signals.recommendations.watch
Start tracking a recommended company (converts it into a signal)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| recommendation_id | Yes | Recommendation id |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| meta | No |
Start tracking a recommended company (converts it into a signal)
| Name | Required | Description | Default |
|---|---|---|---|
| recommendation_id | Yes | Recommendation id |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| meta | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnlyHint=false, idempotentHint=false, and destructiveHint=false — marking it as a mutating, non-idempotent, non-destructive operation. The description adds the state-transition detail that a recommendation becomes a signal (openWorldHint=true, so effects likely extend beyond the return value). It does not disclose reversibility or side effects beyond the conversion, but it does add value over the annotations.
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 names the action, the target, and the resulting state with zero wasted words. It is not padded, though it is terse enough to omit usage guidance that would elevate it further.
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?
With one fully-documented parameter, an output schema, and annotation coverage, the tool is nearly complete. The main gap is the absence of usage/selection guidance relative to the signal-tracking sibling cluster, which prevents a higher score.
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 description coverage is 100% and the single parameter recommendation_id is straightforwardly documented ('Recommendation id'). The description adds no additional meaning beyond the schema, so the baseline of 3 applies — adequate but no extra value.
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 uses a specific verb-resource pair ('Start tracking a recommended company') and adds the conversion clause ('converts it into a signal') that clarifies what the action accomplishes beyond the bare verb 'watch'. It is clearly distinct from recommendation-related siblings like block/dismiss/restore, though it does not explicitly differentiate itself from the similarly-named signals.track sibling.
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?
No guidance is given on when to use this tool versus alternatives. With siblings signals.track, signals.untrack, signals.recommendations.block, and signals.recommendations.dismiss all nearby, the description provides no selection criteria or exclusions, leaving the agent to infer intent from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.