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.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionfpf:actualizeExecute the skills CLI command in your project's root directory to begin installation:
Fetches fpf:actualize from neolabhq/context-engineering-kit 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 fpf:actualize. Access via /fpf:actualize 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
0
total installs
0
this week
765
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
765
stars
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command performs a three-part audit against recent git changes to surface potential context drift, stale evidence, and outdated decisions.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).
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
Review changed files for core project configuration:
package.json, go.mod, Cargo.toml, requirements.txtDockerfile, docker-compose.yml.env.example, config filesIf configuration files changed:
.fpf/context.mdAsk user if they want to update context.md
.fpf/evidence/carrier_ref field in each evidence file.fpf/decisions/Create/update .fpf/.baseline file:
# FPF Actualization Baseline
# Last actualized: 2025-01-15T16:00:00Z
commit: abc123def456
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.
Track the last actualization point:
# FPF Actualization Baseline
last_actualized: 2025-01-15T16:00:00Z
commit: abc123def456789
branch: main
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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Useful defaults in fpf:actualize — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
fpf:actualize is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
fpf:actualize has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend fpf:actualize for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
fpf:actualize reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend fpf:actualize for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: fpf:actualize is the kind of skill you can hand to a new teammate without a long onboarding doc.
fpf:actualize reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: fpf:actualize is focused, and the summary matches what you get after install.
fpf:actualize fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
showing 1-10 of 28