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

Annotations already declare read-only, open-world, non-destructive, non-idempotent behavior, so the safety profile is covered. The description adds genuinely new context: results are 'newest first' and sourced from public broadcasters and newspapers, and it enumerates the returned fields, which matters since no output schema exists.

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?

Front-loaded with the core purpose, then a 'Use when:' clause, then param enumeration and a concrete example call. Efficiently laid out, though restating the enum lists duplicates structured data and adds length without new information.

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 simple read-only list tool with rich annotations and no output schema, the description covers purpose, trigger conditions, valid topics/languages, and the return fields. Its main gap is the absence of any guidance separating it from the sibling news_search.

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 67%; the enum values for lang and topic are already fully documented in the schema, and the description largely repeats them rather than adding meaning. The 'results' parameter is undocumented in both places, and the example invocation is the only real addition. 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?

States a concrete verb and resource with scope: 'Today's latest news headlines from public broadcasters and newspapers, newest first.' That is far more specific than the title alone. It does not name or distinguish itself from the sibling news_search, so it stops short of a 5.

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?

It provides a 'Use when:' clause covering current events and 'latest headlines on a topic.' However, that trigger overlaps almost entirely with what a sibling named news_search would plausibly do, and the description never mentions news_search or any when-not condition, leaving the agent unable to discriminate between the two.

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

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

Annotations already declare this a safe, non-destructive, open-world read. The description adds genuinely new behavioral context: the ~1-2 day freshness window and the fact that sources are public broadcasters and newspapers. It says nothing about how results are ranked, whether the search is case-sensitive, or what the response looks like, but against annotations that carry the safety profile this is solid added context.

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?

Front-loaded with purpose, then scope, then a negative boundary, then a use-when clause and a concrete call example. Every sentence earns its place and nothing is padded.

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 three-parameter read tool with no output schema, the essential facts are present: what it searches, how fresh the data is, what sources, and how to call it. The one real gap is sibling disambiguation against news_headlines, which the description never addresses.

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 67%: lang and query are documented in the schema (including the important 'all must appear in the headline or excerpt' semantics), while results has no description at all. The description's example reinforces query/lang usage but adds no semantics for results or expansion of the lang enum. Baseline 3 is appropriate given the schema carries most of the load.

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?

States a specific verb (searches) and resource (latest news) and pins the scope tightly: roughly the last one or two days, from public broadcasters and newspapers, matching words like a name, place or event. The recency boundary ('Not an archive') sharply separates it from a general news database. It never explicitly distinguishes itself from the sibling news_headlines, which is the only missing piece.

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?

Provides an explicit trigger ('Use when: you need recent news about a specific subject') plus a negative boundary ('Not an archive'). What it lacks is a conditional route to the alternative – it never says to prefer news_headlines in some situation, leaving the agent to guess between the two siblings.

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