Polish Academic MCP

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

With no annotations provided, the description carries the full burden and does well: it warns about potential large data size ('can be very large'), advises on performance optimization ('Prefer narrow...'), explains the purpose of 'since_modification_date' for incremental sync, and clarifies the 'with_generated' parameter. It lacks details on error handling or rate limits, but covers key behavioral aspects.

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?

The description is highly concise and well-structured: it starts with the core purpose, immediately provides critical usage tips, explains key parameters in context, and ends with a clear distinction from sibling tools. Every sentence adds value with zero waste.

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 tool with 6 parameters, no annotations, and no output schema, the description does well: it covers purpose, usage guidelines, and key behavioral traits. However, it lacks details on output format (e.g., structure of returned judgments) and error scenarios, which would be helpful given the complexity. It's mostly complete but has minor 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 the schema already documents all parameters. The description adds some context: it explains 'since_modification_date' as 'incremental sync' and 'with_generated' as 'include SAOS enrichment module fields,' but doesn't provide additional syntax or format details beyond the schema. This meets the baseline for high schema coverage.

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?

The description clearly states the tool's purpose: 'SAOS bulk dump of judgments (full records per row — can be very large).' It specifies the verb ('dump'), resource ('judgments'), and scope ('bulk' with 'full records per row'), distinguishing it from sibling tools like 'saos_search_judgments' by emphasizing it's for 'mirror/sync' rather than search.

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 provides explicit guidance on when to use this tool vs. alternatives: 'Prefer narrow judgment_start_date/judgment_end_date and page_size 10–20' for performance, and 'Not a replacement for saos_search_judgments (different use case: mirror/sync).' It also advises on incremental sync with 'since_modification_date' and includes context for 'with_generated'.

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