plan

A planning command that turns a team objective into questions, assumptions, hypotheses, experiments, stakeholders, and decisions.

In plain words
What is it for?
Use it to plan product work by loading relevant strategy, metrics, user evidence, prior decisions, and risks, then drafting the needed planning records.
Why use it?
It gives an unclear objective a concrete path toward an execution decision.

Command for Claude Code

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/phuryn/pm-brain/plan
Clone the repo
git clone --depth 1 https://github.com/phuryn/pm-brain

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 499 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 $0.00000 $0.00499
Opus 5 $0.00000 $0.00249
Sonnet 5 $0.00000 $0.00100
Haiku 4.5 $0.00000 $0.00050

Measured 2d ago against content hash 9a2bc45a9503, 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 2d 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.

.claude/skills/pm-brain/scaffold/.claude/commands/plan.md · 45 lines

How it starts

The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/plan

Turn a new team objective into a concrete plan: what we know, what we assume, who to interview, which hypotheses to open, which experiments to run, what decision would unlock execution.

Input

An objective statement. Example: /plan reduce onboarding drop-off by 20% in Q3.

Loads

  • knowledge/strategy.md (priorities, non-goals, north-star, tensions)
  • knowledge/product/metrics.md (current values, definitions)
  • knowledge/product/features/ filtered to ones touching the objective
  • knowledge/users/insights.md, relevant personas.md / segments.md
  • All active hypotheses/ in the area
  • decisions/ filtered to relevant prior commitments
  • stakeholders/ filtered to people who'd influence or block the plan
  • rules/discovery.md, rules/prioritization.md, rules/data.md

Updates

  • A draft ingestion/adhoc/<date>-plan-<slug>.md capturing the planning session
  • hypotheses/<slug>.md — drafts for any value/usability/feasibility/viability/other risk that needs testing (status: candidate)
  • decisions/<date>-<slug>.md — drafts for go/no-go points (status: pending)
  • stakeholders/<slug>.md § Open asks — drafts for the alignment conversations the plan implies

Nothing committed without operator confirmation per autonomy mode.

Surfaces

Six blocks, in this order:

  1. What we already know — citations to insights, hypotheses, decisions, metrics
  2. Assumption vs evidence — explicitly tagged, with provenance for each
  3. Who to interview — segments, personas, specific named users; recent coverage gaps
  4. Hypotheses to open — across the 5 risk areas, with the test for each
  5. Experiments to run — sequenced, with success criteria and what would invalidate
  6. Decision points — the go/no-go moments and what evidence would unlock each

Plus:

  • Constraints from strategy.md § Non-goals that bound the plan
  • Stakeholder alignment conversations the plan requires (linked to /prep)
  • One paragraph on what would make the plan unwise (so the operator can falsify it early)

Read the full file on GitHub · 45 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. 2d ago First seen · 45 lines · 0 tokens per session scan A 9a2bc45a9503

Subscribe to this mod's changes

plan is a command published in the GitHub repository phuryn/pm-brain (537 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 499 tokens. 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.