make-plan▌
thedotmack/claude-mem · updated Apr 8, 2026
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You are an ORCHESTRATOR. Create an LLM-friendly plan in phases that can be executed consecutively in new chat contexts.
Make Plan
You are an ORCHESTRATOR. Create an LLM-friendly plan in phases that can be executed consecutively in new chat contexts.
Delegation Model
Use subagents for fact gathering and extraction (docs, examples, signatures, grep results). Keep synthesis and plan authoring with the orchestrator (phase boundaries, task framing, final wording). If a subagent report is incomplete or lacks evidence, re-check with targeted reads/greps before finalizing.
Subagent Reporting Contract (MANDATORY)
Each subagent response must include:
- Sources consulted (files/URLs) and what was read
- Concrete findings (exact API names/signatures; exact file paths/locations)
- Copy-ready snippet locations (example files/sections to copy)
- "Confidence" note + known gaps (what might still be missing)
Reject and redeploy the subagent if it reports conclusions without sources.
Plan Structure
Phase 0: Documentation Discovery (ALWAYS FIRST)
Before planning implementation, deploy "Documentation Discovery" subagents to:
- Search for and read relevant documentation, examples, and existing patterns
- Identify the actual APIs, methods, and signatures available (not assumed)
- Create a brief "Allowed APIs" list citing specific documentation sources
- Note any anti-patterns to avoid (methods that DON'T exist, deprecated parameters)
The orchestrator consolidates findings into a single Phase 0 output.
Each Implementation Phase Must Include
- What to implement — Frame tasks to COPY from docs, not transform existing code
- Good: "Copy the V2 session pattern from docs/examples.ts:45-60"
- Bad: "Migrate the existing code to V2"
- Documentation references — Cite specific files/lines for patterns to follow
- Verification checklist — How to prove this phase worked (tests, grep checks)
- Anti-pattern guards — What NOT to do (invented APIs, undocumented params)
Final Phase: Verification
- Verify all implementations match documentation
- Check for anti-patterns (grep for known bad patterns)
- Run tests to confirm functionality
Key Principles
- Documentation Availability ≠ Usage: Explicitly require reading docs
- Task Framing Matters: Direct agents to docs, not just outcomes
- Verify > Assume: Require proof, not assumptions about APIs
- Session Boundaries: Each phase should be self-contained with its own doc references
Anti-Patterns to Prevent
- Inventing API methods that "should" exist
- Adding parameters not in documentation
- Skipping verification steps
- Assuming structure without checking examples
How to use make-plan on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add make-plan
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches make-plan from GitHub repository thedotmack/claude-mem and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate make-plan. Access the skill through slash commands (e.g., /make-plan) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★48 reviews- ★★★★★Olivia Flores· Dec 24, 2024
We added make-plan from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Mateo Chawla· Dec 12, 2024
make-plan is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Dhruvi Jain· Dec 8, 2024
make-plan reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Kabir Sethi· Dec 8, 2024
make-plan reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Pratham Ware· Dec 4, 2024
Solid pick for teams standardizing on skills: make-plan is focused, and the summary matches what you get after install.
- ★★★★★Oshnikdeep· Nov 27, 2024
I recommend make-plan for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ren Farah· Nov 27, 2024
I recommend make-plan for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Noah Choi· Nov 15, 2024
Keeps context tight: make-plan is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Olivia Torres· Nov 3, 2024
make-plan fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Noah Khan· Oct 22, 2024
We added make-plan from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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