Update a signal template by creating a new version while preserving the template ID. Omitted fields keep their previous values.
| Name | Required | Description | Default |
|---|---|---|---|
| templateId | Yes | The unique identifier of the template to update | |
| __requestBody | Yes | Request body |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (which indicate mutation but no destructiveness), the description discloses key behaviors: a new version is created and the template ID is preserved. It also notes that omitted fields keep previous values, which is important for understanding state changes.
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, well-crafted sentence that communicates the core behavior and partial-update semantics without any filler. It is front-loaded with the action and resource.
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 rich input schema and the absence of an output schema, the description covers the essential behavioral context: versioning, ID preservation, and partial updates. It is sufficient for an agent to invoke the tool correctly, though it does not detail return values or potential 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?
Schema coverage is 100%, so parameters are already documented. The description adds meaningful semantic information: the `__requestBody` is partial-update oriented, where omitted fields retain previous values, clarifying how to use the request body effectively.
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 clearly states the tool updates a signal template, with the specific behavior of creating a new version while preserving the template ID. This distinguishes it from sibling tools like create (which would create a new ID) and delete.
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 implies when to use this tool: to update an existing template while keeping its ID, and that partial updates are allowed since omitted fields retain previous values. It doesn't explicitly name alternatives, but the context is clear and useful.
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.
