requirements-analysis
GitHub用于分析PigeonPod项目的功能、增强或非功能性需求,评估其价值、可行性、架构契合度及风险。需先查阅本地代码文档,再结合MCP工具确认外部依赖约束,最终输出决策与实施策略。
Trigger Scenarios
Install
npx skills add aizhimou/pigeon-pod --skill requirements-analysis -g -y
SKILL.md
Frontmatter
{
"name": "requirements-analysis",
"description": "Analyze product and technical requirements for the PigeonPod project with software engineering rigor. Use when users ask to evaluate a feature, enhancement, non-functional requirement, integration, or migration for value, feasibility, architecture fit, implementation impact, risk, delivery scope, or tradeoffs. Do not use for bug triage or root-cause analysis; use `bug-analysis` for bugfix-oriented work. Always inspect current repository docs and code first, then use MCP tools including Context7 to verify external library, framework, or API constraints before concluding."
}
Requirements Analysis
Analyze requirements against PigeonPod goals, current architecture, and implementation reality.
Follow This Workflow
- Restate the requirement in one short paragraph.
- Identify requirement type:
feature,enhancement,non-functional,integration, ormigration. - Define expected user value and business value.
- Read relevant project docs and code before giving conclusions.
- Use MCP/Context7 to confirm dependency or API constraints when external libraries/services are involved.
- Evaluate architecture fit, implementation complexity, data impact, and operational impact.
- Propose an implementation strategy with phased scope (
MVP,next,later). - Output a decision with explicit rationale and open questions.
If the request is primarily about broken behavior, regressions, incorrect results, crashes, or root-cause analysis, use bug-analysis instead.
Read Local Context First
Prioritize these files for PigeonPod:
README.mddev-docs/architecture/architecture-design-en.mdbackend/src/main/resources/application.ymlbackend/src/main/resources/db/migration/*.sql- Relevant backend packages under
backend/src/main/java/top/asimov/pigeon/ - Relevant frontend routes/components under
frontend/src/pages/andfrontend/src/components/
Use fast discovery commands when needed:
rg -n "keyword|concept|module" backend/src/main/java frontend/src dev-docs README.md
rg --files dev-docs/
Use Context7 and MCP Deliberately
Use Context7/MCP when the requirement depends on framework/library/service behavior, version constraints, configuration, or integration details.
Typical triggers:
- Spring Boot/MyBatis-Plus/Sa-Token behavior or config decisions
- React/Mantine/React Router/i18next/Axios constraints
- YouTube Data API v3 limits/quotas/contract details
- RSS/Podcasting namespace compatibility details
- yt-dlp options/behavior and compatibility implications
Rules:
- Resolve library ID first, then query focused questions.
- Prefer primary/official docs and version-aware guidance.
- Distinguish facts from inference.
- If docs conflict with local implementation, prioritize local code reality and call out the gap.
Evaluate With These Dimensions
Assess each dimension explicitly:
- Value Alignment: Match with PigeonPod core goals (YouTube-to-podcast conversion, auto-sync/download, feed usability, operations simplicity).
- Feasibility: Confirm technical possibility with current stack and constraints.
- Architecture Fit: Check compatibility with backend service boundaries, scheduler/event flow, DB schema, and frontend route/state model.
- Data and Migration Impact: Identify new fields/tables, migration requirements, backfill, and backward compatibility.
- API and Contract Impact: Identify REST/RSS contract changes and consumer compatibility risks.
- Security and Compliance: Review auth, permissions, secrets/API keys, abuse vectors.
- Performance and Cost: Estimate queue pressure, I/O/download load, external API quota consumption, and storage growth.
- Testability and Operability: Define unit/integration/e2e coverage and monitoring/logging needs.
Produce This Output Format
Use this structure in final analysis:
## Requirement Summary
- User request:
- Requirement type:
- Assumptions:
## Value Assessment
- User value:
- Product/business value:
- Priority suggestion: High/Medium/Low
## Feasibility and Architecture Fit
- Current touchpoints:
- Proposed changes:
- Architecture fit verdict: Good/Partial/Poor
## Impact Analysis
- Backend impact:
- Frontend impact:
- Database/migration impact:
- External dependency impact:
- Security/performance/ops impact:
## Delivery Plan
- MVP scope:
- Non-MVP scope:
- Estimated complexity: S/M/L/XL
- Key risks and mitigations:
## Decision
- Recommendation: Proceed / Proceed with constraints / Defer / Reject
- Reasoning:
- Open questions:
Decision Heuristics
- Recommend
Proceedwhen value is clear, fit is good, and risk is manageable. - Recommend
Proceed with constraintswhen value is high but scope/risk needs staged delivery. - Recommend
Deferwhen value exists but prerequisites are missing. - Recommend
Rejectwhen requirement conflicts with core goals or creates disproportional cost/risk.
Quality Bar
Before finalizing, verify all checks:
- Base conclusions on repository evidence, not assumptions only.
- Confirm external-library/API claims through Context7/MCP when relevant.
- Separate facts, assumptions, and unknowns.
- Include at least one feasible implementation path.
- Include explicit tradeoffs and rollback/fallback considerations.
Version History
- d4e69d1 Current 2026-08-20 12:06


