Raw capture — raw/intent-layer.md
url: https://www.railly.dev/blog/intent-layer/ date_fetched: 2026-07-05 backfilled: true
Today I’m releasing /intent-layer
npx skills add crafter-station/skills --skill intent-layer -g
Works with Claude Code, Codex, Cursor, Copilot, and 10+ more agents .
I’ve been using Claude Code daily for months. Same model, same prompts, completely different results depending on the repo.
On a large codebase I watched Claude:
Reasonable search. Wrong places. Bug still there.
Your best engineers don’t grep randomly. They have a mental map:
That map took years to build. Your agents don’t have it.
Context engineering is designing the full information an agent needs to perform reliably:
Intent Layer solves the first piece: system prompt infrastructure.
The skill helps you set up AGENTS.md files at folder boundaries. Simple markdown that gives agents the context they can’t get from code alone:
# Payment Service
## Purpose
Handles payment processing and settlement.
Does NOT own billing/invoicing (see billing-service).
## Contracts
- All processor calls go through src/clients/processor.ts
- Settlement config lives in ../platform-config/rules/
## Pitfalls
- src/legacy/ looks dead but handles pre-2023 accounts
- Test mode hits real sandbox. Charges appear then void.
Run /intent-layer on your project and it:
Run it again later to audit existing nodes or find new candidates as your codebase grows.
Same bug, with AGENTS.md in place:
npx skills add crafter-station/skills --skill intent-layer -g
Intent Layer is the first of several context engineering skills I’m building. More coming soon.
Built on The Intent Layer by Tyler Brandt. His AI Adoption Roadmap maps the stages most teams are stuck at. Start there for the full methodology.
Context engineering framework from DAIR.AI and LangChain .
Also related to my earlier AI-First Manifesto where I proposed LLMS.md files. Intent Layer is the evolved version of that idea.
Follow @RaillyHugo for more on context engineering.