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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds value beyond that by disclosing the return payload shape (latest reading, change, next release, source) and the effect of include_descriptions, though it says nothing about result volume or pagination for an unfiltered call.

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 front-loaded sentences: identify the tool, scope the coverage, then give filtering and disambiguation tactics. The long indicator enumeration earns its space by defining dataset boundaries and ends before it becomes a catalogue.

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?

Output schema exists, so return values need not be detailed, yet the description still summarizes them. With all three params documented in-schema and the discovery role stated, an agent has everything needed to call this correctly.

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 baseline is 3; the description earns above that by adding Polish/English search examples ('inflacja', 'wages') for the free-text query and a stated rationale for include_descriptions (disambiguating similar keys). The group enum values themselves are left to 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?

States a specific verb and resource ('Find indicators and their keys') scoped to Polish macroeconomic series, and the enumeration of covered topics makes the dataset boundary explicit. It does not name which sibling to use instead (e.g. get_macro_indicator for fetching a single series), so an agent must infer the discovery-vs-fetch split.

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 concrete usage conditions: filter by group or free text, and set include_descriptions specifically when keys look alike (cpi-rr vs hicp-rr). Missing an explicit exclusion such as 'use compare_macro_indicators instead when you need to contrast series', so it stops short of full routing guidance.

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