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Agent Skill · 研究检索

plan-hard(努力计划)

plan-hard 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

plan-hard 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 46,976。

总安装 753周安装 32GitHub Stars 6下载 264核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:plan-hard(努力计划)
来源仓库:https://github.com/duc01226/easyplatform
仓库路径:skills/plan-hard
安装命令:
npx skills add https://github.com/duc01226/easyplatform --skill plan-hard
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/duc01226/easyplatform --skill plan-hard

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于在任务前查找、检索和筛选相关信息。适合根据关键词、任务场景或来源线索快速定位候选结果,支持多宿主环境协作。通过 npx skills add 命令从指定 GitHub 仓库安装,使用前需确认权限和维护状态。建议检查是否会触发联网、命令执行或文件读写操作,确保符合安全策略。

可结合来源仓库和原始 README 进一步核验具体用法和适用边界。

来源仓库内路径:skills/plan-hard

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/duc01226/easyplatform --skill plan-hard;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

plan-hard 怎么安装?

在终端执行 npx skills add https://github.com/duc01226/easyplatform --skill plan-hard。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

plan-hard 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

plan-hard 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

plan-hard 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

plan-hard 用的人多吗?

公开数据是累计安装 753 次,近一周安装 32 次,下载 264 次,GitHub 6 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

plan-hard 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
plan-hard

努力计划 · 本页

7536需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.
Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.
AI Mistake Prevention — Failure modes to avoid on every task: - Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. - Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. - Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. - Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. - When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. - Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. - Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. - Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. - Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. - Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.
Understand Code First — HARD-GATE: Do NOT write, plan, or fix until you READ existing code. 1. Search 3+ similar patterns (grep/glob) — cite file:line evidence 2. Read existing files in target area — understand structure, base classes, conventions 3. Run python.claude/scripts/code_graph trace <file> --direction both --json when .code-graph/graph.db exists 4. Map dependencies via connections or callers_of — know what depends on your target 5. Write investigation to .ai/workspace/analysis/ for non-trivial tasks (3+ files) 6. Re-read analysis file before implementing — never work from memory alone 7. NEVER invent new patterns when existing ones work — match exactly or document deviation BLOCKED until: - [] Read target files - [] Grep 3+ patterns - [] Graph trace (if graph.db exists) - [] Assumptions verified with evidence
Cross-Service Check — Microservices/event-driven: MANDATORY before concluding investigation, plan, spec, or feature doc. Missing downstream consumer = silent regression. | Boundary | Grep terms | | --- | --- | | Event producers | Publish, Dispatch, Send, emit, EventBus, outbox, IntegrationEvent | | Event consumers | Consumer, EventHandler, Subscribe, @EventListener, inbox | | Sagas/orchestration | Saga, ProcessManager, Choreography, Workflow, Orchestrator | | Sync service calls | HTTP/gRPC calls to/from other services | | Shared contracts | OpenAPI spec, proto, shared DTO — flag breaking changes | | Data ownership | Other service reads/writes same table/collection → Shared-DB anti-pattern | Per touchpoint: owner service · message name · consumers · risk (NONE / ADDITIVE / BREAKING). BLOCKED until: Producers scanned · Consumers scanned · Sagas checked · Contracts reviewed · Breaking-change risk flagged
Estimation Framework — Story Points (Modified Fibonacci) + Man-Days for 3-5yr dev (6 productive hrs/day,.NET + Angular stack). AI estimate assumes Claude Code with good project context (code graph, patterns, hooks active). | SP | Complexity | Description | Traditional (code + test) | AI-Assisted (code+rev + test+rev) | | --- | --- | --- | --- | --- | | 1 | Low | Trivial: single field, config flag, CSS fix | 0.5d (0.3d+0.2d) | 0.25d (0.15d+0.1d) | | 2 | Low | Small: simple CRUD endpoint OR basic component | 1d (0.6d+0.4d) | 0.35d (0.2d+0.15d) | | 3 | Medium | Medium: form + API + validation | 2d (1.3d+0.7d) | 0.65d (0.4d+0.25d) | | 5 | Medium | Large: multi-layer feature (BE + FE) | 4d (2.5d+1.5d) | 1.0d (0.6d+0.4d) | | 8 | High | Very large: complex feature + migration | 6d (4d+2d) | 1.5d (1.0d+0.5d) | | 13 | Critical | Epic: cross-service — SHOULD split | 10d (6.5d+3.5d) | 2.0d (1.3d+0.7d) | | 21 | Critical | MUST split — not sprint-ready | >15d | ~3d | AI speedup grows with task size: SP 1 ≈ 2x · SP 2-3 ≈ 3x · SP 5-8 ≈ 4x · SP 13+ ≈ 5x. Pattern-heavy CQRS/Angular boilerplate eliminated in hours at any scale. Fixed overhead: human review. AI column breakdown: (code_gen × 1.3) + (test_gen × 1.3) — each artifact adds 30% human review overhead. Test writing with AI = few hours generation + 30% review, same model as coding. Output story_points, complexity, man_days_traditional, man_days_ai in plan/PBI frontmatter.
  • docs/project-reference/domain-entities-reference.md — Domain entity catalog, relationships, cross-service sync (read when task involves business entities/models) (content auto-injected by hook — check for [Injected:...] header before reading)
  • docs/specs/ — Test specifications by module (read existing TCs to include test strategy in plan)
Plan Quality — Every plan phase MUST ATTENTION include test specifications. 1. Add ## Test Specifications section with TC-{FEAT}-{NNN} IDs to every phase file 2. Map every functional requirement to ≥1 TC (or explicit TBD with rationale) 3. TC IDs follow TC-{FEATURE}-{NNN} format — reference by ID, never embed full content 4. Before any new workflow step: call TaskList and re-read the phase file 5. On context compaction: call TaskList FIRST — never create duplicate tasks 6. Verify TC satisfaction per phase before marking complete (evidence must be file:line, not TBD) Mode: TDD-first → reference existing TCs with Evidence: TBD. Implement-first → use TBD → /tdd-spec fills after.
Iterative Phase Quality — Score complexity BEFORE planning. Complexity signals: >5 files +2, cross-service +3, new pattern +2, DB migration +2 Score >=6 → MUST ATTENTION decompose into phases. Each phase: - ≤5 files modified - ≤3h effort - Follows cycle: plan → implement → review → fix → verify - Do NOT start Phase N+1 until Phase N passes VERIFY Phase success = all TCs pass + code-reviewer agent approves + no CRITICAL findings.
Fix-Layer Accountability — NEVER fix at the crash site. Trace the full flow, fix at the owning layer. AI default behavior: see error at Place A → fix Place A. This is WRONG. The crash site is a SYMPTOM, not the cause. MANDATORY before ANY fix: 1. Trace full data flow — Map the complete path from data origin to crash site across ALL layers (storage → backend → API → frontend → UI). Identify where the bad state ENTERS, not where it CRASHES. 2. Identify the invariant owner — Which layer's contract guarantees this value is valid? That layer is responsible. Fix at the LOWEST layer that owns the invariant — not the highest layer that consumes it. 3. One fix, maximum protection — Ask: "If I fix here, does it protect ALL downstream consumers with ONE change?" If fix requires touching 3+ files with defensive checks, you are at the wrong layer — go lower. 4. Verify no bypass paths — Confirm all data flows through the fix point. Check for: direct construction skipping factories, clone/spread without re-validation, raw data not wrapped in domain models, mutations outside the model layer. BLOCKED until: - [] Full data flow traced (origin → crash) - [] Invariant owner identified with file:line evidence - [] All access sites audited (grep count) - [] Fix layer justified (lowest layer that protects most consumers) Anti-patterns (REJECT these): - "Fix it where it crashes" — Crash site ≠ cause site. Trace upstream. - "Add defensive checks at every consumer" — Scattered defense = wrong layer. One authoritative fix > many scattered guards. - "Both fix is safer" — Pick ONE authoritative layer. Redundant checks across layers send mixed signals about who owns the invariant.
Each phase file MUST ATTENTION satisfy: <=5 files per phase, <=3h effort, clear success criteria, mapped test cases.
Evidence Gate: MANDATORY IMPORTANT MUST ATTENTION — every claim, finding, and recommendation requires file:line proof or traced evidence with confidence percentage (>80% to act, <80% must verify first).
External Memory: For complex or lengthy work (research, analysis, scan, review), write intermediate findings and final results to a report file in plans/reports/ — prevents context loss and serves as deliverable.

Quick Summary

Goal: Research, analyze the codebase, and create a detailed phased implementation plan with user collaboration.

Workflow:

  1. Pre-Check — Detect active/suggested plan or create new directory
  2. Research — Parallel researcher subagents explore different aspects (max 5 tool calls each)
  3. Codebase Analysis — Search for project reference docs (patterns-reference, project-structure, architecture, adr); scout if not found
  4. Plan Creation — Planner subagent creates plan.md + phase-XX files with full sections
  5. Post-Validation — Optionally interview user to confirm decisions via /plan-validate

Key Rules:

  • PLANNING ONLY: do NOT implement or execute code changes
  • Always run /plan-review after plan creation
  • Ask user to confirm before any next step
  • MANDATORY IMPORTANT MUST ATTENTION detect new tech/lib in plan and create validation task (see New Tech/Lib Gate below)

New Tech/Lib Gate (MANDATORY for all plans)

MANDATORY IMPORTANT MUST ATTENTION after plan creation, detect new tech/packages/libraries not in the project. If found: TaskCreate per lib → WebSearch top 3 alternatives → compare (fit, size, community, learning curve, license) → recommend with confidence % → AskUserQuestion to confirm. Skip if plan uses only existing dependencies.

Greenfield Mode

Auto-detected: If no existing codebase is found (no code directories like src/, app/, lib/, server/, packages/, etc., no manifest files like package.json/*.sln/go.mod, no populated project-config.json), this skill switches to greenfield mode automatically. Planning artifacts (docs/, plans/,.claude/) don't count — the project must have actual code directories with content.

When greenfield is detected:

  1. Skip codebase analysis phase (researcher subagents that grep code)
  2. Replace with: market research + business evaluation phase using WebSearch + WebFetch
  3. Delegate architecture decisions to solution-architect agent
  4. Output: plans/{id}/plan.md with greenfield-specific phases (domain model, tech stack, project structure)
  5. Skip reading project reference docs (won't exist in greenfield)
  6. Enable broad web research for tech landscape, best practices, framework comparisons
  7. Every decision point requires AskUserQuestion with 2-4 options + confidence %
  8. [CRITICAL] Business-First Protocol: Tech stack decisions come AFTER full business analysis. Do NOT ask user to pick a tech stack upfront. Instead: complete business evaluation → derive technical requirements → research current market options → produce comparison report → present to user for decision. See solution-architect agent for the full tech stack research methodology.
  • Research reports <=150 lines; plan.md <=80 lines
  • External Memory: Write all research and analysis to .ai/workspace/analysis/{task-name}.analysis.md. Re-read ENTIRE analysis file before generating plan.

Activate planning skill.

Scaffolding-First Protocol (Conditional)

Activation conditions (ALL must be true):

  1. Active workflow is greenfield-init OR big-feature
  2. AI MUST ATTENTION self-investigate for existing base/foundational abstractions using these patterns:

- Abstract/base classes: abstract class.*Base|Base[A-Z]\w+|Abstract[A-Z]\w+ - Generic interfaces: interface I\w+<|IGeneric|IBase - Infrastructure abstractions: IRepository|IUnitOfWork|IService|IHandler - Utility/extension layers: Extensions|Helpers|Utils|Common (directories or classes) - Frontend foundations: base.*component|base.*service|base.*store|abstract.*component (if frontend present) - DI/IoC registration: search for DI registration patterns idiomatic to the project's framework

  1. If existing scaffolding found → SKIP. Log: "Existing scaffolding detected at {file:line}. Skipping Phase 1 scaffolding."
  2. If NO foundational abstractions found → PROCEED with scaffolding phase.

When activated:

Phase 1 of the plan MUST ATTENTION be Architecture Scaffolding — all base abstract classes, generic interfaces, infrastructure abstractions, and DI registration with OOP/SOLID principles. Runs BEFORE feature stories. AI self-investigates what base classes the tech stack needs. All infrastructure behind interfaces with at least one concrete implementation (Dependency Inversion).

When skipped: Plan proceeds normally — feature stories build on existing base classes.

PLANNING-ONLY — Collaboration Required

DO NOT use the EnterPlanMode tool — you are ALREADY in a planning workflow. DO NOT implement or execute any code changes. COLLABORATE with the user: ask decision questions, present options with recommendations. After plan creation, ALWAYS run /plan-review to validate the plan. ASK user to confirm the plan before any next step.

Your mission

Pre-Creation Check (Active vs Suggested Plan)

Check the ## Plan Context section in the injected context:

  • If "Plan:" shows a path -> Active plan exists. Ask user: "Continue with this? [Y/n]"
  • If "Suggested:" shows a path -> Branch-matched hint only. Ask if they want to activate or create new.
  • If "Plan: none" -> Create new plan using naming from ## Naming section.

Workflow

  1. If creating new: Create directory using Plan dir: from ## Naming section, then run node.claude/scripts/set-active-plan.cjs {plan-dir} If reusing: Use the active plan path from Plan Context. Make sure you pass the directory path to every subagent during the process.
  2. Follow strictly to the "Plan Creation & Organization" rules of planning skill.
  3. Use multiple researcher agents (max 2 agents) in parallel to research for this task: Each agent research for a different aspect of the task and are allowed to perform max 5 tool calls.
  4. Analyze the codebase: search for project reference docs (patterns-reference, project-structure, architecture, adr) and read those found. ONLY PERFORM THIS IF docs not found or older than 3 days: Use /scout <instructions> to search the codebase for files needed.
  5. Main agent gathers all research and scout report filepaths, and pass them to planner subagent with the prompt to create an implementation plan of this task.
  6. Main agent receives the implementation plan from planner subagent, and ask user to review the plan

Post-Plan Validation (Optional)

After plan creation, offer validation interview to confirm decisions before implementation.

Check ## Plan Context -> Validation: mode=X, questions=MIN-MAX:

ModeBehavior
promptAsk user: "Validate this plan with a brief interview?" -> Yes (Recommended) / No
autoAutomatically execute /plan-validate {plan-path}
offSkip validation step entirely

If mode is prompt: Use AskUserQuestion tool with options above. If user chooses validation or mode is auto: Execute /plan-validate {plan-path} SlashCommand.

Output Requirements

Plan Directory Structure (use Plan dir: from ## Naming section)

{plan-dir}/
├── research/
│   ├── researcher-XX-report.md
│   └── ...
├── reports/
│   ├── XX-report.md
│   └── ...
├── scout/
│   ├── scout-XX-report.md
│   └── ...
├── plan.md
├── phase-XX-phase-name-here.md
└── ...

Research Output Requirements

  • Ensure every research markdown report remains concise (<=150 lines) while covering all requested topics and citations.

Plan File Specification

  • Every plan.md MUST ATTENTION start with YAML frontmatter: --- title: '{Brief title}' description: '{One sentence for card preview}' status: pending priority: P2 effort: {sum of phases, e.g., 4h} story_points: {sum of phase SPs, e.g., 8} man_days_traditional: '{total e.g., 6d (4d code + 2d test)}' man_days_ai: '{total with AI e.g., 3d (2d code + 1d test)}' branch: {current git branch} tags: [relevant, tags] created: {YYYY-MM-DD} ---
  • Save overview at {plan-dir}/plan.md (<80 lines): list each phase with status, progress, and links to phase files.
  • For each phase, create {plan-dir}/phase-XX-phase-name-here.md with sections: Context links, Overview, Key Insights, Requirements, Alternatives Considered (minimum 2 approaches with pros/cons), Design Rationale (WHY chosen approach), Architecture, UI Layout (see below), Related code files, Implementation Steps, Todo list, Success Criteria, Risk Assessment, Security Considerations, Next steps.
  • UI Layout: For frontend-facing phases, include ASCII wireframe. Classify components by tier (common/domain-shared/page-app). For backend-only phases: ## UI Layout → N/A — Backend-only change.

IMPORTANT Task Planning Notes (MUST ATTENTION FOLLOW)

  • Always plan and break work into many small todo tasks using TaskCreate
  • Always add a final review todo task to verify work quality and identify fixes/enhancements
  • MANDATORY FINAL TASKS: After creating all planning todo tasks, ALWAYS add these final tasks:

1. Task: "Write test specifications for each phase" — Add ## Test Specifications with TC-{FEAT}-{NNN} IDs to every phase file. Use /tdd-spec if feature docs exist. Use Evidence: TBD for TDD-first mode. 2. Task: "Run /plan-validate" — Trigger /plan-validate skill to interview the user with critical questions and validate plan assumptions 3. Task: "Run /plan-review" — Trigger /plan-review skill with deep 3-round protocol (R1: checklist, R2: code-proof trace, R3: adversarial simulation). Review depth based on SP: ≤3 → 2 rounds min, 4-8 → 3 rounds, >8 → 3 rounds + code-proof mandatory. 4. Task: "Run /why-review (standalone only)" — If NOT inside a workflow, trigger /why-review to validate design rationale, alternatives considered, and risk assessment in the plan. Skip if a workflow already includes /why-review in its sequence.

Important Notes

  • Activate needed skills from catalog during process.
  • Token efficiency without sacrificing quality. Sacrifice grammar for concision in reports.
  • Unresolved questions → list at end of report.

Standalone Review Gate (Non-Workflow Only)

MANDATORY IMPORTANT MUST ATTENTION: If this skill is called outside a workflow (standalone /plan-hard), the generated plan MUST ATTENTION include /review-changes as a final phase/task in the plan. This ensures all implementation changes get reviewed before commit even without a workflow enforcing it. If already running inside a workflow (e.g., feature, bugfix), skip this — the workflow sequence handles /review-changes at the appropriate step.

Next Steps (Standalone: MUST ATTENTION ask user via AskUserQuestion. Skip if inside workflow.)

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS after completing this skill, you MUST ATTENTION use AskUserQuestion to present these options. Do NOT skip because the task seems "simple" or "obvious" — the user decides:

  • "Proceed with full workflow (Recommended)" — I'll detect the best workflow to continue from here (plan created). This ensures review, validation, implementation, and testing steps aren't skipped.
  • "/why-review" — Validate design rationale in the plan before implementation (standalone only — skipped when workflow includes it)
  • "/plan-review" — Validate plan before implementation
  • "/plan-validate" — Interview user to confirm plan decisions
  • "Skip, continue manually" — user decides

Post-Plan Granularity Self-Check (MANDATORY)

Plan Granularity — Every phase must pass 5-point check before implementation: 1. Lists exact file paths to modify (not generic "implement X") 2. No planning verbs (research, investigate, analyze, determine, figure out) 3. Steps ≤30min each, phase total ≤3h 4. ≤5 files per phase 5. No open decisions or TBDs in approach Failing phases → create sub-plan. Repeat until ALL leaf phases pass (max depth: 3). Self-question: "Can I start coding RIGHT NOW? If any step needs 'figuring out' → sub-plan it."

Preservation Inventory (MANDATORY for bugfixes)

Preservation Inventory — MANDATORY for bugfix plans. Trigger keywords in plan title/frontmatter: fix, bug, regression, broken, defect. Author MUST produce this table BEFORE writing implementation steps. Columns: Invariant | file:line | Why (data consequence if broken) | Verification (TC-ID or grep) BLOCKED until: ≥3 rows · every File cell has file:line · every Verification cell has TC-ID or grep (not "manually verify")

After creating all phase files, run the recursive decomposition loop:

  1. Score each phase against the 5-point criteria (file paths, no planning verbs, ≤30min steps, ≤5 files, no open decisions)
  2. For each FAILING phase → create task to decompose it into a sub-plan (with its own /plan → /plan-review → /plan-validate → fix cycle)
  3. Re-score new phases. Repeat until ALL leaf phases pass (max depth: 3)
  4. Self-question: "For each phase, can I start coding RIGHT NOW? If any needs 'figuring out' → sub-plan it."

Closing Reminders

MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting. MANDATORY IMPORTANT MUST ATTENTION validate decisions with user via AskUserQuestion — never auto-decide. MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality. MANDATORY IMPORTANT MUST ATTENTION READ the following files before starting:

  • IMPORTANT MUST ATTENTION verify all phases pass 5-point granularity check. Failing phases → sub-plan. "Can I start coding RIGHT NOW?" <!-- SYNC:understand-code-first:reminder -->
  • IMPORTANT MUST ATTENTION search 3+ existing patterns and read code BEFORE any modification. Run graph trace when graph.db exists.
  • IMPORTANT MUST ATTENTION include story_points, complexity, man_days_traditional, man_days_ai in plan/PBI frontmatter. Use SP table: SP 1=0.5d/0.25d, SP 2=1d/0.35d, SP 3=2d/0.65d, SP 5=4d/1.0d, SP 8=6d/1.5d · SP 13=10d/2.0d. SP 13 SHOULD split, SP 21 MUST split.
  • IMPORTANT MUST ATTENTION include ## Test Specifications with TC IDs per phase. Call TaskList before creating new tasks.
  • IMPORTANT MUST ATTENTION score complexity first. Score >=6 → decompose. Each phase: plan → implement → review → fix → verify. No skipping.
  • IMPORTANT MUST ATTENTION trace full data flow and fix at the owning layer, not the crash site. Audit all access sites before adding ?..
  • IMPORTANT MUST ATTENTION microservices/event-driven: scan producers, consumers, sagas, contracts in task scope. Per touchpoint: owner · message · consumers · risk (NONE/ADDITIVE/BREAKING). Missing consumer = silent regression.
  • MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.
  • MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.

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Gen Agent Trust Hub

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