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

Annotations already cover readOnly/idempotent/non-destructive, but the description goes further with concrete operational facts: stateless edge call, 32 KB payload cap, 60 RPM limit, demo mode, L402 payment of 15 sats, and HTTP 400 on invalid input. This is real behavioral value beyond the annotations, though it doesn't describe response content or partial-failure behavior.

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 purpose and alternative routing are front-loaded, and the operational details are compressed into one sentence with no filler. It is dense and slightly technical, but each clause (limits, payment, error code) carries usable 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?

An output schema exists, so return-value detail is unnecessary; the description covers inputs, defaults, size/rate limits, payment requirements, and error signaling. For a stateless read-only call this is sufficient for an agent to invoke it correctly.

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 the baseline is 3, but the description adds extra meaning: it names text_or_headlines as the accepted input and supplies the default for sentiment_domain ('general_news'), which is not stated in the schema. It does not clarify entity_filter behavior, so it stops short of a 5.

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 (evaluates) applied to a concrete resource (sentiment across news headlines, discussions, articles) with an explicit output shape (bull/bear polarity scores). It also names the sibling it is not, so an agent can distinguish it from compile_competitive_landscape without opening either 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?

Explicitly gives use cases (market sentiment, social brand perception, controversy exposure on specific entities) and names the alternative tool plus the condition that selects it (competitive market comparisons). Nothing is left to inference.

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