pi-planning-with-files

othmanadi/planning-with-files · updated Apr 8, 2026

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$npx skills add https://github.com/othmanadi/planning-with-files --skill pi-planning-with-files
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summary

Persistent file-based planning system for organizing complex multi-step tasks and maintaining context across sessions.

  • 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
skill.md

Planning with Files

Work like Manus: Use persistent markdown files as your "working memory on disk."

FIRST: Check for Previous Session

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:

  1. Run git diff --stat to see actual code changes
  2. Read current planning files
  3. Update planning files based on catchup + git diff
  4. Then proceed with task

Important: Where Files Go

  • Templates are in templates/ inside this skill
  • Your planning files go in your project directory
Location What Goes There
Skill directory Templates, scripts, reference docs
Your project directory task_plan.md, findings.md, progress.md

Quick Start

Before ANY complex task:

  1. Create task_plan.md — Use templates/task_plan.md as reference
  2. Create findings.md — Use templates/findings.md as reference
  3. Create progress.md — Use templates/progress.md as reference
  4. Re-read plan before decisions — Refreshes goals in attention window
  5. Update after each phase — Mark complete, log errors

Note: Planning files go in your project root, not the skill installation folder.

The Core Pattern

Context Window = RAM (volatile, limited)
Filesystem = Disk (persistent, unlimited)

→ Anything important gets written to disk.

File Purposes

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

Critical Rules

1. Create Plan First

Never start a complex task without task_plan.md. Non-negotiable.

2. The 2-Action Rule

"After every 2 view/browser/search operations, IMMEDIATELY save key findings to text files."

This prevents visual/multimodal information from being lost.

3. Read Before Decide

Before major decisions, read the plan file. This keeps goals in your attention window.

4. Update After Act

After completing any phase:

  • Mark phase status: in_progresscomplete
  • Log any errors encountered
  • Note files created/modified

5. Log ALL Errors

Every 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 |

6. Never Repeat Failures

if action_failed:
    next_action != same_action

Track what you tried. Mutate the approach.

The 3-Strike Error Protocol

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

Read vs Write Decision Matrix

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

The 5-Question Reboot Test

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

When to Use This Pattern

Use for:

  • Multi-step tasks (3+ steps)
  • Research tasks
  • Building/creating projects
  • Tasks spanning many tool calls
  • Anything requiring organization

Skip for:

  • Simple questions
  • Single-file edits
  • Quick lookups

Templates

Copy these templates to start:

Scripts

Helper scripts for automation:

  • scripts/init-session.sh — Initialize all planning files
  • scripts/check-complete.sh — Verify all phases complete
  • scripts/session-catchup.py — Recover context from previous session (v2.2.0)

Advanced Topics

Anti-Patterns

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
how to use pi-planning-with-files

How to use pi-planning-with-files on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add pi-planning-with-files
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/othmanadi/planning-with-files --skill pi-planning-with-files

The skills CLI fetches pi-planning-with-files from GitHub repository othmanadi/planning-with-files and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/pi-planning-with-files

Reload or restart Cursor to activate pi-planning-with-files. Access the skill through slash commands (e.g., /pi-planning-with-files) or your agent's skill management interface.

Security & Verification Notice

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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

User Story & Requirements Generation

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

Competitive Analysis

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

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

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

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ 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.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.827 reviews
  • Sakura Thompson· Dec 28, 2024

    I recommend pi-planning-with-files for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Mia Thompson· Dec 16, 2024

    Solid pick for teams standardizing on skills: pi-planning-with-files is focused, and the summary matches what you get after install.

  • Pratham Ware· Dec 12, 2024

    pi-planning-with-files is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Hiroshi Chen· Nov 27, 2024

    pi-planning-with-files is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Camila Taylor· Nov 19, 2024

    Keeps context tight: pi-planning-with-files is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Ira Sanchez· Nov 7, 2024

    pi-planning-with-files has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ishan Gupta· Oct 26, 2024

    Useful defaults in pi-planning-with-files — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Hiroshi Wang· Oct 18, 2024

    pi-planning-with-files fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Camila Sethi· Oct 10, 2024

    Registry listing for pi-planning-with-files matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Noor Mensah· Sep 17, 2024

    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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