implementation-planning

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"]
dependencies	{"strategies":["critical-path-planning","experiment-running","plan-writing","prerequisite-planning","result-analysis"],"tactics":["checkpoint-and-recover","result-validation-loop","subagent-execution-loop","task-decomposition"],"sops":["context-checkpoint","context-init","execution-synthesis","experiment-execution-paper-overview","experiment-execution-paper-research","experiment-execution-paper-search","experiment-execution-quality-gate-check","experiment-execution-saturation-detection","experiment-execution-web-research","experiment-execution-web-search","ponytail:ponytail","ponytail:ponytail-debt","ponytail:ponytail-review","superpowers:brainstorming","superpowers:executing-plans","superpowers:finishing-a-development-branch","superpowers:receiving-code-review","superpowers:requesting-code-review","superpowers:subagent-driven-development","superpowers:test-driven-development","superpowers:using-git-worktrees","superpowers:verification-before-completion","superpowers:writing-plans"]}

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.

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：

1. 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。
2. 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。
3. 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