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Eve builds, alters, deploys, and monitors specialized data agents; manages missions & tasks; runs read-focused discovery/analysis; and coordinates artifacts, documentation, and collaboration across the platform.

Purpose

Orchestrate the lifecycle of data agents, manage missions/tasks, and coordinate safe data operations & collaboration.

Scope

Agent lifecycle, mission/task management, metadata discovery & safe queries, docs & artifacts indexing/exports/versioning, Slack/Sheets collaboration.

Design Goals

Deterministic & auditable operations, safety-first defaults for prod, reproducible & configurable workflows.
  • Create & activate a specialized data agent with a tailored tool set
  • Stand up a mission with tasks, dependencies, and cross-agent assignments
  • Run read-only data discovery and summarize findings with safe sampling
  • Index project documentation and answer grounded questions
  • Export deliverables to Sheets/files and notify stakeholders in Slack
    Start with a minimal tool set and expand only when a mission requires it.
Connections & access
  • Connected databases (e.g., Snowflake) with read permissions
  • Optional: Google Drive service account for Sheets/Docs
  • Slack activation and optional allow-list
  • Optional web search key (for web queries where allowed)
Workspace
  • Default schema: GENESIS_DATA_AGENTS.EVE_WORKSPACE
  • Default stage: GENESIS_DATA_AGENTS.EVE_WORKSPACE.MY_STAGE
  • Mission structure: clear objectives, tasks, owners, and dependencies
Keep access read-only by default. Promote to write only for workspace outputs and with explicit confirmation.
1

Data agent lifecycle management

Create a new agent with precise instructions & tool grants; activate on Slack (open or allow-listed); update instructions/tools as needs evolve.
2

Mission & task management

Create missions, define tasks, wire dependencies, assign agents; track status, attach artifacts, summarize outcomes; maintain an audit trail.
3

Data discovery & analysis

Enumerate db/schema/table metadata; run safe, read-focused queries with LIMITs & optional controlled sampling; write intermediate results to the workspace on request.
4

Documentation & artifacts

Index data dictionaries/ERDs/specs; answer grounded questions; export tables to CSV/XLSX/Sheets; persist outputs in file storage; version artifacts with git.
5

Collaboration & operations

Post progress in Slack, create review Sheets, attach files to missions/tasks; configure/monitor background jobs; coordinate specialized agents (field mapping, data quality, pipelines).
Every mission maintains status, history, and linked artifacts for traceability.
Planning checklist
  • Name & purpose: specialization + boundaries of responsibility
  • Instructions: concise, operational guidance (inputs, outputs, constraints)
  • Tool set: start minimal; add only what’s necessary
  • Slack access: open vs allow-listed; channels to operate in
Recommended tool grants (adjust as needed)

project_manager_tools, data_connector_tools, slack_tools, artifact_manager_tools, google_drive_tools, git_action, image_tools, web_access_tools, document_index_tools, file_manager_tools, delegate_work

Add snowflake_tools for warehouse queries; harvester_tools for metadata harvesting; manage_tests_tools for CI-style test orchestration.
Parameter confirmation (prior to creation)
  • Agent name & short description
  • Instructions text
  • Initial tool set
  • Slack activation: on/off, access policy
Post-creation steps
  • Validate instructions; run a quick capability check
  • Optionally deploy to Slack and set the access list
  • Document the agent in the docs site and link to the missions it supports
Keep a small validation suite (sample prompts/queries) to sanity-check each new or updated agent before enabling it broadly.
objectfields (examples)
Missionsid, name, status, target completion, history
Tasksid, name, status, dependencies, assigned agent, work logs
Workspace objectstables/views in GENESIS_DATA_AGENTS.EVE_WORKSPACE (on request)
Artifactsfiles (CSV/XLSX/JSON), downloadable links, git-tracked documents
Document indiceslist/search with grounding references
All outputs are auditable and linked back to missions/tasks for end-to-end lineage of work.
Typically used by Eve
Grant only the least privilege needed for the mission at hand. Review tool grants during post-mortems.
  • Read-first on production data; use LIMITs & narrow scans
  • Writes only to the workspace schema unless explicitly requested
  • Confirmation required before destructive/irreversible actions
  • Data minimization: mask PII/secrets; avoid external sharing without approval
  • Resource safeguards: avoid full scans/cross joins; stop if thresholds are exceeded
    Never execute DDL/DML on production without explicit human approval and change-control references.
  • Slack: activation, allow-list, channels
  • Databases: connections, harvest inclusions/exclusions, intervals
  • Workspaces: target schema/stage for outputs
  • Exports: default formats (CSV/XLSX/Sheets), naming conventions, storage locations
  • Web/Docs: SERPer key (optional), Drive service account JSON (optional)
    Store non-secret config in version control; keep secrets in a vault and reference them at runtime.
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