yogsoth-ai 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:
- An executable task plan (critical path identified, obstacles resolved)
- Dispatched execution via subagents
- Collected, validated, and statistically analyzed results
- 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.
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
External Implementation Backbone
本 campaign 的实现段（plan-writing → experiment-running → result-analysis）不自造，
而是直接 Skill load superpowers/ponytail 外部 skill 当 SOP。DARE 原生的排程
（CPM/PERT/TOC）与统计分析（bootstrap/ROPE/复现）夹在两端，是三明治：
排程层(DARE: CPM/PERT/TOC)
→ plan-writing: superpowers:brainstorming → superpowers:writing-plans
→ experiment-running: superpowers:using-git-worktrees
→ superpowers:executing-plans | superpowers:subagent-driven-development
→ superpowers:verification-before-completion
→ superpowers:finishing-a-development-branch
→ result-analysis(DARE: 统计 + 复现)
ponytail 三道 gate 贯穿执行段（硬接线进 dependencies，钉在前/后）：
| ponytail gate | 时机 |
|---|---|
| ponytail:ponytail | executing 之前载入（边写边精简） |
| ponytail:ponytail-review | code-review 之后载入（逐 diff 查过度工程） |
| ponytail:ponytail-debt | finishing 之前载入（收集欠债标记） |
舍弃（YAGNI）：ponytail:ponytail-audit（全库扫，错粒度）、ponytail:ponytail-help（速查卡）。
Context Recording
研究过程经 context-management 落盘，与最终报告分属不同文件：
- 进入本 campaign 时：import context-init，topic-slug 传
implementation-planning， 建立本 campaign 的过程 context 文件。init 幂等——同 Phase 重入返回原文件。 - 每个 strategy 完成后：import context-checkpoint（硬约束，不可跳过），把该 strategy 的过程与中间产出 append 进上一步的过程文件。
- 最终报告不写进这个过程文件——由本 campaign 的 synthesis SOP（execution-synthesis）
另起
implementation-planning-report文件落盘（见该 SOP）。
Available Strategies
Optional, no fixed order; the final leaf is always a sop.
| Strategy | When to use |
|---|---|
| critical-path-planning | Identify the shortest execution path via CPM forward/backward pass, resource leveling, and buffer insertion |
| experiment-running | Execute the plan by dispatching fresh subagents per task, monitoring status, and collecting results |
| plan-writing | Format critical path and prerequisites into bite-sized executable plan following superpowers:writing-plans conventions |
| prerequisite-planning | Identify obstacles blocking direct achievement and design intermediate objectives to overcome each |
| result-analysis | Statistically analyze collected results, verify reproducibility, and synthesize findings |
Available Tactics
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use |
|---|---|
| checkpoint-and-recover | Checkpoint state before risky operations, detect anomalies, and recover gracefully |
| result-validation-loop | Validate results through statistical testing, ROPE judgment, reproducibility re-runs, and final synthesis |
| subagent-execution-loop | Orchestrate task execution via fresh subagents with dispatch, monitoring, and result collection |
| task-decomposition | Orchestrate the breakdown of experiment design into sequenced, estimated, and formatted task plan |
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| context-checkpoint | Append research process and results to the current Phase's context file. Each append MUST contain >=500 lines of markdown covering both process and results. Use this skill at plan-designated checkpoint points — typically after each strategy completes or at key decision nodes within a research Phase. |
| context-init | Create a new context file for a research Phase. Called once at Phase start to initialize the file that subsequent context-checkpoint calls will append to. Use this skill whenever a new research Phase begins and a fresh context file is needed. |
| execution-synthesis | Synthesize complete execution report from all results, tests, and reproducibility data |
| experiment-execution-paper-overview | Import SOP: paper landscape scan (from literature-engine skill) |
| experiment-execution-paper-research | Import SOP: paper full-text reading (from literature-engine skill) |
| experiment-execution-paper-search | Import SOP: paper AI summary reading (from literature-engine skill) |
| experiment-execution-quality-gate-check | Shared SOP: verify quality gate criteria are met before proceeding |
| experiment-execution-saturation-detection | Shared SOP: detect information saturation — know when to stop searching/analyzing |
| experiment-execution-web-research | Import SOP: deep full-page content analysis (from web-browsing skill) |
| experiment-execution-web-search | Import SOP: quick web scan discovery (from web-browsing skill) |
| ponytail:ponytail | Lazy-senior reflex: simplest thing that holds; mark every deliberate shortcut |
| ponytail:ponytail-debt | Harvest ponytail debt markers before finishing |
| ponytail:ponytail-review | Audit the diff for over-engineering (delete/stdlib/native/yagni/shrink) |
| superpowers:brainstorming | Turn the experiment design into an implementation spec (clarify -> approaches -> spec -> self-review -> user gate) |
| superpowers:executing-plans | Execute the plan task-by-task in the current session with checkpoints |
| superpowers:finishing-a-development-branch | Verify tests -> merge / PR / branch cleanup |
| superpowers:receiving-code-review | Verify review feedback before applying; push back when wrong |
| superpowers:requesting-code-review | Dispatch a code-reviewer subagent after each task |
| superpowers:subagent-driven-development | Execute the plan via a fresh subagent per task with two-stage review |
| superpowers:test-driven-development | RED -> GREEN -> REFACTOR per task |
| superpowers:using-git-worktrees | Create an isolated worktree + run baseline tests before implementing |
| superpowers:verification-before-completion | Run the proving command and confirm output before claiming done |
| superpowers:writing-plans | Produce a bite-sized, TDD-structured implementation plan from the spec |