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

Beyond the read-only and idempotent annotations, it discloses the typical document length, windowing behavior, and the meanings of `char_count` and `has_more`. It also explains all three no-text conditions through `extract_status`, including that `empty` commonly means a scan without OCR.

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 description is compact and front-loaded with the tool's unique value, then moves logically into long-document navigation and extraction failures. Nearly every phrase supplies actionable information, with no generic filler.

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?

Despite having no output schema, the definition covers the distinctive returned fields, large-text navigation, continuation indicators, and reasons text may be unavailable. Together with the fully documented input schema, this provides enough context for correct selection and invocation.

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 already 100%, but the description adds useful operational context for `text_query`: starting at the beginning usually exposes front matter, so a query can target the desired passage. The remaining parameter mechanics are primarily handled by 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 identifies a single Supreme Court publication and its distinctive outputs: extracted text, `document_url`, cited case numbers, and linked ЄДРСР `edrsr_ids`. It also distinguishes the content as analytical reports rather than judgments and states that only this tool returns the linked identifiers.

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 gives practical retrieval guidance: use `text_query` to avoid opening a long report at its cover page and contents, and do not treat these publications as judgments. However, it does not explicitly direct agents to `ua_vs_digest__search` for discovery or name the appropriate judgment-retrieval alternative.

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