make-plan
The make-plan skill creates a phased, documentation-driven implementation strategy by deploying subagents to discover relevant APIs, signatures, and patterns before synthesizing a structured plan with verification checkpoints. Use it when planning complex features, multi-step implementations, or tasks requiring accurate API knowledge before execution, especially as a precursor to the "do" skill for hands-on implementation.
git clone --depth 1 https://github.com/thedotmack/claude-mem /tmp/make-plan && cp -r /tmp/make-plan/plugin/skills/make-plan ~/.claude/skills/make-planSKILL.md
# 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: 1. Sources consulted (files/URLs) and what was read 2. Concrete findings (exact API names/signatures; exact file paths/locations) 3. Copy-ready snippet locations (example files/sections to copy) 4. "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: 1. Search for and read relevant documentation, examples, and existing patterns 2. Identify the actual APIs, methods, and signatures available (not assumed) 3. Create a brief "Allowed APIs" list citing specific documentation sources 4. 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 1. **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" 2. **Documentation references** — Cite specific files/lines for patterns to follow 3. **Verification checklist** — How to prove this phase worked (tests, grep checks) 4. **Anti-pattern guards** — What NOT to do (invented APIs, undocumented params) ### Final Phase: Verification 1. Verify all implementations match documentation 2. Check for anti-patterns (grep for known bad patterns) 3. 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 ## See Also - `oh-my-issues` — the issue-side sibling. When the plan you're being asked to make is rooted in a bug or feature backlog rather than a fresh idea, route through `oh-my-issues` first to cluster issues by root cause into plan masters and `plans/0X-*.md` design docs. `make-plan` then operates on the design doc for one plan slice.
Watch a pull request or review cycle until it is ready to merge. Use when asked to babysit, monitor, or keep checking PR comments, reviews, and CI until all actionable issues are resolved.
Audit a design against Dieter Rams' ten "Good design is..." principles, then hand off a /make-plan prompt for one of three outcomes — new design, refine design, or redesign. Use when the user says "audit this design", "design review", "check this UI against Rams", "is this UI good", "critique this design", "design audit", or asks for a critique that should lead to a plan.
Execute a phased implementation plan using subagents. Use when asked to execute, run, or carry out a plan — especially one created by make-plan.
Explain how claude-mem captures observations, when memory injection kicks in, and where data lives. Use when the user asks "how does claude-mem work?" or "what is this thing doing?".
Build and query AI-powered knowledge bases from claude-mem observations. Use when users want to create focused "brains" from their observation history, ask questions about past work patterns, or compile expertise on specific topics.
Prime a codebase by reading every source file in full. Use when starting work on a new or unfamiliar project, or when the user asks to "learn the codebase", "read the codebase", "prime", or "get up to speed".
Search claude-mem's persistent cross-session memory database. Use when user asks "did we already solve this?", "how did we do X last time?", or needs work from previous sessions.