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>
Match the mentor runtime tech_research prompt: cite sources with their URLs
(doc pages, repository links, web results) so the calling lead can follow
them. Applied to both the engineering and work copies per the copy-with-tweaks
convention.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- Add Quentin as work-team lead agent for solution architecture & demos,
with aws_sa repositioned as Quentin's exclusive subagent (tool, not peer)
- Add CASE as engineering lead agent for field/physical layer (LAN, hardware)
- Bump unified Neo4j schema to v2.4.0:
- Add Solution and Demo node types under Quentin's domain
- Update assistant ownership table with Quentin, CASE, and AWS SA scoping
- Update README and neo4j shared docs to reflect new team rosters and
subagent boundaries
- Introduced `neo4j-schema-init.py` for creating the foundational schema for the personal knowledge graph used by multiple AI assistants.
- Implemented functionality for creating constraints, indexes, and sample nodes, along with comprehensive testing of the schema.
- Added `neo4j-validate.py` to perform validation checks on the Neo4j knowledge graph, including constraints, indexes, sample nodes, relationships, and junk data detection.
- Enhanced logging for better traceability and debugging during schema initialization and validation processes.
