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

Annotations already carry the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), lowering the bar. The description adds real value beyond annotations by disclosing the behavioral trait that a human-readable page is published on brunosan.de and is included via published_url, plus the digest composition (stats, top-5 clusters). No rate limits or other constraints disclosed, but the output-context addition is meaningful.

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?

Well front-loaded: purpose in the first sentence, followed by use cases, example queries, then args/returns. The structure is logical and every section earns its place, though the Returns block is fairly detailed and the three example queries are somewhat redundant with the stated use cases. Slightly long but efficiently organized.

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?

Covers what, when, how to call (date param), and precisely what comes back (date, published_url, stats, top_clusters with nested fields). With annotations covering the safety profile and the description itself detailing the return shape, little is missing for a read-only digest tool. The sole notable gap is the unmentioned api_key parameter and no explicit rate-limit or freshness caveat.

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 Args section explains the date parameter ('Date YYYY-MM-DD, empty = latest available day') and reinforces the return semantics, though the schema already documents date identically. Notably, api_key is entirely absent from the description's Args section — an agent reading only the description wouldn't learn it's a required input. The description does add interpretive value via the Returns section mapping fields like stats and top_clusters.

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 opens with a precise specifier — 'Complete daily digest: all clusters, top articles, and statistics for one day' — naming both the resource (one day's AI news) and scope (clusters, articles, stats). It adds 'The full overview of a day's AI news' which clearly separates it from siblings like news_search, news_trending, and news_risk_radar without needing to open their schemas.

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 concrete usage context — 'ideal for morning briefings, newsletter preparation, or "summarize today's AI news"' — plus three illustrative example queries covering today, a past date, and a specific calendar day. This is clear context for when to invoke it, though it never names sibling alternatives or states when NOT to use it, lacking explicit exclusions.

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