implementation-planning
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npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/implementation-planning**Positioning**: "How to do it + do it" — from validated experiment design to executed results.
SKILL.md
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--- name: implementation-planning description: "Plan execution path, produce executable plan, dispatch subagents, collect and analyze results" version: 1.0.0 category: experiment-execution type: campaign strategies: - critical-path-planning - prerequisite-planning - plan-writing - experiment-running - result-analysis tactics: - task-decomposition - subagent-execution-loop - checkpoint-and-recover - result-validation-loop --- # Campaign 4: Implementation Planning **Positioning**: "How to do it + do it" — from validated experiment design to executed results. ## HARD-GATE Before entering this campaign, the following must be true: - [ ] Experiment design exists (output of Campaign 3: experiment-design) - [ ] Variables are operationalized with concrete measures - [ ] Success criteria are defined with statistical thresholds - [ ] Resource budget is allocated (tokens, time, compute) If any gate fails, STOP and return to the appropriate upstream campaign. ## Campaign Goal Transform a validated experiment design into: 1. An executable task plan (critical path identified, obstacles resolved) 2. Dispatched execution via subagents 3. Collected, validated, and statistically analyzed results 4. A comprehensive execution report with reproducibility verification ## Strategy Selection | Situation | Strategy | Key Question | |-----------|----------|--------------| | Need shortest execution path | critical-path-planning | What is the shortest path? | | Obstacles block direct execution | prerequisite-planning | What obstacles are in the way? | | Ready to format executable plan | plan-writing | How to write it as an executable plan? | | Plan ready, execute tasks | experiment-running | How to execute? | | Results collected, need analysis | result-analysis | What do the results tell us? | Typical flow: critical-path-planning → prerequisite-planning → plan-writing → experiment-running → result-analysis ## Budget Gate | Phase | Max Budget | Checkpoint | |-------|-----------|------------| | Planning (strategies 1-3) | 20% of total | Plan document produced | | Execution (strategy 4) | 60% of total | All tasks DONE or BLOCKED | | Analysis (strategy 5) | 20% of total | Statistical report produced | If any phase exceeds budget, STOP and report partial results. ## Superpowers Adaptation This campaign internalizes two superpowers patterns: ### From superpowers:writing-plans - Tasks are bite-sized (one clear action each) - Every task specifies exact file paths (no placeholders) - TDD where applicable (test first, implement second) - No TBD/TODO in final plan — everything resolved or explicitly deferred ### From superpowers:subagent-driven-development - Fresh subagent per task (clean context) - Three-stage review: implementer → reviewer → integration - Status codes: DONE / BLOCKED / NEEDS_CONTEXT - Continuous execution until all tasks complete or budget exhausted ## Minimum Yield Even if execution is partial, this campaign MUST produce: - Task dependency graph (from planning phase) - Execution log with status per task - Whatever results were collected before budget/failure - Clear statement of what remains undone and why