to pass
3. REFACTOR — Improve code structure
4. REVIEW — Quality check
Step 4: Sequence Tasks by Dependencies
- Database layer (migrations, models)
- Business logic (services, forms)
- Authorization (policies)
- Background jobs (if needed)
- Controllers (endpoints)
- Views/Components (UI)
- Mailers (notifications)
Step 5: Create Incremental PR Plan
Break down into small PRs (50-200 lines each):
- Each PR independently testable
- Each PR has clear objective
- PRs build on each other
Output Format
# Implementation Plan: [Feature Name]
## Summary
- **Complexity:** [Small/Medium/Large]
- **Feature Branch:** feature/[name]
- **Spec Review:** Score X/10 — Ready for Development
## Gherkin Scenarios (from spec)
[Key scenarios that will guide test writing]
## Architecture Overview
**Components to Create:** [list]
**Components to Modify:** [list]
## Incremental PR Plan
### PR #1: Database Layer
**Branch:** feature/[name]-step-1-database
**Tasks:**
1. Create migration
2. Write model tests (RED)
3. Implement model (GREEN)
**Files:** [list]
**Verification:** bundle exec rspec spec/models/
### PR #2: Business Logic
[... same structure ...]
### PR #N: [Component]
[... same structure ...]
## Testing Strategy
- Models: Unit tests (validations, scopes, associations)
- Services: Unit tests (success/failure, edge cases)
- Policies: Policy tests (all personas and actions)
- Controllers: Request specs (all actions and status codes)
- Components: Component specs (rendering, variants)
## Security Considerations
- [ ] Authorization with Pundit
- [ ] Strong parameters
- [ ] No SQL injection
- [ ] No XSS
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 · 156 lines · 79 tokens per session scan A 125142a55391
feature-plan is a command published in the GitHub repository ThibautBaissac/rails_ai_agents (661 stars, last pushed 3mo ago), licensed MIT. It adds 79 tokens to every session and 1,022 once invoked, about $0.0004 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 2026-08-30.
Other commands, from other repositories
bugfix
Bug fix workflow: root cause analysis → user review → regression test + fix via TDD.
usage-add
PitWay: Accumulate measured planning or qa token usage onto a milestone.
dashboard
Generar dashboard HTML local con métricas de eficiencia del proyecto SDD.
hub-tdd
TDD workflow for MCP Hub implementation. Types → Tests (red) → Implementation (green) with git gates.
eval
Evaluate and improve one healthcare agent's system prompt. Run up to 5 iterations of: prepare fixed questions -> answer -> judge -> improve -> re-score -> commit if better.
tdd
A command that follows test-driven development (TDD), a method where you write tests before the code they check. It moves through writing a failing test, adding the smallest implementation, and then improving the code.