speckit.plan

A command that creates a detailed implementation plan from a feature specification. It uses templates to record research, design decisions, data structures, interfaces, and setup instructions before coding begins.

In plain words
What is it for?
Use it to plan a feature in a repository that follows the Specify workflow, including research, data models, API contracts, quick-start notes, and agent context updates.
Why use it?
It turns an idea into a documented plan and highlights unanswered questions or rule violations early. This helps the team agree on the design before implementation work starts.

Command for Cursor

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 commands/visactor/vchart/speckit.plan
Clone the repo
git clone --depth 1 https://github.com/VisActor/VChart

Made for: Cursor.

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 736 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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.

ModelPer sessionOnce invoked
Fable 5 $0.00014 $0.00736
Opus 5 $0.00007 $0.00368
Sonnet 5 $0.00003 $0.00147
Haiku 4.5 $0.00001 $0.00074

Measured yesterday against content hash f38916c5d609, 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

Copies of this mod

8 near-identical copies found in the catalogue:

.cursor/commands/speckit.plan.md · 90 lines

How it starts

The opening of the file, as written. The whole thing — 90 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 · 90 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 · 90 lines · 14 tokens per session scan A f38916c5d609

Subscribe to this mod's changes

speckit.plan is a command published in the GitHub repository VisActor/VChart (1,834 stars, last pushed 7d ago), licensed MIT. It adds 14 tokens to every session and 736 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.