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/spec-review)<a href="https://agentmods.dev/commands/thibautbaissac/rails_ai_agents/spec-review"><img src="https://agentmods.dev/badge/commands/thibautbaissac/rails_ai_agents/spec-review/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/spec-review"><img src="https://agentmods.dev/badge/commands/thibautbaissac/rails_ai_agents/spec-review.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 | $0.00028 | $0.02471 |
| Opus 5 | $0.00014 | $0.01236 |
| Sonnet 5 | $0.00006 | $0.00494 |
| Haiku 4.5 | $0.00003 | $0.00247 |
Grade A, and why
spec-review 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 11d 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 — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Input
$ARGUMENTS
You MUST consider the user input before proceeding (if not empty).
Goal
Act as a devil's advocate — challenge the current feature specification from multiple adversarial perspectives to find gaps, risks, and blind spots that the spec author may have missed. This is a read-only analysis that produces a structured critique. No files are modified.
This command is designed to run AFTER /sdd:specify (and optionally after /sdd:clarify) but BEFORE /sdd:plan. It adds the most value when the spec is considered "ready" but has not yet been translated into architecture.
Operating Constraints
STRICTLY READ-ONLY: Do not modify any files. Output a structured review report. The user decides which findings to address (via /sdd:clarify, /sdd:specify, or manual edits).
Adversarial Mindset: Your job is to find problems, not to praise. A spec with zero findings is suspicious — push harder. However, do not fabricate issues. Every finding must cite a specific spec section or absence.
Constitution Authority: If .specify/memory/constitution.md exists, all findings must be evaluated against its principles. Constitution violations are automatically CRITICAL.
Execution Steps
1. Initialize Review Context
Run .specify/scripts/bash/check-prerequisites.sh --json --paths-only from repo root once. Parse JSON for:
FEATURE_DIRFEATURE_SPEC
If FEATURE_SPEC does not exist, abort and instruct user to run /sdd:specify first.
For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'''m Groot' (or double-quote if possible: "I'm Groot").
2. Load Review Context
- REQUIRED: Read the feature spec at FEATURE_SPEC
- IF EXISTS: Read
.specify/memory/constitution.mdfor principle validation - IF EXISTS: Read
.specify/memory/lessons-learned.md— filter to entries tagged[phase:specify]or[phase:all]for known specification pitfalls from past features
3. Adversarial Analysis Passes
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.
- 11d ago First seen · 223 lines · 28 tokens per session scan A c89b4795bb1b
spec-review is a command published in the GitHub repository ThibautBaissac/rails_ai_agents (661 stars, last pushed 3mo ago), licensed MIT. It adds 28 tokens to every session and 2,471 once invoked, about $0.0001 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
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.