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

With no annotations and no output schema, the description carries the full behavioral burden, and it does disclose the fixed cardinality (exactly 4 items), guaranteed source diversity, and that each item links to the original. It says nothing about freshness/timezone for "today", auth requirements, caching, or what happens when a source has no signal, which are real gaps for a daily-feed tool.

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 filler: the first front-loads what is returned and the second states the trigger. Every clause (source names, cardinality, original links) carries information an agent would otherwise have to guess.

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?

Because there is no output schema, the description must describe the return value, and it does so well (exactly 4 items, one per source, linked to originals). The only missing piece is how "today" is scoped temporally and how empty-source days are handled.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; schema coverage is 100% and the empty object is self-explanatory. Baseline 4 applies for a no-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 names a concrete resource (today's AI signals) and goes further by specifying the exact return contract: four items, one per named source, each linking to the original. That is enough to distinguish it from siblings such as archive_days, what_changed, top_models, and top_repos without opening any schema.

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 asks what's new in AI today" gives a clear triggering condition. It stops short of naming alternatives or exclusions (e.g. when to prefer archive_days for older dates or what_changed for diffs), so the agent must infer the boundary from sibling names alone.

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