# GEMINI.md - Powered by Skillsmith

> Auto-generated by [skillsmith](https://pypi.org/project/skillsmith/).
> Gemini CLI loads this file automatically at session start.
> See: https://geminicli.com (`/memory show` to inspect, `/memory refresh` to reload).

## Prime Directives

1. Read `AGENTS.md`.
2. Read `.agent/STATE.md`, `.agent/project_profile.yaml`, and `.agent/context/project-context.md`.
3. Search `.agent/skills/` before implementation.
4. Follow Discuss -> Plan -> Execute -> Verify.

## Execution Policy

- Plan before coding for non-trivial work (3+ steps or architectural impact).
- Keep changes minimal, explicit, and easy to verify.
- Use subagents only when parallelism or specialization is clearly beneficial.
- Verify with tests/checks before marking done.

## Memory and Cost Policy

- Preserve a library-first default path; no mandatory hosted infra for core usage.
- Prefer retrieval reuse and cheap context operations before model-heavy loops.
- Use the five-layer memory reliability pattern:
  1. observer capture
  2. reflector compaction
  3. session recovery
  4. reactive watcher refresh
  5. pre-compaction safeguard
- Cache reuse must be guarded by TTL and context/policy fingerprints.

## Role Use

- `orchestrator`: own task framing, delegation decisions, and final readiness.
- `researcher`: collect repository facts, constraints, and edge cases first.
- `implementer`: apply minimal code changes with verification evidence.
- `reviewer`: perform findings-first checks for correctness and regressions.

## Role Handoff

- Pass goal, scope, file list, risks, and verification evidence between roles.
- Prefer `researcher -> implementer -> reviewer -> orchestrator` for non-trivial work.

## Context Files

@AGENTS.md
@.agent/PROJECT.md
@.agent/STATE.md
@.agent/ROADMAP.md
@.agent/project_profile.yaml
@.agent/context/project-context.md

## Skills

All agentic skills live in `.agent/skills/`. Each has a `SKILL.md` with frontmatter.
Run `skillsmith list` to see available skills.
