Robert Helewka
fba4e4bb27
Canonical prompts had drifted from the deployed code. research gained a third
fan-out member (doc_lookup / mnemosyne) and its synthesizer was promoted from a
merge step into the researcher: it holds dolores and time, and escalates to a
real browser when a source comes back blocked, a URL looks guessed, or a
load-bearing claim needs a live check.
All three variants updated — personal, work, engineering — preserving each
team's memory framing and the personal variant's node-schema and Cypher
sections. The engineering variant was a near-stub; it now carries the same
structure as the others.
Dolores had no canonical prompt anywhere in koios despite running on all three
teams. Added prompts/{personal,work,engineering}/subagents/dolores.md from the
deployed instruction, unchanged — this closes a documentation gap rather than
altering her behaviour. Her prompt stays deliberately narrow: she is handed one
page and one question at a time, and browser tradecraft is what she is for.
docs/*/subagents.md gain a dolores entry with delegation guidance, including
the task-sizing rule that keeps callers from handing her multi-site errands.
Work's research Runtime line said "TBD, port to be assigned" — mentor's
research has been live on 24250 for some time.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
95 lines
5.3 KiB
Markdown
95 lines
5.3 KiB
Markdown
# Engineering Subagents
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The engineering leads (Harper, Scotty, CASE) delegate narrow, repeatable tasks to **subagents** — minimal-personality agents with a tight tool surface and a focused role. Subagents are called as tools, not addressed as collaborators. They don't own graph nodes and don't have character bibles.
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Subagents are runtime processes (defined under `kottos/agents/`), exposed as MCP tools via StreamableHTTP. The canonical prompt text lives in `prompts/engineering/subagents/` — copies in the runtime code should match.
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## Catalog
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### research
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**Purpose:** Answer a question by searching the public web, Robert's Neo4j memory, and the Mnemosyne document library in parallel — then judging what came back and verifying it against live pages where it matters.
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**Composition:** `fast.parallel` of four sub-agents:
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- `web_search` — argos; reports blocked/empty/JS-shell results rather than papering over them
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- `memory_lookup` — neo4j (read-only)
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- `doc_lookup` — mnemosyne (read-only); passes `library_type` when the domain is clear
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- `synthesizer` — the researcher: reads all three reports, escalates to **dolores** for a real browser when a source is blocked, a URL looks guessed, or a load-bearing claim needs a live check
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**Tools:** argos, neo4j_cypher, mnemosyne, dolores, time
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**When to delegate:**
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- A question where being wrong has a cost — the answer gets verified, not just retrieved
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- "What do I already know about X, and what's actually true about it now?"
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- Anything whose answer goes stale: prices, availability, dates, current status
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- When the lead wants memory-aware research without burning its own context
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**When NOT to delegate:**
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- Quick web lookups where memory isn't relevant — use Argos directly
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- Pure graph queries where the web isn't needed — query Neo4j directly
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- Operating a browser as the goal itself (a form, a flow, a screenshot) — use `dolores`
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**Prompt:** [prompts/engineering/subagents/research.md](../../prompts/engineering/subagents/research.md)
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**Runtime:** `kottos/agents/research.py` — port 24150
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---
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### dolores
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**Purpose:** Operate a real web browser. Dolores drives a headed Chromium on the RDP desktop host via Playwright — she reads live pages, fills forms, works through multi-step flows, and returns screenshots.
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**Composition:** single `fast.agent`.
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**Tools:** playwright
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**When to delegate:**
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- A task that genuinely requires a browser: a form to fill, a login flow, a multi-step navigation
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- A page Argos can't render — JS-heavy, client-rendered, cookie-walled
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- When the *visual itself* is the deliverable ("what does this page look like")
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**When NOT to delegate:**
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- Finding an answer — that's `research`, which will call Dolores itself when a source needs verifying
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- Anything the cached snippet already answers
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**Sizing the task:** one page and one question at a time. She has no view of the caller's goal, so a task spanning several sites — or one whose later steps depend on what earlier ones turn up — comes back thin or wrong. Chain the steps from the calling side instead.
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**Prompt:** [prompts/engineering/subagents/dolores.md](../../prompts/engineering/subagents/dolores.md)
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**Runtime:** `kottos/agents/dolores.py` — port 24153
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---
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### tech_research
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**Purpose:** Investigate technical questions — library comparisons, API docs, framework patterns, code examples. Returns structured analysis with options, trade-offs, code snippets, version notes, and cited recommendations.
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**Tools:** context7 (primary), github, argos (fallback)
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**When to delegate:**
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- "How does library X work?" / "What are my options for Y?" / "Which framework should I use for Z?"
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- Anything where the answer requires checking current documentation, real-world code, and possibly web research
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- Library version migration questions
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- API design comparison work
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**When NOT to delegate:**
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- General research where memory matters — use `research` instead
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- Quick documentation lookup on a known library — use Context7 directly
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- Code review of Robert's own code — leads handle that with their full context
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**Prompt:** [prompts/engineering/subagents/tech_research.md](../../prompts/engineering/subagents/tech_research.md)
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**Runtime:** `kottos/agents/tech_research.py` — port 24151
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---
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## Conventions
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**Source of truth:** koios is the master. The prompt text in `prompts/engineering/subagents/` is canonical; runtime `.py` files should load from or match these prompts. When iterating, edit koios first and propagate.
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**Personality:** Subagents have minimal personality. Their identity is their role: "you are a technical research specialist," not a named character. CASE was once cataloged here but was promoted to a lead agent in 2026-05 — see [case.md](case.md). The line: if the agent has a character, an inspiration, a domain it owns end-to-end, it's a lead; if it's a narrow utility called by other agents, it's a subagent.
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**Cross-team reuse:** A subagent may be useful to other teams (work, personal). The convention is **copy with tweaks** rather than share a single file — small per-team adjustments (different tool emphasis, different output format) are legitimate and the duplication is cheap.
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**Graph ownership:** Subagents do not own node types and generally do not write to the graph. If a subagent needs to persist something, it returns the proposed write to the calling agent and lets the lead persist it.
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