get_accountAccount status: plan, whether the briefing is currently running, when the next one is due, how many sources and stories are in the system, and the AI cost accrued this month.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description provides a comprehensive list of the data fields returned (plan, briefing running, next due date, source/story counts, AI cost), which is behavioral transparency beyond the readOnlyHint annotation. The annotation already indicates a safe read operation, and the description adds value by detailing what is fetched. No contradictions.
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, well-structured sentence that lists all relevant data fields with commas and a conjunction. Every word adds value, and there is no redundancy or verbosity.
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 has no parameters, no output schema, and a simple read operation, the description is complete enough. It lists all likely return fields, and the sibling tools cover other capabilities. The only minor gap is that it does not mention the return format (e.g., JSON structure), but for a zero-param tool, this is acceptable.
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 no parameters, so the description does not need to add parameter meaning. The schema coverage is 100%, and the description compensates by explaining the output, which is the only relevant semantic aspect. A baseline of 4 is appropriate for a zero-parameter tool.
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 that the tool returns account status, including plan, briefing status, next due date, source and story counts, and AI cost. This is a specific verb-resource pairing ('get account') with a detailed breakdown of what is returned, distinguishing it from sibling tools that manage feeds, briefings, or sources.
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 used to check account-level information, and the sibling tools list includes many alternatives for specific actions (e.g., add_feed, generate_briefing), so the context helps differentiate. However, there is no explicit guidance on when to use this tool versus alternatives, nor any exclusions.
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.