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

Annotations cover read-only and closed-world, but the description adds substantial behavior: default stack inclusion, newest-first default ordering, 'truncated' and 'skipped' semantics, the authority relationship to get_feedback counts, and crucially a prompt-injection warning that returned text is untrusted data. Far exceeds the annotation bar.

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 purpose, then behavior and safety notes in compact sentences. Slightly dense with several distinct ideas (pagination, stacks, ordering, truncation, injection warning) but every sentence earns its place.

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 read tool with no output schema, the description covers return ordering, stack defaults, truncation/skip semantics, authority vs. get_feedback, and the untrusted-data warning. Nothing an agent needs to call or interpret it correctly is missing.

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 parameters are already documented. The description still adds value: default ordering, the include_stacks cost tradeoff, and the subtle levels filtering rule that a level outside the five values is returned unfiltered but never matched. Goes beyond restating the schema.

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 states a specific verb+resource+scope: browser console entries captured for one Ybug feedback item. It distinguishes itself from the sibling get_feedback_network_requests and clarifies its relationship to get_feedback's approximate counts.

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?

Gives explicit when-to-use guidance for include_stacks ('scan a long log cheaply, then re-request the page you care about with stacks'), and explains the levels filter semantics including the subtle empty-filtered-page case. Does not name alternative tools for cross-log analysis, but context is clear.

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