Magnus Hedemarkandfactory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
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Move the 8 directories under bundles/ to the repo root via git mv and remove the now-empty bundles/ directory. Replace the "bundles" entry in pyproject.toml [tool.deptry] extend_exclude with the 8 moved dir names so the moved trees stay excluded from Python dependency analysis. Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
4.8 KiB
product-lifecycle
Route a product through its full lifecycle — from discovery to post-launch learning — by composing existing specialist product skills with phase-entry evidence, handoff artifacts, and escalation rules.
Why Install This Skill
Product work is naturally multi-phase: you discover a problem, validate a strategy, design a solution, run experiments, hand off to delivery, drive adoption, measure success, and decide whether to continue or retire. But the specialist skills that support each phase — product-discovery, product-strategy, product-experimentation, product-adoption, and others — don't connect to each other. An agent that loads product-discovery has no built-in knowledge of what comes next or what evidence to hand off.
The product-lifecycle bundle fills this gap. It's a thin orchestration layer that sits above the specialist skills and provides three things:
- A phase routing table that tells the agent which skill to load at each point in the lifecycle.
- Phase-entry evidence and handoff contracts so the agent knows what to expect at each transition and what to produce for the next phase.
- Stop and escalation rules at every phase so the agent knows when to halt — and the lifecycle ledger preserves what was learned even when work stops.
The bundle is thin by design. It never duplicates a specialist's methodology. If you only need one phase, load that specialist skill directly. If you need to navigate a product across multiple phases with evidence handoffs between them, load this bundle.
What You Get
| Path | What it provides |
|---|---|
SKILL.md |
Thin umbrella with a 9-phase routing table, loading protocol, and "When not to use" boundary |
README.md |
This file — human-facing overview |
AGENTS.md |
Agent-facing loading and operational instructions |
references/phases.md |
Detailed per-phase contracts: entry evidence, output artifacts, escalation behavior, completion criteria, and lifecycle evidence ledger spec |
references/discovery-brief.md |
Bounded discovery brief comparing with existing bundles (neckbeard, workflow-architect, tailscale, research-and-vault) and stating the bundle boundary |
references/capability-map.md |
Capability area → owning skill lookup table for quick reference without traversing the full lifecycle |
evals/evals.json |
Schema-v1 output-quality evaluation cases covering a complete lifecycle, ambiguous requests, failed experiments, non-adoption, and justified retirement |
manifest.yaml |
Machine-readable bundle manifest (schema v1): purpose, audience, stages, included skills, prerequisites, outputs, handoffs, conflicts, and eval suite |
Quick Start
Load the umbrella when you need to route a product across multiple lifecycle phases:
- Start with the phase routing table in
SKILL.mdto locate your current phase. - Load
references/phases.mdfor the detailed phase contract. - Load the specialist skill(s) named in the phase row and follow their method.
- Write phase outputs to the lifecycle evidence ledger.
- The next phase reads the ledger and continues.
For single-phase work, load the specialist skill directly — e.g.,
product-discovery for stakeholder interviews, product-experimentation for
experiment design, or product-adoption for adoption planning.
Triggers
- Evaluating a new product idea end-to-end.
- Managing a product through its lifecycle phases.
- Connecting product phases that currently operate in isolation.
- Needing phase-entry evidence and handoff contracts between product skills.
- Deciding whether to continue, pivot, or retire a product.
- A stakeholder request that needs to be routed through discovery, strategy, and validation before delivery.
- A product that has launched and needs adoption measurement, success evaluation, and lifecycle review.
Do not trigger for:
- A single product task owned by a specialist skill — load that skill directly.
- Software delivery lifecycle work — route to
neckbeard. - Standalone strategic analysis, financial modeling, or GTM planning without a lifecycle context.
Requirements
- No API keys, services, or network dependencies.
- No environment variables required.
- Compatible with any agent harness that supports the Agent Skills format.
- The specialist skills this bundle routes to must be installed. The bundle
assumes the following catalog skills are available:
product-discovery,product-strategy,product-roadmapping-and-portfolio,product-design-and-ux,product-experimentation,product-analytics-and-measurement,product-adoption,conditional-customer-success,product-operations-and-governance,product-lifecycle-learning,implementation-planning,spec-driven-development,production-readiness,release-engineering,product-methodology,go-to-market,financial-modeling,data-scientist.