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/9j/rapidspec/proposalgit clone --depth 1 https://github.com/9j/RapidSpecWhat 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 | $0.00013 | $0.03279 |
| Opus 5 | $0.00006 | $0.01639 |
| Sonnet 5 | $0.00003 | $0.00656 |
| Haiku 4.5 | $0.00001 | $0.00328 |
Grade A, and why
RapidSpec: Proposal scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 464 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create RapidSpec Proposal
Transform feature descriptions, bug reports, or improvements into well-structured RapidSpec proposals with automated verification and research.
Feature Description
<feature_description> #$ARGUMENTS </feature_description>
Main Tasks
1. Parallel Verification & Research
<critical_requirement> MUST verify actual code exists before proposing. No "imaginary code". All file references must be verified with Read, Grep, or Git commands. </critical_requirement>
Run these agents in parallel at the same time:
Repository analysis:
- Task repo-research-analyst(feature_description)
Investigation agents:
- Task git-history-analyzer(affected_files)
- Task pattern-recognition-specialist(affected_files)
Research agents:
- Task best-practices-researcher(feature_description, technology_stack)
- Task framework-docs-researcher(detected_framework)
Verification Checklist:
- Read actual files with
@file/path,Grep,Glob - Check git history:
git log --oneline -- path/to/file - Find existing patterns in codebase
- Document all findings with specific file paths (e.g.,
src/app/page.tsx:42)
Research Collection:
- WebSearch for latest patterns (e.g., "Next.js 16 caching patterns 2025")
- Check reference repositories (midday-ai, dub, epic-stack)
- Read library CHANGELOG.md for breaking changes
- Analyze git log for past decisions:
git log --all --grep="keyword" - Include URLs to external documentation and best practices guides
2. Synthesize Research & Present Options
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.
- yesterday First seen · 464 lines · 0 tokens per session scan A 627d2436e7e8
RapidSpec: Proposal is a command published in the GitHub repository 9j/RapidSpec (5 stars, last pushed 9mo ago), licensed MIT. It adds 13 tokens to every session and 3,279 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 2026-08-31.
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.