SuperAPI AI Directory

feature-request-prioritization-review

Writing & research

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Updated 10-16 02:31

About this skill

Feature Request Prioritization Review

Use this skill to convert feature request prioritization, evidence quality, duplicate clustering, segment fit, roadmap, and close-the-loop questions into a concrete artifact with owners, gates, metrics, and recovery paths.

Workflow

  1. Identify request source, affected users, segment, job/pain, evidence, frequency, revenue/retention impact, strategic fit, current workaround, and delivery constraints.
  2. Read references/feature-request-prioritization-patterns.md.
  3. Classify request as bug, usability gap, workflow blocker, enterprise ask, compliance/security need, pricing/package gap, integration, power-user enhancement, or strategic bet.
  4. Define evidence score, clustering, opportunity framing, impact/effort/risk, dependency map, decision owner, communication plan, and revisit trigger.
  5. Produce prioritization review, state machine, decision table, event schema, scoring checklist, and stakeholder response.

When not to use

  • Do not use for generic advice the base model already handles without this skill's specific artifact contract.

Guardrails

  • Do not rank by loudest customer, biggest logo, newest ticket, or sales urgency alone.
  • Do not promise roadmap dates until ownership, scope, tradeoffs, and delivery confidence are approved.
  • Do not merge bugs, support confusion, workflow jobs, and strategic bets into one undifferentiated request list.
  • Do not close the loop with vague “maybe later” when the decision and reasoning are known.

Output format

Request context:
Audience / source of truth / risk boundary:

Prioritization plan:
| Area | Decision | Evidence | Risk | Owner |
| --- | --- | --- | --- | --- |

Evidence, tradeoffs, decision, and customer response:
- <trigger> -> <policy, metric, edge case, support note>