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Overview

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Tool Name

make_baby_bot

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Purpose

The make_baby_bot toolset lets you create, configure, deploy, and administer purpose-built data agents. Define instructions, select implementations, assign tools, manage permissions, and roll out bots to Slack or other environments.

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Key Features & Functions

Create Specialized Agents

Spin up new bots with clear instructions and a chosen model implementation.

Curate Tool Access

Grant or remove capabilities so each bot has only what it needs.

Deploy to Slack

Connect data agents to Slack with controlled access to users or channels.

Admin & Governance

List, monitor, update, and retire bots with auditable controls.

Evolve Implementations

Switch engines or providers as requirements change.
Name and scope each data agent narrowly. Fewer tools and focused instructions produce safer, more predictable behavior.

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Input Parameters for Each Function

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make_baby_bot

Parameters
NameDefinitionFormat
bot_idUnique id in the format bot_name-xxxxxx (6 letter code).String
bot_nameHuman friendly data agent name.String
bot_instructionsSystem instructions.String
bot_implementationEngine type, for example openai, cortex.String
available_toolsComma separated tool names to grant.String
activate_slackSet Y to enable Slack deployment, N to disable.String
slack_access_opentrue for open to all, false for allow list.Boolean
runner_idServer identifier for hosting (if applicable).String
confirmedExtra confirmation flag used only when prompted by the system.String

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get_available_tools

Parameters
NameDefinitionFormat
include_functionsInclude function details. Default false.Boolean

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_remove_bot

Parameters
NameDefinitionFormat
bot_idId of the agent to delete.String
confirmedExtra confirmation flag when requested.String
Removing a data agent is permanent. Back up instructions and configs before calling _remove_bot.

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_list_all_bots

Parameters
NameDefinitionFormat
with_instructionsInclude full instruction text. Default false.Boolean

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_deploy_to_slack

Parameters
NameDefinitionFormat
bot_idAgent id to deploy to Slack.String
Slack deployment requires a configured app, valid credentials, and any required org approvals.

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add_new_tools_to_bot

Parameters
NameDefinitionFormat
bot_idTarget agent id.String
new_toolsTool names to add.Array of strings

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remove_tools_from_bot

Parameters
NameDefinitionFormat
bot_idTarget agent id.String
remove_toolsTool names to remove.Array of strings

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update_bot_instructions

Parameters
NameDefinitionFormat
bot_idTarget agent id.String
new_instructionsReplacement instruction text.String

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update_app_level_key

Parameters
NameDefinitionFormat
bot_idTarget agent id.String
slack_app_level_keyNew Slack app level key.String

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_update_bot_implementation

Parameters
NameDefinitionFormat
bot_idTarget agent id.String
bot_implementationNew engine type, for example openai.String

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_modify_slack_allow_list

Parameters
NameDefinitionFormat
actionOne of LIST, GRANT, REVOKE, GRANT ALL, REVOKE ALL.String
bot_idTarget agent id.String
user_identifierSlack user id beginning with U (when applicable).String
user_nameFull name for user lookup (optional).String
Use Cases below are NOT limited to those and are only referenced as an example.

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Use Cases

  1. Data Engineering Agents
    Build and operate data pipelines with guardrails. Grant data_connector_tools, dbt_action, and git_action for model runs, schema checks, and versioned SQL changes. Example: An agent compiles and runs selected dbt models on demand, posts run results, and opens a PR with updated snapshots.
  2. Data Ops Agents
    Monitor jobs, surface incidents, and automate remediation steps. Combine genesis_job_tools, harvester_tools, jira_connector_tools, and slack_tools for alerting and ticketing. Example: On failed harvest or long-running warehouse jobs, the agent creates a Jira issue, posts context to Slack, and links logs.
  3. Business Analyst Agents
    Provide safe self-service analysis with read-only access. Use data_connector_tools for parameterized queries and export to Sheets via google_drive_tools. Example: An analyst asks for weekly revenue by segment; the agent runs a vetted query, returns a table, and publishes a refreshed Google Sheet.

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Workflow/How It Works

  1. Create a agent with a unique bot_id, instructions, implementation, and initial tools.
  2. Grant or remove tools as the scope sharpens.
  3. Deploy to Slack if collaboration is required.
  4. Control access with allow lists or open access.
  5. Iterate on instructions or switch implementations as needs evolve.
  6. Retire safely when the data agent is no longer needed.

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Integration Relevance

  • slack_tools for deployment and notifications.
  • project_manager_tools to align agents with missions and tasks.
  • data_connector_tools for data access in analytics and BI agents.
  • jira_connector_tools to create or update tickets from a agent.
  • file_manager_tools to capture outputs and attach artifacts.

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Configuration Details

  • bot_id must match name-xxxxxx where xxxxxx is 6 letters or digits.
  • Tool names must match get_available_tools exactly.
  • Choose the implementation based on model capability, latency, and cost.
  • Slack permissions should follow your org policy for user access and scopes.

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Limitations or Notes

  1. Deleting a data agent cannot be undone.
  2. Tool grants are validated and will fail for unknown tools.
  3. Slack deployment requires correct app configuration and workspace permissions.
  4. Switching implementations can change model behavior and token limits.
  5. Access control changes apply immediately and may interrupt active users.
  6. Network connectivity is required for external integrations.

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Output

  • Creation and updates
    Agent id, configuration summary, granted tools, and deployment status.
  • Listings Arrays of data agents with ids, names, status, and optional instructions.
  • Access control Current allow list entries and confirmations for grants or revokes.
  • Deployment Slack integration status and any required follow ups.
  • Errors Clear messages for invalid ids, missing permissions, or unsupported tools.