PrusaMCP

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool 'enregistre' (records/stores) data and that it 'peuvent être partagées anonymement' (may be shared anonymously), which hints at data persistence and privacy considerations. However, it doesn't address critical behavioral aspects like authentication requirements, rate limits, whether the operation is idempotent, what happens on failure, or what confirmation/response to expect. For a data submission tool with 19 parameters, this is insufficient.

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 perfectly concise with two sentences that each earn their place. The first sentence states the core action and key parameters. The second sentence explains the value and data usage policy. No wasted words, front-loaded with the primary purpose, and appropriately sized for the tool's complexity.

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?

Given the high parameter count (19), no annotations, and no output schema, the description provides adequate basic context about what the tool does and why. However, it lacks sufficient behavioral transparency for a data submission tool, doesn't explain what happens after submission (success/failure responses), and offers minimal guidance on usage versus alternatives. The 100% schema coverage helps, but the description alone leaves gaps in operational understanding.

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 19 parameters thoroughly with descriptions, constraints, and defaults. The description adds minimal value beyond the schema by mentioning the four main scoring dimensions (quality, adhesion, strength, issues) and the purpose of data collection. However, it doesn't provide additional context about parameter relationships, formatting expectations, or usage patterns that aren't already in the schema descriptions.

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 with specific verbs ('Enregistre un retour après impression') and resources ('Note la qualité, l'adhésion, la solidité, et les problèmes rencontrés'). It distinguishes itself from siblings like 'export_feedback' or 'feedback_stats' by focusing on submission/recording rather than analysis or export. The description explicitly mentions what data is captured and the downstream benefits.

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 implies usage context ('après impression') but doesn't provide explicit guidance on when to use this tool versus alternatives. There's no mention of prerequisites, timing considerations, or comparison with sibling tools like 'diagnose_print' or 'upload_print'. The agent must infer usage from the purpose statement alone.

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