fpf:actualize

neolabhq/context-engineering-kit · updated Apr 8, 2026

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$npx skills add https://github.com/neolabhq/context-engineering-kit --skill fpf:actualize
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summary

This command is a core part of maintaining a living assurance case. It keeps your FPF knowledge base (.fpf/) in sync with the evolving reality of your project's codebase.

skill.md

Actualize Knowledge Base

This command is a core part of maintaining a living assurance case. It keeps your FPF knowledge base (.fpf/) in sync with the evolving reality of your project's codebase.

The command performs a three-part audit against recent git changes to surface potential context drift, stale evidence, and outdated decisions. This aligns with the Observe phase of the FPF Canonical Evolution Loop (B.4) and helps manage Epistemic Debt (B.3.4).

Action (Run-Time)

Step 1: Check Git Changes

Run git commands to identify changes since last actualization:

# Get current commit hash
git rev-parse HEAD

# Check for changes since last known baseline
# (Read .fpf/.baseline file if it exists, otherwise use initial commit)
git diff --name-only <baseline_commit> HEAD

# List all changed files
git diff --stat <baseline_commit> HEAD

Step 2: Analyze Report for Context Drift

  1. Review changed files for core project configuration:

    • package.json, go.mod, Cargo.toml, requirements.txt
    • Dockerfile, docker-compose.yml
    • .env.example, config files
  2. If configuration files changed:

    • Re-read project structure (README, config files)
    • Compare detected context with .fpf/context.md
    • Present diff to user
  3. Ask user if they want to update context.md

Step 3: Analyze Report for Evidence Staleness (Epistemic Debt)

  1. Read all evidence files in .fpf/evidence/
  2. Check carrier_ref field in each evidence file
  3. Cross-reference with changed files from git diff
  4. If a referenced file changed:
    • Flag the evidence as STALE
    • Note which hypothesis is affected

Step 4: Analyze Report for Decision Relevance

  1. Read all DRR files in .fpf/decisions/
  2. Trace back to source evidence and hypothesis files
  3. If foundational files changed:
    • Flag the DRR as POTENTIALLY OUTDATED

Step 5: Update Baseline

Create/update .fpf/.baseline file:

# FPF Actualization Baseline
# Last actualized: 2025-01-15T16:00:00Z
commit: abc123def456

Step 6: Present Findings

Output a structured report:

## Actualization Report

**Baseline**: abc123 (2025-01-10)
**Current**: def456 (2025-01-15)
**Files Changed**: 42

### Context Drift

The following configuration files have changed:
- package.json (+5 dependencies)
- Dockerfile (base image updated)

**Action Required**: Review and update `.fpf/context.md` if constraints have changed.

### Stale Evidence (3 items)

| Evidence | Hypothesis | Changed File |
|----------|------------|--------------|
| ev-benchmark-api | api-optimization | src/api/handler.ts |
| ev-test-auth | auth-module | src/auth/login.ts |
| ev-perf-db | db-indexing | migrations/002.sql |

**Action Required**: Re-validate to refresh evidence for affected hypotheses.

### Decisions to Review (1 item)

| DRR | Affected By |
|-----|-------------|
| DRR-2025-01-10-api-design | src/api/handler.ts changed |

**Action Required**: Consider re-evaluating decision via `/fpf:propose-hypotheses`.

### Summary

- Context drift detected: YES
- Stale evidence: 3 items
- Decisions to review: 1 item

Run `/fpf:decay` for detailed freshness management.

File: .fpf/.baseline

Track the last actualization point:

# FPF Actualization Baseline
last_actualized: 2025-01-15T16:00:00Z
commit: abc123def456789
branch: main

When to Run

  • Before starting new work: Ensure knowledge base is current
  • After major changes: Sync evidence with code changes
  • Weekly maintenance: Part of regular hygiene
  • Before decisions: Ensure evidence is still valid
how to use fpf:actualize

How to use fpf:actualize 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 fpf:actualize
2

Execute installation command

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

$npx skills add https://github.com/neolabhq/context-engineering-kit --skill fpf:actualize

The skills CLI fetches fpf:actualize from GitHub repository neolabhq/context-engineering-kit 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/fpf:actualize

Reload or restart Cursor to activate fpf:actualize. Access the skill through slash commands (e.g., /fpf:actualize) 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

Submit your Claude Code skill and start earning

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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

4.828 reviews
  • Kiara Torres· Dec 24, 2024

    Useful defaults in fpf:actualize — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Amina Jain· Dec 12, 2024

    fpf:actualize is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Kabir Menon· Nov 23, 2024

    fpf:actualize has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Arya Jackson· Nov 15, 2024

    I recommend fpf:actualize for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Benjamin Jain· Nov 3, 2024

    fpf:actualize reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Amina Ghosh· Oct 22, 2024

    I recommend fpf:actualize for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Maya Rahman· Oct 14, 2024

    Keeps context tight: fpf:actualize is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Noah Sanchez· Oct 6, 2024

    fpf:actualize reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Rahul Santra· Sep 5, 2024

    Solid pick for teams standardizing on skills: fpf:actualize is focused, and the summary matches what you get after install.

  • Kofi Ghosh· Sep 1, 2024

    fpf:actualize fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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