application-lifecycle-trace
Skill1 starsChanged 10 days agoMITView on GitHub
Show case application lifecycle
In this repository29 other files it gives its agents.
- AGENTS.mdAGENTS.md
- vercel-react-best-practices/AGENTS.mdAGENTS.md
- architecture-reviewSkill
- awsSkill
- codebase-mapperSkill
- code-review-frontendSkill
- comment-sickoSkill
- cspSkill
- demo-scriptSkill
- documentation-writerSkill
- dotnetSkill
- feature-orchestratorSkill
- frontend-patternsSkill
- lets-talk-about-itSkill
- nextjs-proxy-csp-hardeningSkill
- owasp-securitySkill
- pr-body-styleSkill
- prd-modeSkill
- prove-it-worksSkill
- security-reviewSkill
- simplifySkill
- sweSkill
- systems-architectureSkill
- task-generation-modeSkill
- thermo-nuclear-code-quality-reviewSkill
- typescript-react-reviewerSkill
- typescript-strict-styleSkill
- vercel-react-best-practicesSkill
- whats-going-onSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
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
Keep the trace focused on primary flows.
- Distinctive: line 15
Do not modify source code.
- Distinctive: line 54
Error Handling: If requirements are ambiguous, the AI must re-trigger the clarification loop.
≈ “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
Title: PRD Generation
Guardrails
- Trace only flows supported by source, docs, tests, or explicit user context.
- Label inferred lifecycle steps as assumptions.
- Keep the trace focused on primary flows. Do not add speculative components.
- Do not modify source code.
User Story: As a developer, I want to provide a high-level feature idea and receive a structured, unambiguous PRD so that a junior developer can implement it with minimal oversight.
Layer 1: User Journey (Flowchart)
Layer 2: Component Architecture
| Component | Logic Source | Responsibility | Key Reference |
| User Interface | System Prompt | Capture intent and selections | Prompt Entry |
| Clarification Processor | Rule: Process | Generate lettered/numbered questions | PRD Mode: Step 2 |
| Generation Engine | Rule: Structure | Format data into standard PRD sections | PRD Structure |
| Storage Manager | Rule: Output | Write Markdown to specific directory | /tasks/prd-*.md |
Layer 3: Sequence Diagram
Key Design Patterns Used:
- Stateful Interaction: The system pauses for user feedback (Clarification Step) before proceeding to final generation, ensuring accuracy.
- Template Method: The PRD follows a rigid, predefined structure regardless of the feature content to ensure consistency.
- Persistence Ignorance: The logic focuses on document structure, while the storage rule dictates the final file path and naming convention.
Data Structures
Quick Reference
- Event Triggers: User prompt containing "new feature" or "PRD".
- File Format: Standard GFM (GitHub Flavored Markdown).
- Error Handling: If requirements are ambiguous, the AI must re-trigger the clarification loop.
- Validation: Final PRD must be legible by a "Junior Developer" profile.
Related Lifecycles
- Task Decomposition: Converting a PRD into a
tasks-prd-*.mdfile. - DAP Implementation: Creating a Deployment Action Plan for schema changes.
- System Onboarding: Generating
use_cases.mdfrom repo analysis.
Next Step: I can now save this lifecycle trace to .planning/memory/system/001_lifecycle_prd_generation.md. Would you like me to finalize the file creation?
Install:
npx skills add ChristopherAlphonse/calphonse-skills --skill application-lifecycle-trace
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
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.