Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so safety needs no restating. Because no output schema exists, the description earns credit for disclosing the return payload (title, date, URL, category, summary); it omits ordering guarantees and the default result count, which live only in the schema.

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?

Two sentences, no waste, with the invocation trigger front-loaded ahead of the return description. The topic list is long but functional for intent matching.

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 two-optional-parameter read tool with full annotations and no output schema, the definition covers trigger, scope, return fields, and the optional category filter. Minor gaps are ordering and what happens when the category yields no matches.

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 coverage is 100%, so both parameters are already documented, including the default of 10 and the reference to list_categories for slugs. The description only adds that the category filter is optional and single-valued, which is marginal beyond the schema — baseline 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?

Names a specific resource (newest Emerge Times articles on AI agents, AGI, robotics, agent economy) and enumerates the returned fields, so the agent knows exactly what it gets. It does not explicitly distinguish itself from search_articles or get_article, leaving the recency-vs-query distinction to inference.

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?

"Use when the user wants recent news about..." is an explicit trigger tied to user intent, which is strong guidance. There are no when-not conditions or named alternatives (e.g., 'use search_articles for keyword queries'), so routing between siblings still requires inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.