plan

A command that creates a detailed implementation plan for a requested feature without changing the code.

In plain words
What is it for?
Use it to plan features such as new endpoints, authentication options, or IP-based rate limiting, then approve the proposed plan.
Why use it?
It checks for existing work, finds reusable code, identifies affected files, and highlights risks before implementation begins.

Command

Part of the fp plugin — 19 skills, 19 commands, 4 agents, 1 hook shipped together

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/vynazevedo/first-plan/plan
Clone the repo
git clone --depth 1 https://github.com/vynazevedo/first-plan

Or install fp, the plugin that ships this one along with the rest of its 19 skills, 19 commands, 4 agents, 1 hook.

Per session 47 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,694 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 $0.00047 $0.01694
Opus 5 $0.00023 $0.00847
Sonnet 5 $0.00009 $0.00339
Haiku 4.5 $0.00005 $0.00169

Measured 3d ago against content hash 00756e694d68, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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 3d 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.

commands/plan.md · 190 lines

How it starts

The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/fp:plan

Gera plano da Fase 2 - sempre pausa pedindo aprovação humana.

Argumentos

$ARGUMENTS - descrição da feature solicitada em texto livre. Exemplos:

  • "adicionar endpoint de export CSV para /orders"
  • "implementar autenticação por API key além do JWT existente"
  • "adicionar rate limiting por IP no gateway"

Workflow

Passo 1 - Pre-flight

  1. Verificar .first-plan/ existe e STATE.md indica fase >= discovered
  2. Verificar se já há plano ativo (07-state/STATE.md em awaiting_approval ou executing):
    • Se sim, perguntar: "Plano está . Substituir? (sim/não)"
    • Não prosseguir sem confirmação
  3. Verificar staleness: se muitos arquivos stale, recomendar /fp:refresh antes

Passo 2 - Verificação de duplicidade

Aplicar skill reconciliation:

  1. Spawnar reconciliation-auditor com feature_query=<argumento>:
Task(
  subagent_type="reconciliation-auditor",
  description="Duplicate check for plan request",
  prompt="Audit feature: '<arg>'. Apply classification. Return status + evidence + recommendation."
)
  1. Se status = IMPLEMENTED:

    • PARAR - perguntar ao usuário:
      Esta feature parece já implementada (<evidência>).
      
      Opções:
      A) Cancelar plano (a feature já existe)
      B) Modificar a feature existente em vez de criar nova
      C) Seguir com plano mesmo assim (pode estar errado a matriz)
      
      Qual? [A/B/C]
      
    • Não prosseguir sem decisão.
  2. Se status = IN_PROGRESS:

    • Avisar: "Há trabalho em flight em /. Sugiro continuar nesse contexto em vez de plano novo."
    • Perguntar se quer prosseguir mesmo assim.
  3. Se status = DRIFTED:

    • Perguntar: "A feature solicitada é justamente reconciliar o drift detectado em ?"
  4. Se status = SPEC_ONLY ou NOT_STARTED ou nova: Prosseguir.

Passo 3 - Coleta de contexto relevante

Ler trechos relevantes da camada compilada:

  • 01-topology/architecture.md - onde a feature se encaixa
  • 01-topology/boundaries.md - se feature toca contratos
  • 02-conventions/* - todas as convenções aplicáveis
  • 03-reuse/INDEX.md - candidatos a reuse
  • 04-domain/* - entidades e flows relevantes
  • 05-risks/* - riscos em paths que provavelmente serão tocados
  • 06-rationale/* - decisões a respeitar
  • 07-state/in-flight.md - PRs/branches que podem conflitar
  • 08-meta/questions.md - perguntas abertas relevantes

Read the full file on GitHub · 190 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. 3d ago First seen · 190 lines · 47 tokens per session scan A 00756e694d68

Subscribe to this mod's changes

plan is a command published in the GitHub repository vynazevedo/first-plan (23 stars, last pushed 8d ago), licensed MIT. It adds 47 tokens to every session and 1,694 once invoked, about $0.0002 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.