Get latest signals
get_latest_signalsReturn the newest verified AI-agent ecosystem signals with source URLs, change types, and action items.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
get_latest_signalsReturn the newest verified AI-agent ecosystem signals with source URLs, change types, and action items.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral disclosure. It states that results are 'verified' and include 'source URLs, change types, and action items,' which tells the agent what to expect. However, it does not describe ordering beyond 'newest,' how the limit affects results, or any caveats about data freshness or access requirements.
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?
Single sentence, front-loaded with the action and object, and no filler. Every word contributes to understanding the tool's purpose and output.
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?
For a one-parameter tool, the description covers the core return value, but there is no output schema and no guidance about when to prefer this over similarly named siblings. The agent can call it correctly from name, schema, and description, but the description does not fully compensate for the missing return schema and usage context.
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, limit, has no description in the schema (0% schema description coverage), and the tool description never mentions it. While the name and min/max/default make its purpose inferable, the description adds no explicit connection between limit and the number of returned signals.
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 names a specific verb ('Return') and resource ('newest verified AI-agent ecosystem signals') and lists return fields ('source URLs, change types, and action items'), so an agent can tell this is a latest-signals list tool. It does not explicitly contrast with siblings like search_signals or get_signal, but 'newest' provides an implicit differentiator.
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 sentence says when to use this tool versus sibling tools such as search_signals, get_signal, or get_daily_briefing. The description only states what the tool returns, leaving the agent to infer that 'latest' is the selection criterion. There are no exclusions or alternative routing clues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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