Browser Automation Agent by Nova (CIVAI)

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 says nothing about whether this ends the turn, whether it mutates state, whether it should be combined with other tool calls, or what the reply consists of — significant gaps for a tool with zero structured behavioral coverage.

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?

A single tight sentence that front-loads the action and appends the trigger condition; nothing is wasted. It is efficient, though it is efficient at a fairly low level of detail.

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?

The tool is low-complexity (one optional param, no output schema), so the short description is defensible, but with no annotations and no output schema the description should at least clarify the conversational fallback's role in the turn lifecycle. It stops just short of that.

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?

There is one optional parameter (reply_hint) whose schema description already covers it at 100% coverage, so the baseline of 3 applies. The description adds no syntax, format, or influence guidance beyond what the schema already supplies.

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?

It gives a verb ('reply conversationally') and a trigger condition ('when the request is ambiguous or needs clarification'), which separates it from the calendar siblings by function. However, the 'resource' is nebulous — there is no statement of what the reply acts on or produces, so the agent must infer it is a non-action fallback.

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 names one condition for use: ambiguity or need for clarification. It implies, but never states, that the event-management siblings (add/update/delete/check events) are the alternative when the request is clear, leaving the when-not boundary to inference.

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?

No annotations are provided, so the description carries the full behavioral burden, and it discloses nothing: not the scope of the history (current session vs. all), pagination limits, or whether the read requires an active session. For a tool with zero annotation coverage this is a serious gap.

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?

It is short and front-loaded with the verb and resource, so there is no rambling. But the emoji and 'BrowserGPT Agent:' prefix consume space without conveying information, and brevity here reflects under-specification rather than efficient communication.

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?

With no annotations, no output schema, and a single vaguely-described parameter, the description leaves an agent unable to call this tool confidently or know what it returns. It should at minimum state the history scope and the relationship to the sibling tools.

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 reported at 100%, so the baseline of 3 applies per the rubric. The description adds nothing about the 'detail' parameter, but the schema is credited with documenting it.

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 phrase 'get session history' states a specific verb and resource, so the core purpose is inferable. However, it is prefixed with branding ('🤖 BrowserGPT Agent') that adds nothing, and it offers no distinction from siblings like converse, submit_task, or track_task. Meaningful but minimal.

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?

There is no indication of when to call this tool, what it retrieves history for, or how it relates to the sibling tools. An agent must guess whether this is a prerequisite for converse or a standalone lookup.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure, and it discloses nothing: no mutation semantics, no auth requirements, no side effects, no return behavior. 'Submit' implies a write action but nothing confirms what it affects or whether it is reversible.

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 short, but brevity here reflects under-specification rather than efficient conciseness. A single emoji-prefixed fragment earns no informational place and front-loads nothing an agent can act on.

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?

With no annotations, no output schema, and no usage or behavioral detail, the definition is completely inadequate for a task-submission tool that sits alongside related session and tracking tools. An agent has no basis for deciding to call it or predicting its effect.

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?

There is only one parameter and schema description coverage is 100%, so per the baseline rule the schema itself does the documenting work. The description adds no meaning about what 'detail' should contain, but the high coverage keeps this at the baseline rather than lower.

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 is essentially a restatement of the tool name: 'BrowserGPT Agent: submit task' adds no verb-object specificity beyond what 'submit_task' already conveys. It does not distinguish this from siblings like track_task or converse, so an agent cannot tell what submitting a task actually accomplishes.

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?

There is no statement of when to use this tool versus converse, track_task, or get_session_history. No preconditions, no alternatives, no context — the agent must guess from the name alone.

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?

No annotations are provided, so the description carries the full behavioral burden, and it discloses nothing: not whether tracking is a read or write, what state it changes, whether it requires an active session, or what it returns.

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?

Very short, but this is under-specification rather than conciseness — the single fragment carries no actionable content, and the emoji/agent prefix consumes space without earning it.

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 tool with no annotations, no output schema, and no meaningful description, an agent cannot determine purpose, safety profile, or expected result. The definition is inadequate for correct invocation.

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 there is only one optional parameter ('detail'), so the schema already documents the input; the description adds nothing beyond it. Baseline 3 applies when the schema does the heavy lifting.

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 is essentially a tautology: 'track task' restates the tool name track_task, prefixed with an emoji and 'BrowserGPT Agent.' It names no verb that clarifies behavior and gives no hint of what tracking entails or how it differs from siblings like submit_task or get_session_history.

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?

No guidance at all on when to use this tool, when not to, or which sibling (converse, get_session_history, submit_task) is the alternative. The agent is left entirely to inference.

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