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Track Monitored Companies

track_monitored_companies

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesList of dicts, each with: - identifier: The company's display name (canonical) or a TLD-shape domain (e.g. "stripe.com") — REQUIRED - display_name: Human-readable company name (optional; falls back to identifier) - stage: 'active' (default) or 'removed' - data: Dict of company attributes — website, raw_input, etc. (optional)
agent_idYesID of the agent to add companies to
on_behalf_ofNoAn agency client's email, from list_agency_clients, to run this call in that client's account: their agents, settings, connected accounts, and credits. Omit it to act on your own account.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / on_behalf_of
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "An agency client's email, from list_agency_clients, to run this call in that client's account: their agents, settings, connected accounts, and credits. Omit it to act on your own account."
+}
  2. Changed3 schema fields changed
    • addedInput schema / properties / agent_id
      Added value: +{
+  "description": "ID of the agent to add companies to",
+  "type": "integer"
+}
    • removedInput schema / properties / task_id
      Removed value: -{
-  "description": "ID of the task to add companies to",
-  "type": "integer"
-}
    • changedInput schema / required
      Previous value: -[
-  "task_id",
-  "items"
-]New value: +[
+  "agent_id",
+  "items"
+]
  3. First observed

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare readOnlyHint=false and destructiveHint=false; the description adds real value beyond them by disclosing cross-agent dedup behavior, the nightly-sweep consumer of active rows, and that duplicates yield updated/skipped counts rather than fresh rows. It omits auth/credit requirements, but the mutation semantics are well covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short tagged sections, front-loaded with the summary and the key side effect. Slightly terse but every sentence carries weight; no redundancy against the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description compensates by sketching the return dict (created/updated/skipped counts plus skipped details), and parameters are fully documented in the schema. Only edge behavior on malformed identifiers or errors is left unspecified, which is a minor gap for a bulk-add tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents agent_id, items, the identifier/display_name/stage/data fields, and on_behalf_of. The description adds nothing about parameter syntax or formats, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Names a specific verb+resource ('bulk-add companies to an agent's monitoring list'), states the scoping behavior (cross-agent dedup), and explains the consequence (nightly sweep watches every active row). This clearly separates it from siblings like update_monitored_company and edit_monitor_members without needing to name them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It implies when to use it ('adding companies here turns monitoring on for the agent') but never states when to prefer it over query_monitored_companies, update_monitored_company, or edit_monitor_members, and gives no prerequisites or exclusions. Usage is inferable but not spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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