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Product plan

Skill RubenGlez/harness/skills/product-plan

Define the full product vision — audience, positioning, features, roadmap, and UX direction — through a structured interview. Use after ideate, or directly when the idea is already validated and you're ready to spec the product.From its SKILL.md

Install
npx -y skills add RubenGlez/harness --skill product-plan

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
  • runs commandsInstructs the agent to run 3 commands, including `gh issue list` and 2 more.

SKILL.md

4.3 KB, 968 tokens by cl100k_base, as published. Nobody here has run it

Product Plan

Step 1: Read the project

Before asking anything, gather all available context:

Ideation output — read .harness/product/idea.md if it exists:

  • Extract: concept, problem, market landscape, competitor list, viability verdict
  • These questions are already answered — do not re-ask them in the interview

Existing product docs — read .harness/product/ for prior decisions to update rather than re-litigate

Codebase — if code already exists:

  • Read README.md for stated goals and audience
  • Scan the feature surface: routes, screens, commands, or API endpoints
  • Check the roadmap or issue tracker if present (gh issue list)
  • Note what's implemented, what's stubbed, and what's conspicuously absent

Starting mid-flow on an existing project: if code exists but .harness/ is absent, treat this as step 2 — /ideate was skipped. Read the codebase and README to reconstruct what idea.md would have said, then proceed.

Synthesize into a one-paragraph internal picture. Do not share this — use it to skip already-answered questions and form sharper hypotheses.

Step 2: Interview

Interview the user relentlessly — one question at a time. For every question, state a concrete recommendation or hypothesis first. Never ask a bare question. Lead with your position — "My read is X. Do you agree?" — so the user reacts to a specific claim.

Be a realist, not a cheerleader. Surface the truth, not validation: name failure modes, push back on optimistic answers, make vague audiences concrete, call out weak moats.

Work through these dimensions in order; skip any already answered. See REFERENCE.md for detailed questions per dimension:

  1. The idea
  2. Target audience
  3. Market and competition (skip if idea.md covers it)
  4. Value and differentiation
  5. Validation
  6. Features
  7. UX and design

Step 3: Report

After the interview, produce a report with these sections:

  • Audience — who it's for, who the early adopter is, why they care
  • Value Proposition — for whom, the key benefit, the core differentiator, why users switch (synthesize from dimensions 4 and 5)
  • Market Positioning — category, differentiation, competitive gap
  • Competitive Analysis — top 3–5 competitors, strengths, weaknesses
  • Direction Assessment — go / conditional go / no-go with 2–3 reasons
  • Prioritized Feature Backlog — must-have / should-have / nice-to-have
  • UX and Design Direction — core workflow, interaction model, design register
  • Key Risks — 2–3 assumptions most likely to be wrong and how to test them

Step 4: Write docs

Doctier bootstrap (once per repo)

.harness/ is tracked in git as age-encrypted blobs via doctier. If .doctier.yml exists at the repo root, skip this — the repo is already set up. If .harness/ already exists but is gitignored (a pre-doctier project), follow the adoption recipe in the migrate-docs skill's REFERENCE.md instead. Otherwise, run the bootstrap in ../_shared/doctier-bootstrap.md.

Spawn the doc writer

Spawn a subagent to write all product docs. Pass the full report as context — it cannot read the conversation.

Runtime note: if your runtime can't spawn a subagent (e.g. Codex), write the docs yourself in this session — see ../_shared/runtime-parallelism.md.

Rules: all files go under .harness/product/; update existing rather than overwrite; omit sections with no source; never link to .harness/ from public docs.

The subagent writes: product.md, roadmap.md, competitors.md, ux.md (if UI discussed), and CONTEXT.md (domain glossary). See REFERENCE.md for templates.

After the subagent finishes, confirm every file written. Refresh the doc index and commit — worktrees and future sessions only see committed .harness/ content:

doctier agents --write
git add .harness AGENTS.md && git commit -m "docs: product plan"

Recommend: "Run /dev-plan to define the architecture and generate feature specs."

What ships with it: 1 file

3.9 KB alongside SKILL.md

Gives 1 of the 12 instructions most plan spec skills give in 968 tokens

Counted across 1,360 of the 2,617 authors here whose files we hold, read 2026-09-06

  • Ask one question at a timehere, and in 73 of 1360
  • Write the spec using the templatein 22 of 1360
  • Ask clarifying questions if neededin 19 of 1360, across 18 files
  • Wait for user confirmation before proceedingin 19 of 1360
  • Save plans to the plans directoryin 17 of 1360, across 13 files
  • Check for product marketing context firstin 16 of 1360, across 5 files
  • Read the plan file completelyin 16 of 1360
  • Order tasks by dependencyin 16 of 1360
  • Gather context from the conversationin 15 of 1360, across 9 files
  • Explore the codebase instead of askingin 15 of 1360, across 13 files
  • Wait for explicit user approvalin 14 of 1360, across 13 files
  • Quiz the user on the breakdownin 13 of 1360, across 7 files

Said here and by no other author read

  • Gather available context before asking anything
  • State a concrete recommendation or hypothesis first
  • Name failure modes and push back on optimistic answers
  • Produce a report after the interview
  • Update existing files rather than overwrite
  • Commit the generated product docs

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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