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

With no annotations, the description carries the full behavioral burden, yet it only states the output granularity and available filters. It omits that period_type and period_key are mandatory, says nothing about the simulated turnout/strategy inputs, error behavior, or defaults.

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?

A single tightly-written sentence with the resource and granularity front-loaded and no filler. Nothing extraneous, though the brevity comes partly at the cost of missing required-parameter context.

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 six-parameter tool with no annotations and no output schema, the description covers the return level and two filters but leaves the two required period parameters and the simulation inputs unexplained. Adequate but with clear gaps.

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 description coverage is 100%, so all six parameters are already documented in the schema; baseline is 3. The description echoes the voivodeship_code and district_number filters but adds no syntax or format detail beyond 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 (Zwraca) and resource (lokalne projekcje poparcia partii) plus the exact granularity (380 powiatów). This granularity implicitly distinguishes it from siblings like get_district_projections, get_voivodeship_projections, and get_national_projection, though it never names them.

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 mention of filtering by voivodeship code or district number implies when the tool is useful, but there is no explicit when-to-use/when-not-to-use guidance and no reference to the sibling projection tools an agent should choose between.

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