add_label

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

With no annotations, the description carries full burden, but it only states the action itself. It omits behavioral traits such as whether labels must pre-exist, whether existing labels are overwritten or appended, and permission requirements. This is comparable to the update_drive example, which scored 2 for a mutation tool with no annotations.

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 a single concise sentence with no filler, front-loading the verb and resource. It is appropriately sized for a simple tool.

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 tool's simplicity (4 params, no output schema, no annotations), the description is too sparse to fully equip an agent. It lacks guidance on prerequisites, idempotency, and error conditions, making it incomplete despite the accurate one-line summary.

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 only 25% (only 'labels' has a description). The description adds no parameter-level meaning beyond the action, and does not compensate for undocumented owner, repo, or issue_number. The labels parameter's schema description is helpful, but the overall parameter guidance is minimal.

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 uses specific verb 'add' and identifies the resource ('labels') and target ('issue or pull request'), clearly distinguishing from siblings like remove_label and add_issue_comment. No ambiguity about the operation.

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 clear context (issue or pull request) but does not mention when to prefer this over alternatives like remove_label or add_issue_comment. No exclusions or conditional usage are stated, leaving the agent to infer from the name and sibling list.

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