Forge Platform

Handbook

Forge micro-agent

A micro-agent is a bounded local-LLM run for a single judgment task (for example one AI UX ruleset rule on a harness fixture). It uses a micro-pack (fixed prompt + manifest), not full Cursor .cursor/rules/, and does not…

Definition

A micro-agent is a bounded local-LLM run for a single judgment task (for example one AI UX ruleset rule on a harness fixture). It uses a micro-pack (fixed prompt + manifest), not full Cursor .cursor/rules/, and does not use vector DB or MCP in MVP.

Components

Piece Owner Role
Micro-pack forgesdlc-kitchensink tools/forge-micro-agent/packs/<pack-id>/ — manifest.yaml, prompt.md, context-schema.json
Context assembly KS website-ux-auditor ux-assemble-context.mjs → context.json (audit slice + Playwright evidence)
Runner forge-workcells (private) Workcell local_llm_worker — LCDL chat, writes micro-agent.log + model output
Inference forge-lcdl LLM_* profile via read_profile_from_env_file
Contracts forge-platform AgentRun, WorkcellRequest, WorkcellResult (pattern); harness parses findings via existing JS

Context budget

Default 32K tokens per pack (max_context_tokens in manifest). Assemblers truncate audit JSON and cap screenshot/crop count.

Harness entry

# Cursor CLI (default when agent on PATH)
./invoke-ai-ruleset-harness.sh --only-rule AI.VISUAL.HIERARCHY

# Local LLM via forge-workcells
./invoke-ai-ruleset-harness.sh --only-rule AI.VISUAL.HIERARCHY \
  --llm --llm-env=/path/to/lcdl.env

Quota: gateway_probe_lcdl.py --env-file when --llm is set (not Cursor QUOTA_OK).

Cursor vs local LLM

Path Trigger Executor
Cursor Default; agent on PATH run-design-ai-rule.sh → Cursor CLI
Local LLM --llm / --llm-env= forge-workcells run --workcell local_llm_worker

Both paths feed parse-ai-agent-findings.mjs and expect-ai-rule-detection.sh.

Out of scope (MVP)

  • Full .mdc rule loader
  • Vector DB / RAG
  • MCP tool orchestration
  • Multi-rule local-LLM campaign (bootstrap stays --only-rule)
  • Replacing daily Cursor IDE use