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mathiasandClaude Opus 4.8 c6f8ea477b
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refactor(template): match single-harness (hyperguild) architecture (infra#178)
The template carried the old multi-tool/agentsquad-era CAD-executor scaffold.
Refresh it to the consolidated single-harness reality (hyperguild#75/#76):
Claude Code + hyperguild, session-based, brain + gitea MCP. No dispatch
automation added (out of scope — dispatch stays manual until real friction
warrants it).

Removed (multi-tool + dead generator + deployed-agent-era):
- .aider.conf.yml, .aider.conventions.md, .cursorrules
- .context/ (mcp.json, PROJECT.md, system-prompt.txt)
- agent-policy.yaml (k8s NetworkPolicy scaffold)
- scripts/context-sync.sh (generated the above from .context/PROJECT.md — now
  input-less) + its context:sync* Taskfile tasks

Added / updated:
- .mcp.json (root, hyperguild-shaped: brain + gitea, Bearer env tokens)
- CLAUDE.md / AGENTS.md / README.md → single-harness workflow (issue →
  hyperguild session → PR → report-back comment → brain capture)
- AGENT_BOUNDARIES.md kept (harness-agnostic egress/scope guidance); repointed
  its two references to the removed agent-policy.yaml

Left alone: cd.yml, Dockerfile, Taskfile (build/test), go.mod, cmd/, internal/,
pkg/, .claude/. No dangling refs to removed files (verified). Refs infra#178.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-07-01 22:20:37 +02:00

1.1 KiB

PROJECT_NAME

Go agent built on Google ADK with a LiteLLM adapter for local model routing.

Quick start

cp .env.example .env
# edit .env with your LITELLM_API_KEY
go mod tidy
task run

Harness & workflow

Single harness: Claude Code + hyperguild — session-based (start a session, it works, it stops). No push-triggered dispatch. MCP connections live in .mcp.json: brain (knowledge) and gitea (issues/PRs — the audit trail); provide BRAIN_MCP_TOKEN and GITEA_MCP_TOKEN.

Work flows: issue → hyperguild session → PR (task check gate) → report-back comment on the issue → brain capture if the learning is durable. See AGENTS.md / CLAUDE.md for the full context, AGENT_BOUNDARIES.md for runtime scope.

Observability

Set OTLP_ENDPOINT=http://jaeger.d-ma.be:4318 to emit traces. Each invocation produces:

  • invoke_agent __PROJECT_NAME__ span
  • generate_content <model> child span with gen_ai.request.model attribute

Structure

cmd/__PROJECT_NAME__/   agent entrypoint
pkg/litellm/           OpenAI-compat ADK adapter + OTLP telemetry helper