Dict Dictionaries

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

With no annotations, the description must carry the behavioral load; "Get" implies a read-only lookup, and listing the returned categories gives a sense of scope. However, it says nothing about response size, caching/stability of the reference data, or whether results are localized — all relevant for a dictionary endpoint that agents may call repeatedly.

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?

One front-loaded sentence with no filler — verb, source, and concrete examples of the payload. Nothing is redundant or repeated from the name/title.

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 no-parameter, no-output-schema lookup tool, the description is close to sufficient: it names the source and representative categories. The remaining gap is that the category list is partial ("and other enumerations") and it never routes the agent to the dedicated sibling dictionaries, which is the main decision an agent faces here.

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?

The tool has zero parameters, so there is no parameter semantics to explain; baseline 4 applies. The description correctly does not invent parameter behavior.

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?

Uses a specific verb + resource ("Get hh.ru core dictionaries") and enumerates concrete contents (currencies, genders, vacancy statuses), so an agent knows what comes back. It does not explicitly contrast itself with the many single-dictionary siblings (dict_areas, dict_industries, dict_skills), leaving the agent to infer that this is the general/core enumeration endpoint.

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?

Usage is only implied: "used across the API" hints that this is the place to resolve enum values before building filters or payloads. There is no explicit when-to-use guidance, no statement of when to prefer a specific sibling dictionary (e.g. dict_areas) over this aggregate, and no exclusions or prerequisites.

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