browser_rename_tab

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

No annotations are provided, so the description carries the full burden. It discloses that the label affects how the LLM refers to the tab and appears in browser_list_tabs output, giving important behavioral context beyond the schema. It does not mention reversibility or permissions, but for a simple rename operation, this is adequate.

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 concise sentences, front-loaded with the action, and every word adds value. No fluff or repetition.

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 2-parameter tool with no output schema and no annotations, the description is complete. It explains the tool's purpose, the label's significance, and its effect on output. No additional details are necessary.

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%, so the baseline is 3. The description adds meaning by explaining that the label is 'human-readable' and used by the LLM and list output, clarifying the semantic purpose of the 'label' parameter beyond the schema's 'New label for the tab'.

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 action ('Set a human-readable label') and the resource ('a bound tab'). It distinguishes itself from sibling tools like browser_close_tab or browser_set_active_tab by focusing on labeling, and mentions the label's role in conversation and list output.

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?

Provides clear context on when to use this tool: when you want to assign a human-readable label to a tab for LLM reference and list output. It does not explicitly name alternatives or exclusions, but the context is sufficient for appropriate use.

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