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

Annotations already declare read-only, idempotent and closed-world behavior, so the safety profile is covered. The description adds that matching is semantic and that the response carries titles, URLs, dates and relevant passages, which is genuinely useful given no output schema exists. It says nothing about result ranking, coverage limits, or the effect of the 15-result cap.

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?

Three short sentences, with the corpus and purpose front-loaded and return contents last. Each sentence carries distinct information; only the parenthetical topic list is slightly expendable.

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 two-parameter search tool with no output schema, the description covers corpus, query mode and return shape, which is what an agent needs to invoke it correctly. The omission is the undocumented limit parameter and any note on ranking or result count.

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 50%: the query parameter is documented in the schema with an example, and the description reinforces that natural-language questions are accepted. The limit parameter is undocumented in both places, so its meaning and the default/max bounds are left to the raw schema. Baseline 3 applies.

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 (semantic search) and enumerates the corpus precisely: articles, trackers, reports and glossary on Asia's digital economy, with topic examples. This clearly separates it from siblings like get_latest_articles, get_glossary_term and get_tracker, which target single content types.

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?

The description signals the intended mode of use (natural-language questions, semantic matching) but never states when to choose this over get_latest_articles for recent news or get_glossary_term for a definition. Usage is implied rather than routed.

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