signal_subscriptions-start
Start a signal subscription
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| subscriptionId | Yes | The unique identifier of the subscription to start |
Start a signal subscription
| Name | Required | Description | Default |
|---|---|---|---|
| subscriptionId | Yes | The unique identifier of the subscription to start |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare it as mutating, non-idempotent, and non-destructive, but the description adds no behavioral context. It doesn't explain what 'start' does (e.g., activates a paused subscription, begins delivery), what state changes occur, or whether it can be repeated. No annotation contradiction exists.
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 with no filler. It is efficient for the minimal information it provides, though it is under-specified from a completeness perspective.
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 a simple one-parameter schema, the description leaves critical ambiguity about subscription lifecycle and the difference from 'trigger' or 'resume'. Without this context, an agent cannot reliably choose this tool among many similar sibling operations.
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 only parameter 'subscriptionId' is fully described in the schema (100% coverage) with a clear definition. The description adds no additional semantic value, so the baseline of 3 applies.
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 'Start a signal subscription' uses a specific action verb and identifies the resource, distinguishing it from siblings like 'stop', 'trigger', and 'create'. It doesn't explicitly state that it operates on an existing subscription, but the required subscriptionId implies this.
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 provides no guidance on when to use this tool versus alternatives. It fails to mention prerequisites (e.g., subscription must exist) or contrast with 'signal_subscriptions-create' or 'signal_subscriptions-trigger'.
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.