All 17 assistants can now read and write their Daedalus workspace. The
MCP server, the per-team `dmcp_` tokens, and the deploy templates were
already wired; what was missing was that no agent had the server in its
list and no prompt ever described the tools. Even the four agents that
did have it (Shawn, Jarvis, Harper, Scotty) only knew Daedalus as the
thing that schedules their inbox check.
Adds the tool docs (docs/tools/daedalus.md human reference,
prompts/tools/daedalus.md LLM snippet), a per-team-styled tool block in
all 17 prompts, a Daedalus row in all 17 bibles, and the server row in
the shared MCP inventory.
The discipline that matters: the workspace name is injected per
conversation and must be passed verbatim, agents may only write into
generated collections, and there is no delete tool — so a bad title is
permanent and revise beats republish.
Co-Authored-By: Claude Opus 5 (1M context) <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
- New docs/tools/athena.md documenting CRM capabilities and MCP tools
- Refactor docs/work/alan.md to separate system prompt from persona
reference
- Clarify Athena scope, vocabulary, and operational gotchas
- 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.
