edgegate_get_huggingface_integration

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

The description discloses a key behavioral trait: 'Does not return the token itself,' which is valuable. However, with no annotations, it does not explicitly state this is a read-only operation or discuss permissions/side effects. It adds some context but is not comprehensive.

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 two concise sentences, front-loaded with the primary purpose and a useful caveat. No redundant information.

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 simple getter with one parameter and no output schema, the description covers the core behavior and a critical security aspect. It lacks return format or error scenarios, but these are not essential for this low-complexity 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?

The schema has one parameter, workspace_id, with no description. The description's reference to 'this workspace' ties the parameter to its meaning, adding minimal value. The parameter is self-explanatory, so a baseline of 3 is appropriate despite the low 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 specifies the exact action ('Show') and resource ('whether a personal HuggingFace token is connected to this workspace'), with additional status detail (active/disabled). This clearly distinguishes it from sibling tools like connect_huggingface or get_qaihub_integration.

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 this tool is for checking HuggingFace token connection status, but provides no explicit guidance on when to use it versus alternatives (e.g., before connecting, or instead of connect_huggingface). Context is clear but exclusions are absent.

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