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Examples

This section provides practical examples for using SKF: Skill Forge.


Developer adds cognee to a Python project for AI memory management. Agent keeps hallucinating method signatures and config options.

@Ferris QS https://github.com/topoteretes/cognee

Ferris reads the repository, extracts the public API via source reading, validates against spec. Skill appears in skills/cognee/. Agent stops hallucinating. Forty-seven seconds. Done.

Alex’s team adopts BMAD for 10 microservices (TypeScript, Go, Rust).

@Ferris SF # Setup — Deep mode detected
@Ferris AN # Analyze — 10 services mapped
@Ferris CS --batch # Create — batch generation

10 individual skills + 1 platform stack skill. BMM architect navigates cross-service flows with verified knowledge.

Sarah prepares v3.0.0 with breaking changes.

@Ferris AS # Audit — finds 3 renames, 1 removal, 1 addition
@Ferris US # Update — preserves [MANUAL] sections, adds annotations
@Ferris TS # Test — verify completeness
@Ferris EX # Export — package for npm release

Ships with npm release. Consumers upgrade — their agents use the correct function names. Zero hallucination tickets.

Armel’s full-stack project: Next.js + Serwist + SpacetimeDB + better-auth.

@Ferris SS

Ferris detects 8 significant dependencies, finds 5 co-import integration points. Generates a consolidated stack skill. The agent now knows: “When you modify the auth flow, update the Serwist cache exclusion at src/sw.ts:L23.” Integration intelligence no other tool provides.


BMAD user starts a new project. BMM architect suggests skill generation after retrospective.

@Ferris BS # Brief — scope the skill
@Ferris CS # Create — compile from brief
@Ferris TS # Test — verify completeness
@Ferris EX # Export — inject into CLAUDE.md

Skills accumulate over sprints. Agent gets smarter every iteration.

Alex needs cross-service knowledge for 10 microservices.

One forge project, multiple QMD collections, hub-and-spoke skills with integration patterns.

Developer needs skills for a library that doesn’t have official skills.

@Ferris QS better-auth

Checks ecosystem first. If no official skill exists: generates from source. source_authority: community.

No source code available — only documentation.

Generate from docs + QMD-indexed content. T2/T3 confidence only. source_authority: community.


Start with Quick mode (no setup required), upgrade to Forge (install ast-grep), then Deep (install QMD). Each tier builds on the previous — you never lose capability.

Use --batch with create-skill and test-skill to process multiple skills at once. Progress is checkpointed — use --continue to resume if interrupted.

Stack skills focus on integration patterns. Individual skills focus on API surface. Use both together for maximum coverage.

After each sprint’s refactor, run @Ferris US to regenerate changed components. Export updates CLAUDE.md automatically. Skill generation becomes routine — like running tests.


“Forge halted: ast-grep not found” Install ast-grep to unlock Forge mode: https://ast-grep.github.io

“No brief found” Run @Ferris BS first to create a skill brief, or use @Ferris QS for brief-less generation.

“Ecosystem check: official skill exists” An official skill already exists for this package. Consider installing it with npx skills add instead of generating your own.

Quick mode skills have lower confidence Quick mode reads source without AST analysis. Install ast-grep to upgrade to Forge mode for structural truth (T1 confidence).


  • Run /bmad-help — analyzes your current state and suggests what to do next (e.g. /bmad-help my batch creation failed halfway, how do I resume?)
  • Run @Ferris SF to check your current tier and tool availability
  • Review forge-config.yaml for runtime configuration
  • Check module configuration in your BMAD settings