Exemple de codi de mapicgc-gl-js

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

No annotations, so the description carries the burden. It does add that examples are 'complet i funcional' and 'based on the real library API', which signals output quality, but says nothing about format/length of the returned snippet, whether it is read-only, or any limits.

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?

Two tight sentences, front-loaded with the return value, followed by the topic enumeration. Nothing redundant or padded.

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 one-parameter, no-output-schema tool the description covers what it returns conceptually, but leaves the shape of the response (snippet only? multiple files? framework version?) unspecified, which matters for a code-generation tool.

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% and the single 'topic' parameter is already documented with examples in the schema. The description's topic list partially duplicates that, adding a few extra valid values but no new syntax or constraints.

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: returns a complete, working code example for a given mapicgc-gl-js topic, and enumerates the topic space. It does not distinguish itself from siblings like get_started, get_api, or search_docs, so an agent must infer the 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?

Usage is only implied by 'per a un tema concret' — the agent can guess this is for copy-paste-ready samples rather than reference docs, but no explicit when-to-use or when-to-prefer-get_api/get_started is given despite obvious sibling overlap.

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