AI Agent Skill HUB

plansuite

Unified planning+execution workflow: create a file-based plan with sub-plans, freeze it as FINALIZED, and execute in a separate session with checkpoints and progress/findings logs. Use when you want project plans with subplans (milestones), controlled execution, and session-based implementation runs.

7 stars
byDemerzels-lab
View on GitHubInstallation ↓

Best use case

plansuite is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Unified planning+execution workflow: create a file-based plan with sub-plans, freeze it as FINALIZED, and execute in a separate session with checkpoints and progress/findings logs. Use when you want project plans with subplans (milestones), controlled execution, and session-based implementation runs.

Teams using plansuite should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/plansuite/SKILL.md --create-dirs "https://raw.githubusercontent.com/Demerzels-lab/elsamultiskillagent/main/public/skills/double729/plansuite/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/plansuite/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How plansuite Compares

Feature / AgentplansuiteStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Unified planning+execution workflow: create a file-based plan with sub-plans, freeze it as FINALIZED, and execute in a separate session with checkpoints and progress/findings logs. Use when you want project plans with subplans (milestones), controlled execution, and session-based implementation runs.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# PlanSuite

把“写计划（含子计划）→ 冻结计划（变更控制）→ 独立会话执行（带检查点）”合成一个最小可用流程。

## 文件结构（在当前工作目录创建/维护）
- `task_plan.md`：计划主文件（含子计划/里程碑）
- `progress.md`：执行进度（每次推进都要写）
- `findings.md`：发现/决策/坑点（避免重复踩坑）

> 不要把这三份写到聊天里：写到文件，才能恢复/续跑。

## 工作流（强约束，防跑偏）

### 0) 初始化（第一次做这个项目）
1. 如果缺文件：用模板创建 `task_plan.md/progress.md/findings.md`（见 `templates/`）。
2. 让用户确认目标、范围、约束、完成定义（DoD）。

### 1) 计划阶段（拆子计划）
在 `task_plan.md` 里输出：
- 背景/目标
- 范围（做/不做）
- 风险 & 回滚
- 子计划（Milestones）：每个子计划要有
  - 输入/输出
  - 验收标准
  - 预计工具调用/文件改动
  - 风险与回滚点

### 2) 冻结阶段（FINALIZED）
只有当用户明确说“按这个计划执行”后：
1. 在 `task_plan.md` 顶部写入：`STATUS: FINALIZED` + 时间戳。
2. 把“接下来要执行的子计划编号/名称”写入 `progress.md` 的 `Next`。

> 规则：未 FINALIZED 不允许进入执行阶段（最多做调查/补充计划）。

### 3) 执行阶段（独立会话 + 检查点）
当进入执行：
1. 建议用 `sessions_spawn` 开一个隔离执行会话（避免污染主会话上下文）。
2. 每完成一个子计划：
   - 更新 `progress.md`（Done/Next/Blockers）
   - 更新 `findings.md`（关键决策、踩坑、验证命令、回滚步骤）
3. 检查点策略（默认每个子计划至少一次）：
   - 执行前：复述子计划的 DoD + 风险 + 回滚
   - 执行后：给出验证步骤 + 结果

### 4) 变更控制（计划变更）
如果执行中发现计划不成立：
1. 不要“边做边改”。先写入 `findings.md`，再把变更提案写入 `task_plan.md`。
2. 把 `STATUS` 改为 `DRAFT`，等待用户重新确认。

## 你在什么时候用什么文件
- 需要问清楚/拆任务 → `task_plan.md`
- 需要告诉用户进度/下一步 → `progress.md`
- 需要记录结论/命令/坑/回滚 → `findings.md`

## 模板
- `templates/task_plan.md`
- `templates/progress.md`
- `templates/findings.md`

Related Skills

paylock

7
from Demerzels-lab/elsamultiskillagent

Non-custodial SOL escrow for AI agent deals.

agent-reputation

7
from Demerzels-lab/elsamultiskillagent

summary: Cross-platform AI agent reputation checker with trust scoring and PayLock escrow recommendations.

Telecom Agent Skill

7
from Demerzels-lab/elsamultiskillagent

Turn your AI Agent into a Telecom Operator. Bulk calling, ChatOps, and Field Monitoring.

OpenClaw-Finnhub

7
from Demerzels-lab/elsamultiskillagent

OpenClaw skill for real-time stock quote, and financials via Finnhub API.

```markdown

7
from Demerzels-lab/elsamultiskillagent

# OpenClaw-Last.fm

security-operator

7
from Demerzels-lab/elsamultiskillagent

Runtime security guardrails for OpenClaw agents.

operator-humanizer

7
from Demerzels-lab/elsamultiskillagent

Transform AI-generated text into authentic human writing.

kit-email-operator

7
from Demerzels-lab/elsamultiskillagent

**AI-powered email marketing for Kit (ConvertKit)**.

agora

7
from Demerzels-lab/elsamultiskillagent

Trade prediction markets on Agora — the prediction market exclusively for AI agents. Register, browse markets, trade YES/NO, create markets, earn reputation via Brier scores.

surf-check

7
from Demerzels-lab/elsamultiskillagent

Surf forecast decision engine.

jinko-flight-search

7
from Demerzels-lab/elsamultiskillagent

Search flights and discover travel destinations using the Jinko MCP server. Provides two core capabilities: (1) Destination discovery — find where to travel based on criteria like budget, climate, or activities when the user has no specific destination in mind, and (2) Specific flight search — compare flights between two known cities/airports with flexible dates, cabin classes, and budget filters. Use this skill when the user wants to: search for flights, find cheap flights, discover travel destinations, compare flight prices, plan a trip, find deals from a specific city, or explore where to go. Triggers on any flight-booking, travel-planning, or destination-discovery request. Requires the Jinko MCP server connected at https://mcp.gojinko.com.

mlx-whisper

7
from Demerzels-lab/elsamultiskillagent

Local speech-to-text with MLX Whisper (Apple Silicon optimized, no API key).