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.
npx agentmods add commands/thibautbaissac/rails_ai_agents/validategit 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/validate)<a href="https://agentmods.dev/commands/thibautbaissac/rails_ai_agents/validate"><img src="https://agentmods.dev/badge/commands/thibautbaissac/rails_ai_agents/validate.svg" alt="Measured on agentmods" 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 | $0.00024 | $0.02211 |
| Opus 5 | $0.00012 | $0.01105 |
| Sonnet 5 | $0.00005 | $0.00442 |
| Haiku 4.5 | $0.00002 | $0.00221 |
Grade A, and why
validate 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 5d 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 — 214 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
Verify that the codebase implements what the feature specification promises. This command runs AFTER /sdd:implement to detect spec drift — requirements that are unimplemented, broken, or diverged from the spec.
Uses a 4-layer hybrid approach :
- Structural scan — Rails convention-based file existence checks
- Test coverage mapping — RSpec description and metadata matching
- AI semantic analysis — LLM-powered code search for uncovered requirements
- Acceptance test generation — On-demand, user-approved
Operating Constraints
READ-ONLY for source code: Do not modify implementation files. The only files this command may write are the validation report (in FEATURE_DIR) and optionally the spec header (to record validation status).
Constitution Authority: If .specify/memory/constitution.md exists, check whether any constitution principles are violated by the implementation.
Execution Steps
1. Initialize Validation Context
Run .specify/scripts/bash/check-prerequisites.sh --json --paths-only from repo root once. Parse JSON for:
FEATURE_DIRFEATURE_SPECTASKS
If FEATURE_SPEC does not exist, abort: "Run /sdd:specify first."
For single quotes in args, use escape syntax: e.g 'I'''m Groot' (or double-quote if possible).
2. Load Spec and Extract Requirements
Read FEATURE_SPEC and extract:
- Functional Requirements: All FR-### identifiers with their full text
- Success Criteria: All SC-### identifiers with their full text
- Acceptance Criteria: All Given/When/Then scenarios from user stories
- Key Entities: Entity names mentioned in the spec
Build an internal requirements inventory — a list of requirement IDs, their text, and the entity/domain they relate to.
Also load:
- IF EXISTS:
.specify/memory/constitution.mdfor principle validation - IF EXISTS:
.specify/memory/lessons-learned.md— filter to[phase:implement]or[phase:all] - IF EXISTS: FEATURE_DIR/tasks.md — to cross-reference completed tasks with requirements
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.
- 5d ago First seen · 214 lines · 24 tokens per session scan A 2ccd63787741
validate is a command published in the GitHub repository ThibautBaissac/rails_ai_agents (659 stars, last pushed 3mo ago), licensed MIT. It adds 24 tokens to every session and 2,211 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.