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

Annotations already declare read-only/idempotent/non-destructive, and the description adds substantial behavior beyond them: quota cost of 1 per call, no quota charged when the service is temporarily down (count=0 + reason), ambiguous_law / law_not_found / section_format_unsupported handling, and the important caveat that an empty result is not evidence of no precedent (incomplete corpus, best-effort related_laws).

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?

Purpose and sibling routing are front-loaded, then results shape, then error/edge-case bullets — a sensible order with high information density. It is long and dense (nested parentheticals, multiple bullet groups), which costs some scannability, but nearly every line carries operational meaning.

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 an output schema being present, the description still spells out the result fields (no, year_be, verdict, department, doctitle), ordering (newest first), absence of full_text with a pointer to get_deka, and the verdict=None interpretation. Combined with the error-state taxonomy, an agent has everything needed to call and interpret results.

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; the description still adds value by tying parameter outcomes to behaviors — abbreviated law names, names with vs. without พ.ศ. producing ambiguous_law, and section formats that are accepted vs. rejected (วรรค/อนุมาตรา → section_format_unsupported). Most of this is echoed in the schema text, so it is enrichment rather than new semantics.

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?

Starts with a concrete verb+resource: a list of Supreme Court judgments citing a given section, and explains the retrieval mechanism (citation-reference table extracted from judgments, more precise than keyword search). It explicitly distinguishes itself from search_law, get_deka, and verify_citation, so an agent can route 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?

Gives explicit when-to-use ("use when you already know the law name + section"), explicit when-not with a named alternative ("don't know the section / want fact-based search → search_law(corpus=\"deka\")", "know the deka number → get_deka", "check whether a judgment actually cites it → verify_citation"). The routing decision is fully determined.

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