request_deep_diveAsk the next briefing to investigate a topic properly, with fresh web research: it will include a mini-dossier with sources. Use it whenever the person says "I want to know more about X" or "keep digging on this".
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The question or topic to research |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide idempotentHint=true, readOnlyHint=false, destructiveHint=false, giving a basic safety profile. The description adds behavioral context: the tool will produce 'a mini-dossier with sources' via 'fresh web research', which is not captured in annotations. It does not contradict annotations and provides useful additional detail. No discussion of rate limits or auth needs, but the tool is simple enough that this is acceptable.
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 two sentences, each earning its place. The first sentence states what the tool does and its output. The second sentence gives concrete usage scenarios. No filler or redundant information. Front-loaded and efficient.
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 tool's simplicity (one parameter, no output schema, annotations present), the description covers purpose, usage scenario, and output format. It is sufficiently complete for an agent to select and invoke the tool correctly. It could be slightly more explicit about the queuing nature (e.g., 'for the next briefing'), but it is implied. Score 4 reflects good completeness for a simple tool.
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% coverage for the single 'query' parameter with a description: 'The question or topic to research'. The tool description adds that the query will be used for 'fresh web research' and to produce a mini-dossier, but this is about the tool's overall behavior, not additional parameter constraints or formatting. Since the schema already documents the parameter fully, baseline 3 is appropriate.
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's purpose: 'Ask the next briefing to investigate a topic properly, with fresh web research: it will include a mini-dossier with sources.' This makes it immediately obvious that the tool queues a research task for a briefing. It distinguishes itself from siblings like 'list_deep_dives' (which lists results) and 'generate_briefing' (which generates a full briefing) by focusing on the deep-dive request mechanism.
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 explicit usage guidance: 'Use it whenever the person says
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.
Most tools target distinct operations (e.g., add_feed vs. remove_feed, get_source vs. list_sources). However, there is some ambiguity between correct_briefing and tune_topic (both adjust content based on user feedback) and between request_deep_dive and correct_briefing (both can trigger deeper investigation). The descriptions help, but an agent could misselect.
Tool names follow a very consistent verb_noun pattern (e.g., add_feed, create_source, generate_briefing, list_sources). All use snake_case with clear, descriptive verbs and nouns. No mixing of conventions.
With 27 tools, the server covers a rich domain of news feed management, briefing generation, and user preferences. This is slightly above the typical sweet spot but still reasonable given the complexity. Each tool serves a distinct purpose; the count is justified.
The tool set provides full lifecycle coverage: sources can be created, read, updated, and deleted; feeds and searches can be added and removed; briefings can be generated, listed, read, rated, and corrected; deep dives and read-later items are supported. There are no obvious gaps—the domain is thoroughly covered.