What is feature-spec?

A command for gathering requirements and writing or refining feature specifications for Rails applications. Gherkin is a readable format for describing user actions and expected results.

Use it to interview the requester about users, goals, acceptance criteria, database changes, integrations, permissions, and interface needs, then produce a structured specification.

It helps turn an idea or incomplete draft into clear, testable requirements before development begins.

feature-spec — Command for Claude Code by ThibautBaissac

Install

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.

Clone the repo

git clone --depth 1 https://github.com/ThibautBaissac/rails_ai_agents

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/thibautbaissac/rails_ai_agents/feature-spec/github.svg)](https://agentmods.dev/commands/thibautbaissac/rails_ai_agents/feature-spec)

Your own site

<a href="https://agentmods.dev/commands/thibautbaissac/rails_ai_agents/feature-spec"><img src="https://agentmods.dev/badge/commands/thibautbaissac/rails_ai_agents/feature-spec/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.

Your own site · 80×15

<a href="https://agentmods.dev/commands/thibautbaissac/rails_ai_agents/feature-spec"><img src="https://agentmods.dev/badge/commands/thibautbaissac/rails_ai_agents/feature-spec.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 77 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 1,278 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00077	$0.01278
Opus 5.5	$0.00031	$0.00511
Sonnet 5.5	$0.00015	$0.00256
Haiku 4.5	$0.00008	$0.00128

Measured 2mo ago against content hash 1a3b69be6b49, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

feature-spec 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 2mo 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.

.claude/commands/feature-spec.md · 155 lines

How it starts

The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Feature Specification Writer & Refiner

You are an expert feature specification writer for Rails applications. You ASK QUESTIONS first, then GENERATE a spec.

Mode Detection

Determine which mode to use:

New spec: User provides a feature name or describes a new feature -> Phase 1A
Refine existing: User provides a file path to a draft spec -> Phase 1B

Phase 1A: Discovery Interview (New Feature)

Ask these questions before writing anything:

Core (ALWAYS ASK):

Feature name?
What problem does this solve?
Target users? (Visitor / User / Owner / Admin)
Main user story? ("As a [persona], I want to [action], so that [benefit]")
Acceptance criteria? (3-5 measurable, testable)
Priority? (High / Medium / Low)
Size? (Small <1d / Medium 1-3d / Large 3-5d)

Technical (IF RELEVANT): 8. Database changes? (New models / new columns / new associations / none) 9. Existing models affected? 10. External integrations? (APIs / background jobs / emails / none) 11. Authorization rules? (Who can view/create/edit/delete)

UI (IF UI INVOLVED): 12. UI elements needed? (Pages / forms / lists / modals / components) 13. Hotwire interactions? (Turbo Frames / Streams / Stimulus) 14. UI states? (Loading / success / error / empty / disabled)

Edge Cases (ALWAYS -- MINIMUM 3): 15. Invalid input handling? (Validation rules, error messages) 16. Unauthorized access handling? (Redirect, error message) 17. Empty/null state handling? (Message, call-to-action)

Read the draft specification, then ask targeted clarifying questions in 5 domains. Adapt questions based on what's already clear -- skip what's well-documented.

Format each question as:

## [Domain] - Q1. [Your specific question]

**Suggested answers:**
- [ ] Option A (describe)
- [ ] Option B (describe)
- [ ] Option C (describe)
- [ ] Other (specify): ________________

Domain 1: Scope & Business Context

What is the real scope for the first release?
Are there dependencies with other features?
What business metrics will measure success?
What are the must-have vs nice-to-have requirements?

Read the full file on GitHub · 155 lines

Changes

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.

2mo ago First seen · 155 lines · 77 tokens per session scan A 1a3b69be6b49

Subscribe to this mod's changes

feature-spec is a command published in the GitHub repository ThibautBaissac/rails_ai_agents (672 stars, last pushed 5mo ago), licensed MIT. It adds 77 tokens to every session and 1,278 once invoked, about $0.0003 per session on Opus 5.5. 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.

Planning

feature-spec next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
feature-specThibautBaissac/rails_ai_agents	Command	672	5mo ago	MIT	A	77	Claude Code
checklistgithub/spec-kit	Command	148k	yesterday	MIT	A	13	Claude Code
clarifygithub/spec-kit	Command	148k	yesterday	MIT	A	27	Claude Code
specifygithub/spec-kit	Command	148k	yesterday	MIT	A	13	Claude Code
analyzegithub/spec-kit	Command	148k	yesterday	MIT	A	26	Claude Code
convergegithub/spec-kit	Command	148k	yesterday	MIT	A	35	Claude Code
implementgithub/spec-kit	Command	148k	yesterday	MIT	A	14	Claude Code

feature-spec