Verification-driven task decomposition with Sibyl-native tracking. Mined from 200+ real planning sessions — the plans that actually survived contact with code.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionplanExecute the skills CLI command in your project's root directory to begin installation:
Fetches plan from hyperb1iss/hyperskills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate plan. Access via /plan in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Verification-driven task decomposition with Sibyl-native tracking. Mined from 200+ real planning sessions — the plans that actually survived contact with code.
Core insight: Plans fail when steps can't be verified. Decompose until every step has a concrete check. Track in Sibyl so plans survive context windows.
digraph planning {
rankdir=TB;
node [shape=box];
"1. SCOPE" [style=filled, fillcolor="#e8e8ff"];
"2. EXPLORE" [style=filled, fillcolor="#ffe8e8"];
"3. DECOMPOSE" [style=filled, fillcolor="#e8ffe8"];
"4. VERIFY & APPROVE" [style=filled, fillcolor="#fff8e0"];
"5. TRACK" [style=filled, fillcolor="#e8e8ff"];
"1. SCOPE" -> "2. EXPLORE";
"2. EXPLORE" -> "3. DECOMPOSE";
"3. DECOMPOSE" -> "4. VERIFY & APPROVE";
"4. VERIFY & APPROVE" -> "5. TRACK";
"4. VERIFY & APPROVE" -> "3. DECOMPOSE" [label="gaps found", style=dashed];
}
Bound the work before exploring it.
Search Sibyl for related tasks, decisions, prior plans:
sibyl search "<feature keywords>"
sibyl task list -s todo
Define success criteria — what does "done" look like?
Identify constraints:
Classify complexity:
| Scale | Description | Planning Depth |
|---|---|---|
| Quick fix | < 3 files, clear solution | Skip to implementation |
| Feature | 3-10 files, known patterns | Light plan (this skill) |
| Epic | 10+ files, new patterns | Full plan + orchestration |
| Redesign | Architecture change | Full plan + research first |
If this is a quick fix, stop planning and go build. Planning a 5-minute fix is waste.
Understand the codebase surface area before decomposing.
Map the impact surface — which files/modules will this touch?
Identify existing patterns:
Find the dependencies:
A mental model of the change surface:
"This touches: [module A] (new endpoint), [module B] (type changes), [module C] (tests). Pattern follows [existing feature X]. Depends on [infrastructure Y] being available."
Break work into verifiable steps. Every step must have a check.
A step without a verification method is not a step — it's a hope.
For each task, define:
| Field | Description |
|---|---|
| What | Specific implementation action |
| Files | Exact files to create/modify |
| Verify | How to confirm it works |
| Depends on | Which tasks must complete first |
| Method | When to Use |
|---|---|
typecheck |
Type changes, interface additions |
test |
Logic, edge cases, integrations |
lint |
Style, formatting, import order |
build |
Build system changes |
visual |
UI changes (screenshot or browser check) |
curl/httpie |
API endpoint changes |
manual |
Only when no automation exists |
## Task [N]: [Imperative title]
**Files:** `src/path/file.ts`, `tests/path/file.test.ts`
**Depends on:** Task [M]
**Parallel:** Yes/No (can run alongside Task [X])
### Implementation
[2-4 bullet points of what to do]
### Verify
- [ ] `pnpm typecheck` passes
- [ ] `pnpm test -- file.test.ts` passes
- [ ] [specific assertion about behavior]
Mark tasks that can run simultaneously for orchestration:
Wave 1 (foundation): Task 1, Task 2 [parallel]
Wave 2 (core): Task 3, Task 4 [parallel, depends on Wave 1]
Wave 3 (integration): Task 5 [sequential, depends on Wave 2]
Wave 4 (polish): Task 6, Task 7 [parallel, depends on Wave 3]
Review the plan before executing it.
Before presenting to the user, verify:
Show the plan as a structured list with waves:
## Plan: [Feature Name]
**Success criteria:** [measurable outcome]
**Estimated tasks:** [N] across [M] waves
**Parallelizable:** [X]% of tasks can run in parallel
### Wave 1: Foundation
- [ ] Task 1: [title] → verify: [method]
- [ ] Task 2: [title] → verify: [method]
### Wave 2: Core Implementation
- [ ] Task 3: [title] → verify: [method] (depends: 1)
- [ ] Task 4: [title] → verify: [method] (depends: 2)
### Wave 3: Integration
- [ ] Task 5: [title] → verify: [method] (depends: 3, 4)
After presenting, explicitly check:
Register the plan in Sibyl for persistence.
Create a Sibyl task for the feature:
sibyl task create --title "[Feature]" -d "[success criteria]" --complexity epic
Create sub-tasks for each plan step:
sibyl task create --title "Task 1: [title]" -e [epic-id] -d "[implementation + verify]"
Record the plan decision:
sibyl add "Plan: [feature]" "[N] tasks across [M] waves. Key decisions: [architectural choices]. Dependencies: [critical path]."
Plans change when they meet reality. When a task reveals unexpected complexity:
Once the plan is approved, hand off to the right tool:
| Situation | Handoff |
|---|---|
| 3-5 simple tasks, user present | Execute directly with verification gates |
| 5-15 tasks, mixed parallel | /hyperskills:orchestrate with wave strategy |
| Large epic, 15+ tasks | Orchestrate with Epic Parallel Build strategy |
| Needs more research first | /hyperskills:research before executing |
| Phase | Review Level | When |
|---|---|---|
| Full ceremony | Implement + spec review + code review | First 3-4 tasks |
| Standard | Implement + spec review | Tasks 5-8, patterns stabilized |
| Light | Implement + quick verify | Late tasks, established patterns |
This is earned confidence, not cutting corners.
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
hyperb1iss/hyperskills
mattpocock/skills
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
Useful defaults in plan — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
plan has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend plan for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in plan — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend plan for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: plan is focused, and the summary matches what you get after install.
We added plan from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
plan is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
plan reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: plan is focused, and the summary matches what you get after install.
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