Product2Prod --> Product Perspective to Production

Product management for AI agents, from idea to post-production:

• Product ownership, from one idea - /pm-start opens every run: a plain-words interview locks company, domain and output, then routes to the right verb. No prompt-crafting.
• Strategy - the requirements cycle's research and strategy phases build an evidence ledger before anything is written; the portfolio verb adds an independent strategy lens to every score.
• PRDs, specs and use cases - /pm-requirements-v1 emits the spec-kit: spec, plan, data model, contracts and acceptance scenarios (what lands on disk).
• Prioritization and roadmap - /pm-portfolio-v1 turns a backlog into evidence-labelled RICE scores, P0-P3 bands and a sprint or quarter recommendation.
• Go-to-market - /pm-gtm-v1 builds the phase-gated launch plan, per channel and per persona, config-only by design.
• Technical PM and engineering handoff - the sealed handoff package: slices, contracts and a design gate whose approval flag no code path in this plugin writes true.
• Acceptance, analytics and post-production results - /pm-verify-release-v1 grades the pre-declared scenarios against the deployed build and executes the measurement plan, read-only.

Every claim in what it writes is either sourced or labelled unsourced, and no gate is passed by the agent that wants to pass it.

one paragraph of intent → a plain-words interview → a locked context → gated phases → a package on disk that names its sources and its gaps

The agent drafts, then stops. Ruling the open questions stays yours, and the record shows what was known when you ruled. It runs inside an agent you already have, and nothing it writes leaves your machine.

Three plays win most product reviews, and all three are cheating:

• A number arrives sounding certain, and nobody can say where it came from.
• A gate gets passed by the same agent that wanted it open.
• A handoff cannot show what was known, and what was still open, on the day it shipped.

They lose at this table. Every factual claim carries one of six evidence tags, a linter checks that discipline mechanically, and the approval flag ships false with no code path in this plugin that writes it true. What it checks is the discipline, not the truth: a claim can still be wrong, but not quietly wrong. A FOUND must name a place to check; the second command below catches one that does not.

Get it. In Claude, two commands, nothing cloned:

/plugin marketplace add naderelewa/Product-to-Prod
/plugin install product2prod

Or prove it before you read it. No credentials:

git clone https://github.com/naderelewa/Product-to-Prod.git && cd Product-to-Prod
bash tests/run-tests.sh                                                  # the suite behind the badge: 89 checks
bash scripts/tag-lint.sh tests/fixtures/tag-lint/bad-found-no-anchor.md  # watch it catch a FOUND with no locator
scripts/telemetry.sh status                                              # confirms the usage log is off and no file exists

One run, start to finish

One small ask, end to end. Bigger asks are the same shape with more phases.

You type

/pm-start "should [Put Your Company Name] charge sellers a listing fee or a take rate?"

It locks the context and stops until you confirm or correct this block:

company / pack   : <name> (pack: <id> | none = generic mode)
area             : <area>
output           : <deliverable>
destination      : standalone | handoff to <engineering toolchain>
out of bounds    : <anything you said not to touch>

What lands. No files for an ask this small; bigger asks land the package. The routed verb opens one section of the framework library (skills/gtm-domain-library/references/pricing-value-metric.md) and answers with the value-metric tree plus the rows only your instrumentation can fill. The library never supplies your numbers.

Reconstructed excerpt. The flows are battle-tested on real production companies, and those runs stay private, so the excerpt below is rebuilt with placeholders. One engagement built this way is public end to end: Netflix Engagement Intelligence, four phases on public data, 497 evidence tags, every decision gate locked.

Value metric candidates, ranked
1. per completed order      [INFERRED: scales with the value the seller receives]
2. per active listing       [CONSTRUCTED: easier to bill, weaker link to value]
Your take-rate elasticity   [NEEDS-CONFIRMATION → pricing owner: blocks the free-line decision]
Market benchmark            [HYPOTHESIS: no durable market source found]

The gap rows are the feature. Visibly empty beats quietly invented: a reader who sees the gap can close it, one given a confident wrong number cannot. The same run at four sizes across five industries: Example scenarios by industry.

Install

Prerequisite: python3 on your path, and shasum (or sha256sum) for the requirements seal. Most scripts embed a python program (preflight, hostcheck, tag-lint, inference-gate, telemetry), as does the test suite; publish-lint and release are pure shell. Runs in Claude Code and any harness reading the Agent Skills spec, whose protocol is AGENTS.md.

Four rungs, in rising depth.

1. Zero setup: one file, one paste, nothing configured. For a first look. Open any verb's SKILL.md, paste it into your agent, and say "apply this to my product". Every verb runs with nothing configured, consented or connected.

2. Skills folder. Copy the skills/ subfolders into your agent's skills directory; your harness picks them up by name and description.

3. Claude Code (plugin). For day-to-day use with the full surface.

git clone https://github.com/naderelewa/Product-to-Prod.git
claude --plugin-dir Product-to-Prod

Then run init once only if you want one of the two things it governs: the usage log, or a read-only issue-tracker connection. Want neither and there is nothing to set up, which the wizard says in those words; its gates are in Wizard features. Some harnesses namespace skills, so use what your harness lists rather than the bare /pm-start here.

4. Marketplace. The two commands at the top of this page.

Every host-specific key ships null in config/local.template.json, explained in Connections and configuration.

Run it outside Claude Code

The method is markdown plus small scripts, so it travels, and each tier names what you lose.

Full, with gates: claude.ai, Claude Desktop and Cowork, on any paid plan. In Plugins settings, sync this repository's URL as a marketplace and install product2prod. The skills then run in chat where code execution is on, and everything runs in Cowork. Skip the per-skill Skills upload: that door takes one skill folder per zip, and these verbs share scripts/, references/ and config/, which it would strand.

The release ZIP, for the surfaces that execute code and take the plugin whole. Claude Code loads it directly: claude --plugin-dir product2prod-v0.1.3-full.zip; the flag accepts a zip of the plugin directory. Cowork accepts the same file as a custom plugin upload, kept under the .zip name. It is one zip on purpose, the shared folders above inside it.

Degraded, read only: chats with no code execution. Paste any verb's SKILL.md and work the method by hand. The discipline still reads; the enforcement does not run: no tag lint, no inference gate, none of the 89 checks. Treat every claim as untested until the suite runs somewhere with a shell.

One ZIP, one sha256, one manifest, published with this release.

Which verb, when