companies-generate_summary
Generate a company summary
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| __requestBody | Yes | Request body |
Generate a company summary
| Name | Required | Description | Default |
|---|---|---|---|
| __requestBody | Yes | Request body |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false and destructiveHint=false, but the description adds no behavioral context such as whether the operation is asynchronous, consumes credits, or has rate limits. It simply repeats the action without disclosing side effects beyond what annotations already imply.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the core action and resource. It is appropriately brief for a simple tool with one parameter, though it sacrifices detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description is only minimally complete. It omits critical context about the nature of the summary output, whether it is synchronous, or how it relates to other enrichment and summary tools. This is a significant gap for an agent that needs to understand the tool's purpose and side effects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage with a clear description for the 'domain' parameter, so the baseline is 3. The description itself adds no parameter-related information, but it does not need to because the schema is sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('generate') on a resource ('company summary'), which clarifies the basic purpose. However, it does not define what a company summary contains, and it does not distinguish this tool from siblings like companies-list_summaries or signal_summaries-generate, leaving ambiguity about the output type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It lacks any mention of prerequisites, scenarios, exclusions, or differentiation from adjacent tools, so an agent receives no help with selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping purposes, such as signals-firmographics vs companies-enrich_firmographics, findEmail vs contacts-enrich_work_email, and monitors vs signal_subscriptions vs market_signals. While descriptions add some context, an agent could easily select the wrong tool due to the high similarity in function.
Most tools use a resource_subresource-action pattern, but there are inconsistent separators: underscores within some names, hyphens in others (e.g., scoring-assignment-bulk-create), and several camelCase exceptions (findEmail, findEmailBatchGet, getContactResearchByExternalID). This mixed convention makes the tool set feel unpredictable.
With 119 tools, this server vastly exceeds the typical well-scoped range. Even for a comprehensive B2B data platform, the sheer number creates cognitive overload and increases the risk of incorrect tool selection.
The server covers an extensive range of operations: enrichment, lists, contacts, signals, subscriptions, monitors, and scoring. Nearly every resource has create, read, update, and delete or lifecycle equivalents, leaving very few practical gaps for the intended use case.