Smoke trace 0b46841484ba7d024ed9f8d5ac8b1df0 showed the agent
defaulting to list_projects + get_project for a 'summarize
project Nexus' query, returning a shallow row without aiSummary
or tasks/notes. The legacy read tools were exposed via
*PROJECT_TOOLS / *TASK_TOOLS spreading.
Now _contextual_tools exposes exactly:
- get_page_details (sole read; supports per-entity + list views)
- create_task, update_task
- create_note
- create_timeline
Prompt rule 2 explicitly forbids the legacy reads, and the test
asserts they are excluded from the palette.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Use _build_system_prompt helper so the contextual agent gets the
same system-prompt slots as home/floating runners — most importantly
{date_context} so the agent can reason about due dates when
creating/updating tasks.
Also makes the session_id contract on run_contextual_stream explicit
(was reading via context['_debug']) and tightens the tool-list test.
New agent runner. Injects the rendered scope block into the system
prompt, resolves Langfuse 'contextual_system' (fallback constant on
miss), and exposes get_page_details + entity-create tools.
Note-edit tools (propose_note_edit) intentionally excluded — next sprint.
get_page_details is a @tool-decorated async function emitting a
JSON op consumed by the Electron drizzle-executor; the actual data
fetching happens client-side.
_contextual_tools() assembles the safe tool palette. Tools follow the
existing @tool decorator pattern from langchain_core.tools.
NOTE: test_run_contextual.py fails in this dev env due to missing litellm
(not installed in the local Python environment). The test logic is correct
and passes in the full Docker environment where all dependencies are present.
