Persistent file-based planning system for organizing complex multi-step tasks and maintaining context across sessions.
Works with
Creates three markdown files (task_plan.md, findings.md, progress.md) in your project directory to serve as persistent working memory
Includes session recovery via script to sync context after /clear commands and resume interrupted work
Enforces structured workflows: plan first, update after each phase, log all errors, and never repeat failed actions
Provides temp
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionpi-planning-with-filesExecute the skills CLI command in your project's root directory to begin installation:
Fetches pi-planning-with-files from othmanadi/planning-with-files 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 pi-planning-with-files. Access via /pi-planning-with-files 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.
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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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Work like Manus: Use persistent markdown files as your "working memory on disk."
Before starting work, check for unsynced context from a previous session:
Note: The
scripts/directory is inside this skill's installation folder.
# Linux/macOS
python scripts/session-catchup.py "$(pwd)"
# Windows PowerShell
python scripts\session-catchup.py" (Get-Location)
If you cannot find the script:
Ask Pi to locate it for you:
Run the session-catchup.py script from the planning-with-files skill
If catchup report shows unsynced context:
git diff --stat to see actual code changestemplates/ inside this skill| Location | What Goes There |
|---|---|
| Skill directory | Templates, scripts, reference docs |
| Your project directory | task_plan.md, findings.md, progress.md |
Before ANY complex task:
task_plan.md — Use templates/task_plan.md as referencefindings.md — Use templates/findings.md as referenceprogress.md — Use templates/progress.md as referenceNote: Planning files go in your project root, not the skill installation folder.
Context Window = RAM (volatile, limited)
Filesystem = Disk (persistent, unlimited)
→ Anything important gets written to disk.
| File | Purpose | When to Update |
|---|---|---|
task_plan.md |
Phases, progress, decisions | After each phase |
findings.md |
Research, discoveries | After ANY discovery |
progress.md |
Session log, test results | Throughout session |
Never start a complex task without task_plan.md. Non-negotiable.
"After every 2 view/browser/search operations, IMMEDIATELY save key findings to text files."
This prevents visual/multimodal information from being lost.
Before major decisions, read the plan file. This keeps goals in your attention window.
After completing any phase:
in_progress → completeEvery error goes in the plan file. This builds knowledge and prevents repetition.
## Errors Encountered
| Error | Attempt | Resolution |
|-------|---------|------------|
| FileNotFoundError | 1 | Created default config |
| API timeout | 2 | Added retry logic |
if action_failed:
next_action != same_action
Track what you tried. Mutate the approach.
ATTEMPT 1: Diagnose & Fix
→ Read error carefully
→ Identify root cause
→ Apply targeted fix
ATTEMPT 2: Alternative Approach
→ Same error? Try different method
→ Different tool? Different library?
→ NEVER repeat exact same failing action
ATTEMPT 3: Broader Rethink
→ Question assumptions
→ Search for solutions
→ Consider updating the plan
AFTER 3 FAILURES: Escalate to User
→ Explain what you tried
→ Share the specific error
→ Ask for guidance
| Situation | Action | Reason |
|---|---|---|
| Just wrote a file | DON'T read | Content still in context |
| Viewed image/PDF | Write findings NOW | Multimodal → text before lost |
| Browser returned data | Write to file | Screenshots don't persist |
| Starting new phase | Read plan/findings | Re-orient if context stale |
| Error occurred | Read relevant file | Need current state to fix |
| Resuming after gap | Read all planning files | Recover state |
If you can answer these, your context management is solid:
| Question | Answer Source |
|---|---|
| Where am I? | Current phase in task_plan.md |
| Where am I going? | Remaining phases |
| What's the goal? | Goal statement in plan |
| What have I learned? | findings.md |
| What have I done? | progress.md |
Use for:
Skip for:
Copy these templates to start:
Helper scripts for automation:
scripts/init-session.sh — Initialize all planning filesscripts/check-complete.sh — Verify all phases completescripts/session-catchup.py — Recover context from previous session (v2.2.0)| Don't | Do Instead |
|---|---|
| Use TodoWrite for persistence | Create task_plan.md file |
| State goals once and forget | Re-read plan before decisions |
| Hide errors and retry silently | Log errors to plan file |
| Stuff everything in context | Store large content in files |
| Start executing immediately | Create plan file FIRST |
| Repeat failed actions | Track attempts, mutate approach |
| Create files in skill directory | Create files in your project |
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.
shadcn/improve
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
I recommend pi-planning-with-files for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: pi-planning-with-files is focused, and the summary matches what you get after install.
pi-planning-with-files is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
pi-planning-with-files is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: pi-planning-with-files is the kind of skill you can hand to a new teammate without a long onboarding doc.
pi-planning-with-files has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in pi-planning-with-files — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
pi-planning-with-files fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for pi-planning-with-files matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: pi-planning-with-files is focused, and the summary matches what you get after install.
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