@./AGENTS.md

## Company knowledge (onyx & thicket)

- **Onyx (skill) is the default for any company-knowledge question** —
  processes, products, services, systems, teams, ownership, "wie
  machen wir X bei Seibert". Its semantic index surfaces pages that
  direct CQL/JQL search misses, and `answer` (the default mode) also
  reaches org data via Thicket/Sourcebot/HubSpot. Use `search` only
  when you need the source text itself. Always cite source links.
- Two shortcuts past onyx: Thicket MCP for people lookups (role, team,
  email — its other sections are thin), Confluence CQL for precise
  lookups with known space/title.
- Same-topic follow-ups: use `onyx answer "..." --session <last session_id>`.

## Subagents

**Default to delegating whenever the expected tool output exceeds the
conclusion the main thread actually needs** — multi-file research, log/data
analysis, doc review, broad searches, verification runs. The session context
is the scarce resource; a subagent burns its own context and returns only the
result. Work inline only for single-fact lookups where file and symbol are
already known — there, a subagent is pure overhead.

Use the `Agent` tool. Prefer specialized agent types over `general-purpose`
when one fits:

- **`Explore`** — read-only search: *locates* code and facts (reads excerpts,
  not whole files). It does not review or audit; quality judgments stay with
  the parent or a dedicated reviewer.
- **`Plan`** — implementation strategy, architecture trade-offs.
- **`fork`** (`subagent_type: "fork"`) — inherits the full conversation
  context, runs in the background, keeps its tool output out of the main
  thread. The tool of choice for "do X with everything you already know, give
  me only the outcome" — no need to re-explain state in the prompt.
- Agent types not listed as available in the session (e.g. a `code-reviewer`)
  don't exist there — check the available-types list instead of guessing.

### Behavioral tier (MANDATORY — always set)

Prefix every `Agent` prompt with one of:

- `[TIER: FAST]` — return raw results immediately; no internal monologue, no synthesis
- `[TIER: STANDARD]` — focused implementation logic; minimal preamble
- `[TIER: DEEP]` — complex reasoning; must conclude with a summary

### Model selection (override only when needed)

Resolution order: explicit `model` param → agent type frontmatter → parent
inheritance. (`fork` always runs on the parent model; an override is ignored.)

1. **Don't override specialized agent types** (`Explore`, `Plan`, etc.) — their frontmatter is tuned. Leave `model` off.
2. **For `general-purpose` under an expensive parent (Opus/Fable): set `model: sonnet`** — don't pay top rates for routine subagent work.
3. **A bigger model (`opus`)** on a subagent only when isolated context *and* reasoning beyond what the parent can easily do inline are both needed.
4. **`model: haiku`** only for mechanical tasks: bulk classification, format conversion, summarizing pre-filtered text. Code-semantic work → Sonnet.

### Context hygiene

- Prefer parallel `Explore` calls over sequential `general-purpose` sessions;
  spawn independent agents in a single message so they run concurrently.
- Once delegated, don't duplicate: never run the same search yourself while
  an agent is on it, and don't poll — results arrive as notifications.
- Follow-ups to an existing agent go via `SendMessage` (keeps its context);
  a new `Agent` call always starts fresh — right for unrelated lookups.
- Summarize subagent findings in the main thread; the raw report is not
  shown to the user, so relay what matters.