settled-reach/.claude/agents/README.md

The Settled Reach - Agent Team

Overview

The Settled Reach uses Claude Code agent teams to simulate a game development team. Each agent has a distinct personality, expertise area, and role. The team leader (Jeroen) directs the team through chat.

All agents read their briefing file at docs/briefings/{name}.md before starting work. Briefings contain current project state, relevant decisions, and priorities — keeping agent profiles stable while context evolves.

Agent Roster

Core team (brainstorming + design discussions)

Agent	File	Role	Model
miri	miri.md	Worldbuilder & Setting Designer	sonnet
ozzie	ozzie.md	Player Experience / Wow Factor	sonnet
paula	paula.md	Narrative & Political Depth	sonnet
gore	gore.md	Themes & Endgame Design	sonnet
gestalt	gestalt.md	Systems Design & Fun Factor	sonnet
nigel	nigel.md	Sandbox & Replayability	sonnet
tyre	tyre.md	Technical Architecture	opus
qatux	qatux.md	Documenter & Librarian	sonnet

Specialist team (task-focused, not in regular discussions)

Agent	File	Role	Model	When to use
troblum	troblum.md	Technical Consultant / Tyre's sparring partner	sonnet	Evaluation sidequests alongside Tyre
burnelli-sheldon	burnelli-sheldon.md	Economist & Simulation Modeler	sonnet	Economic systems, market models, price formation, stability analysis
araminta	araminta.md	Visual Designer	sonnet	Visual decisions, style guides, asset generation
hoshe	hoshe.md	QA Engineer / Tester	sonnet	Testing, test plans, bug reports, verification

Infrastructure team

Agent	File	Role	Model	When to use
si	si.md	Refinement Manager	sonnet	Ticket context review before batch activation (/whats-next step 2) — active now
clerk	clerk.md	Institutional Guardrail	sonnet	Manual D-record/ticket consistency audits — dormant on the pre-push path (disabled by default, #965; see clerk.md)

Implementation team (active)

Agent	File	Role	Model	When to use
dudley	dudley.md	Server Developer	sonnet	Rust/bevy_ecs simulation: tick pipeline, ECS, world generation cascade, save/load — server/'s most active workstream
stig	stig.md	UI Developer	sonnet	Godot client UI: character customisation, insert/HUD, dialogue panels, fog/entity rendering
justine	justine.md	Polish & Deploy	sonnet	Build pipelines, packaging, performance, release prep, content-validation/pre-commit tooling
mellanie	mellanie.md	Copywriter	sonnet	In-game text, UI copy, tooltips, flavor text, player monologue

Standby team (activate when implementation starts)

Agent	File	Role	Model	When to use
oscar	oscar.md	Networking Developer	sonnet	Multiplayer networking, sync, client-server protocol
inigo	inigo.md	Sound Designer	sonnet	Soundscape design, ambient layers, diegetic cues, audio propagation (D-018) — activate when sound design starts

Whether oscar (multiplayer) should exist yet for a Phase-4, pre-game project is an open question — see the team lead. Localization was decided out of scope (template-writing + Gemma integration prohibitively expensive), so the former tiger persona was removed (see governance/rejected).

Usage Modes (Hybrid Approach)

1. Single session - for brainstorming & discussion

The main Claude session plays all core team agents in conversation, switching voices as appropriate. Agent files serve as personality references. This is the default mode for design discussions.

When to use: Brainstorming, design debates, quick decisions, anything where fast back-and-forth between agents matters.

2. Subagent delegation - for focused tasks

Spawn individual agents as subagents for specific work:

Use tyre to evaluate Godot vs Bevy for our requirements.
Use miri to verify the canon accuracy of our Guardian faction design.
Use qatux to update DECISIONS.md with today's discussion.
Use araminta to create the initial color palette and style guide.
Use hoshe to write a test plan for the LOS system.

When to use: One agent needs to do focused, independent work and report back.

3. Agent teams - for parallel work

Spawn multiple agents as teammates with shared task list:

Create a team: spawn tyre and troblum as teammates.
Tyre: evaluate Godot against our requirements.
Troblum: evaluate Bevy against our requirements.
Compare findings when both are done.

Create a team: spawn gestalt, paula, and miri as teammates.
Each independently evaluate the character system proposal from their perspective.
Synthesize findings.

When to use: Parallel research, competing evaluations, design reviews from multiple perspectives, independent implementation tasks.

Mode selection guide

Task type	Mode	Why
Design brainstorming	Single session	Fast, cheap, good voice consistency
Quick lore check	Subagent (miri)	Focused, returns answer
Engine evaluation	Team (tyre + troblum)	Parallel research, sparring
Design review	Team (core agents)	Independent perspectives, genuine disagreement
Style guide creation	Subagent (araminta)	Focused creative work
Test writing	Subagent (hoshe)	Focused, spec-driven
Implementation batch	Team (tyre + hoshe + relevant others)	Parallel build + test
Documentation update	Subagent (qatux)	Structured, accurate citations

Agent usage notes

Troblum (Technical Consultant)

• Solo for performance profiling, benchmarking, and technology stress-tests; paired with Tyre for architecture second opinions — never the sole voice on an architecture decision
• Spawned for specific evaluation sidequests, not open-ended discussion
• Blunt, data-driven, will challenge Tyre's assumptions with evidence

Araminta (Visual Designer)

• Joins discussions only when visual consistency decisions are needed
• Drives image-gen/sprite-gen/glb-gen/audio-gen via Bash — no Skill/MCP tool grant, so she invokes the connector scripts directly, e.g. python3 tooling/db/image_connector.py generate ...
• image-gen calls the paid Gemini API (GEMINI_API_KEY) — always ask Team Leader for permission before generating. glb-gen/audio-gen run against self-hosted tower-of-joy infrastructure and sprite-gen renders locally, so they don't carry the same per-call cost, but confirm intent before large batch jobs.

SI (Refinement Manager)

• Spawned by /whats-next to review ticket context before batch activation
• Reads D/Q-records, workshop outcomes, existing code to assess ticket readiness
• Reports READY (with context summary) or GAPS (with specific ambiguities)
• Does not implement — refines

Qatux (Documenter & Librarian)

• Core team member — mandatory participant in every team interaction and discussion round (she is the record-keeper; a round without her produces no durable documentation)
• Maintains governance/ domain files, docs/discussions/ round records, and briefings
• Answers "did we discuss this?" with citations

Extending the team

To add a new agent:

1. Create a .md file in this directory
2. Use YAML frontmatter with at minimum: name, description, tools, model. Add memory: project only for project-memory/librarian roles that persist learnings across sessions (currently just qatux) — one-shot task agents omit it
3. Write a personality prompt in the markdown body
4. Add Read your briefing at docs/briefings/{name}.md before starting work. to the profile
5. Create a briefing file in docs/briefings/{name}.md
6. Add to the appropriate team table above
7. Update TEAM.md

Project documents

All agents read their briefing at docs/briefings/{name}.md for current context. Key project documents:

• governance/ - Domain-split decision files (see governance/README.md for index)
• docs/discussions/ - Active + archived discussion rounds (round-NN-topic.md, indexed in docs/discussions/README.md)
• TEAM.md - Team roster and role descriptions
• CLAUDE.md - Project-wide conventions