market_signals-create_subscription
Create a market signal subscription to monitor job posts, LinkedIn posts, fundraising, investments, or IPOs
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| __requestBody | Yes | Request body |
Create a market signal subscription to monitor job posts, LinkedIn posts, fundraising, investments, or IPOs
| Name | Required | Description | Default |
|---|---|---|---|
| __requestBody | Yes | Request body |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false, idempotentHint=false, and destructiveHint=false. The description adds no additional behavioral context beyond what the annotations convey, such as side effects, duplicates, idempotency guarantees, or authentication requirements. The description is merely a purpose statement, so it fails to enrich the agent's understanding of the tool's behavior.
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, front-loaded sentence that efficiently conveys the core purpose without any extraneous information. Every word earns its place.
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?
Despite the tool's complexity (nested filters, multiple signal types, no output schema), the description only covers the high-level purpose. It does not mention that filters are supported, that the tool returns the created subscription, or that the schema contains detailed filter configurations. The agent would need to rely entirely on the schema, which is thorough but leaves out behavioral context. Completeness is insufficient for a tool with this complexity.
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 has 100% description coverage, so the baseline is 3. The description does not add any new meaning to the parameters; it only mentions the types of signals (which map to the 'type' enum) but ignores the nested filters, intervals, webhook URL, etc. No extra parameter semantics are provided.
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 action ('Create'), the resource ('market signal subscription'), and the specific purpose ('monitor job posts, LinkedIn posts, fundraising, investments, or IPOs'). It directly distinguishes from sibling tools like list, get, update, or delete subscriptions by focusing on the creation aspect and listing the monitored signal types.
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 the tool is for setting up new monitoring, but it does not explicitly contrast with alternatives like update_subscription, pause_subscription, or trigger_subscription. No guidance on when to use or not use this tool vs. others is provided, which is a moderate gap.
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.