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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the tool performs a UI action ('Brings the tab to the front and makes it active'), which implies mutation/focus change. However, it doesn't mention potential side effects like browser window activation or what happens if the tab ID is invalid. The description adds meaningful context beyond basic functionality.

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 efficiently structured with three sentences: first states purpose and preference, second explains the behavioral effect, third provides usage guidance. Every sentence adds value, and it's front-loaded with the key action. No wasted words or redundancy.

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 moderate complexity (single parameter, no output schema, no annotations), the description is mostly complete. It covers purpose, usage, and behavioral context adequately. However, it lacks details on error conditions (e.g., invalid tab ID) and doesn't specify return values, which would be helpful since there's no output schema. It compensates well but has minor gaps.

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 the tabId parameter thoroughly. The description adds marginal value by reinforcing the source ('Extract the Tab ID from [Tab ID: 1234567890] in get_tabs output') and clarifying it's 'NOT the display number,' but doesn't provide additional syntax or format details beyond the schema. Baseline 3 is appropriate, but the extra clarification earns a slightly higher score.

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 specific action ('activate/focus'), the resource ('a specific tab in Google Chrome'), and the mechanism ('using its unique tab ID'). It distinguishes from siblings by specifying this is the 'PREFERRED METHOD' for activation by ID, differentiating from close_tab operations and get_tabs.

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?

Explicit guidance is provided on when to use this tool: 'PREFERRED METHOD: Activate (focus) a specific tab... using its unique tab ID' and 'Extract the Tab ID from [Tab ID: 1234567890] in get_tabs output.' This clearly indicates the prerequisite (get_tabs output) and distinguishes it from alternatives like close_tab operations.

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

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

With no annotations provided, the description carries full burden and excels at behavioral disclosure. It explains the HIGH RISK due to index shifting when tabs are reordered/closed, warns about targeting wrong windows, and explicitly labels it as 'LEGACY DANGER' and 'STRONGLY DEPRECATED' - providing crucial behavioral context beyond what parameters alone would indicate.

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 structured and concise: it starts with a warning emoji and 'LEGACY DANGER', states the purpose, explains the risk, provides deprecation guidance, and gives the specific condition for use. Every sentence earns its place with critical 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 2-parameter tool with no annotations and no output schema, the description provides complete context: purpose, risks, deprecation status, alternative tool, and specific usage condition. It compensates for the lack of structured safety annotations by explicitly warning about the dangerous behavior.

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?

With 100% schema description coverage, the baseline is 3. The description adds meaningful context by explaining why the parameters are dangerous ('HIGH RISK of closing wrong tabs due to index shifting'), which provides semantic understanding beyond the schema's technical descriptions of the parameters.

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 verb 'Close' and resource 'a specific tab using window/tab index', making the purpose explicit. It distinguishes from sibling tools by naming 'close_tab_by_id' as the preferred alternative, establishing clear differentiation.

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 explicit usage guidance: 'STRONGLY DEPRECATED: Use close_tab_by_id instead. Only use if Tab ID is unavailable.' This clearly states when not to use this tool and names the alternative, with a specific condition for when it might be appropriate.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively communicates key behavioral traits: the destructive nature ('Close'), the robustness ('IMMUNE to tab reordering, window changes, and index shifting'), and the specific data source requirement ('Extract the Tab ID from get_tabs output'). It doesn't mention error conditions or what happens if the tab doesn't exist.

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 front-loaded with the core purpose in the first sentence, followed by important behavioral context, then specific implementation guidance with a concrete example. Every sentence earns its place with no wasted words, and the structure flows logically from general to specific.

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 single-parameter destructive tool with no annotations and no output schema, the description does an excellent job covering purpose, usage context, parameter semantics, and key behavioral traits. The only minor gap is the lack of information about return values or error conditions, but given the tool's simplicity and the comprehensive parameter coverage, this is acceptable.

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?

With 100% schema description coverage, the baseline is 3. The description adds significant value by explaining where the tabId comes from ('Extract the Tab ID from [Tab ID: 1234567890] in get_tabs output'), providing a concrete example with format, and clarifying what it is NOT ('NOT the display number'). This goes well beyond what the schema provides.

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 specific action ('Close a specific tab'), resource ('in Google Chrome'), and mechanism ('using its unique tab ID'). It explicitly distinguishes this tool from its sibling 'close_tab' by emphasizing the ID-based approach and immunity to tab reordering.

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 explicit guidance on when to use this tool ('PREFERRED METHOD'), when not to use it (vs. index-based alternatives), and references the exact alternative sibling tool 'get_tabs' as the source for obtaining the required tab ID. It clearly establishes the prerequisite relationship with get_tabs.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context about the persistence of tab IDs and output format, but does not cover potential limitations such as browser state dependencies, error conditions, or performance implications. It adequately describes core behavior but lacks depth on operational constraints.

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 front-loaded with the core purpose, followed by essential details about tab IDs and output format. Every sentence earns its place by providing critical information without redundancy, making it efficiently structured 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 tool's low complexity (0 parameters, no output schema, no annotations), the description is largely complete. It covers purpose, output details, and usage guidance. However, it could slightly improve by mentioning any prerequisites (e.g., browser must be open) or error handling, which holds it back from a perfect score.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on output semantics, explaining the structure of tab data (display format and Tab ID) and usage guidance for the IDs. This adds value beyond the empty schema, warranting a score above the baseline of 3.

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 verb ('Get') and resource ('all open tabs from Google Chrome browser'), and distinguishes it from siblings by focusing on retrieval rather than activation or closure. It specifies the scope ('all open tabs') and key output details (unique tab IDs, display format).

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 for usage by emphasizing that Tab IDs should be used for reliable operations, which implicitly guides when to use this tool (to obtain IDs for sibling tools like activate_tab_by_id). However, it does not explicitly state when not to use it or name alternatives, keeping it from a perfect score.

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