speckit.plan

speckit.plan is an agent for coding agents from racecraft-lab/Paddock. It costs 14 tokens per session (787 once invoked), scanned A, a copy of speckit.plan, MIT.

An implementation-planning workflow that turns a feature specification into design and planning files for a software project.

In plain words
What is it for?
Use it to create research notes, data models, API contracts, quickstart instructions, and an implementation plan from a feature request.
Why use it?
It provides a structured way to resolve unknowns, check project rules, and document how a feature should be built before implementation starts.

Agent

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.

agentmods
npx agentmods add agents/racecraft-lab/paddock/speckit.plan
Clone the repo
git clone --depth 1 https://github.com/racecraft-lab/Paddock

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.

agentmods badge for speckit.plan

README.md
[![agentmods](https://agentmods.dev/badge/agents/racecraft-lab/paddock/speckit.plan.svg)](https://agentmods.dev/agents/racecraft-lab/paddock/speckit.plan)
Your own site
<a href="https://agentmods.dev/agents/racecraft-lab/paddock/speckit.plan"><img src="https://agentmods.dev/badge/agents/racecraft-lab/paddock/speckit.plan.svg" alt="Measured on agentmods" height="20"></a>
Per session 14 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 787 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 91% copy Near-identical to another mod 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.

ModelPer sessionOnce invoked
Fable 5 $0.00014 $0.00787
Opus 5 $0.00007 $0.00394
Sonnet 5 $0.00003 $0.00157
Haiku 4.5 $0.00001 $0.00079

Measured yesterday against content hash fc082bd2a57e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

speckit.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 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.

Origin

This is a copy

91% identical to speckit.plan — 9 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.specify/extensions/verify-tasks/.github/agents/speckit.plan.agent.md · 91 lines

How it starts

The opening of the file, as written. The whole thing — 91 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).

Outline

  1. Setup: Run .specify/scripts/bash/setup-plan.sh --json from repo root and parse JSON for FEATURE_SPEC, IMPL_PLAN, SPECS_DIR, BRANCH. 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 context: Read FEATURE_SPEC and .specify/memory/constitution.md. Load IMPL_PLAN template (already copied).

  3. Execute plan workflow: Follow the structure in IMPL_PLAN template to:

    • Fill Technical Context (mark unknowns as "NEEDS CLARIFICATION")
    • Fill Constitution Check section from constitution
    • Evaluate gates (ERROR if violations unjustified)
    • Phase 0: Generate research.md (resolve all NEEDS CLARIFICATION)
    • Phase 1: Generate data-model.md, contracts/, quickstart.md
    • Phase 1: Update agent context by running the agent script
    • Re-evaluate Constitution Check post-design
  4. Stop and report: Command ends after Phase 2 planning. Report branch, IMPL_PLAN path, and generated artifacts.

Phases

Phase 0: Outline & Research

  1. Extract unknowns from Technical Context above:

    • For each NEEDS CLARIFICATION → research task
    • For each dependency → best practices task
    • For each integration → patterns task
  2. Generate and dispatch research agents:

    For each unknown in Technical Context:
      Task: "Research {unknown} for {feature context}"
    For each technology choice:
      Task: "Find best practices for {tech} in {domain}"
    
  3. Consolidate findings in research.md using format:

    • Decision: [what was chosen]
    • Rationale: [why chosen]
    • Alternatives considered: [what else evaluated]

Output: research.md with all NEEDS CLARIFICATION resolved

Phase 1: Design & Contracts

Prerequisites: research.md complete

  1. Extract entities from feature specdata-model.md:
    • Entity name, fields, relationships
    • Validation rules from requirements
    • State transitions if applicable

Read the full file on GitHub · 91 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.

  1. yesterday First seen · 91 lines · 14 tokens per session scan A fc082bd2a57e

Subscribe to this mod's changes

speckit.plan is an agent published in the GitHub repository racecraft-lab/Paddock (11 stars, last pushed 2mo ago), licensed MIT. It adds 14 tokens to every session and 787 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to speckit.plan, differing in 9 lines, and is treated as a copy.

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