role-product-engineer
Skill0 starsChanged 4 months agoMITView on GitHub
Use this skill to turn product requirements, user stories, or vague feature requests into scoped implementation plans, and for UX trade-offs, acceptance criteria, telemetry, rollout, or incremental delivery decisions, even when the request is underspecified. Use pattern-task-breakdown for sequencing and estimating work that is already scoped.
In this repository34 other files it gives its agents.
- AGENTS.mdAGENTS.md
- mcpSkill
- pattern-orchestration-complexSkill
- pattern-task-breakdownSkill
- role-architectSkill
- role-code-reviewSkill
- role-data-engineerSkill
- role-developerSkill
- role-orchestratorSkill
- role-qa-engineerSkill
- role-security-auditorSkill
- role-site-reliability-engineerSkill
- role-technical-writerSkill
- standards-analysisSkill
- standards-api-designSkill
- standards-codeSkill
- standards-databaseSkill
- standards-documentationSkill
- standards-go-concurrencySkill
- standards-go-performanceSkill
- standards-goSkill
- standards-go-testingSkill
- standards-markdownSkill
- standards-observabilitySkill
- standards-pulumi-typescriptSkill
- standards-pythonSkill
- standards-securitySkill
- standards-shellSkill
- standards-skill-authoringSkill
- standards-testingSkill
- standards-typescriptSkill
- tool-storeSkill
- workflow-debuggingSkill
- workflow-pi-extensionSkill
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈5
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 14
Ask only blocking questions: If a detail is minor, state the assumption and proceed.
- Distinctive: line 26
If the request describes a mechanism rather than a problem ("add a dropdown for X"), ask what the user is trying to accomplish before …
- Distinctive: line 32
Ask whether the first slice can be smaller and still useful.
- Distinctive: line 38
First-time: no data yet, nothing configured.
- Distinctive: line 84
Before handing off product scope:
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Provides: Outcome framing, scope reduction, acceptance criteria writing, and rollout planning for feature work.
Quick Reference
Goal: Clarify the outcome, reduce the scope, define done, ship safely
Flow: Frame outcome → Cut to smallest useful slice → Write acceptance criteria → Plan delivery → Close the loop
Ask only blocking questions. If a detail is minor, state the assumption and proceed.
Reference: skill:pattern-task-breakdown for sequencing the resulting work
Workflow
1. Frame the outcome
State the user and the problem, the desired behavior, the signal that will show it worked, and the explicit non-goals. Non-goals matter as much as goals: they are what stops scope from returning later as an assumption.
If the request describes a mechanism rather than a problem ("add a dropdown for X"), ask what the user is trying to accomplish before designing the mechanism.
2. Cut to the smallest useful slice
Identify the MVP path, the follow-up paths, and what is intentionally excluded. The test for a good first slice is whether a real user gets value from it alone, not whether it is easy to build.
Ask whether the first slice can be smaller and still useful. Usually it can.
3. Write acceptance criteria
Describe observable behavior, not implementation. Cover the states that get forgotten:
- First-time: no data yet, nothing configured.
- Empty: valid state, nothing to show.
- Invalid: bad input, rejected with a message the user can act on.
- Permission-denied: who cannot do this, and what they see.
- Slow: the operation takes longer than expected.
- Failed: the operation did not complete, and the user knows what to do next.
4. Plan delivery
Name the implementation seams, the dependencies, the rollout mechanism, and any migration. Decide whether the rollout is reversible or degrades safely. A feature that cannot be turned off is a feature that will cause an incident.
5. Close the loop
Decide what tests, telemetry, docs, and release notes ship with the change. Telemetry decided after launch usually means the success signal was never measured.
Product Review
- Is this solving a user problem, or only adding mechanism?
- Can the first slice be smaller while staying useful?
- What happens in the first-time, empty, invalid, slow, and failed states?
- Who can use it, who cannot, and how is that enforced?
- What metric or observable signal tells us it worked?
- Is the rollout reversible, or can it degrade safely?
- What existing behavior could this change break for current users?
Output Format
For planning responses, keep it compact:
Outcome: {user value}
Scope: {MVP} / Later: {deferred}
Acceptance: {3-7 bullets of observable behavior}
Risks: {top risks with mitigations}
Delivery: {ordered steps}
Open questions: {blocking only}Checklist
Before handing off product scope:
- Outcome, MVP scope, and non-goals are explicit
- Acceptance criteria cover success, empty, invalid, and permission states
- The success signal is named and measurable
- Rollout is reversible or degrades safely
- Blocking questions are separated from stated assumptions
Integration with Other Skills
With pattern-task-breakdown: sequence and estimate the scoped work.
With standards-api-design: design contracts for API-facing features.
With standards-database: plan data model changes and migrations.
With role-qa-engineer: expand acceptance criteria into edge-case coverage.
With standards-observability: instrument the telemetry behind the success signal.
With role-site-reliability-engineer: review risky rollouts and operational impact.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
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