Navigate an open session to a URL (SSRF-guarded). Returns url/status/title + any anti-bot challenge. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | the page to load (http/https) | |
| browser_id | Yes | from browse_open |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (non-read-only, non-idempotent, non-destructive), the description adds useful behavioral context: the tool is SSRF-guarded (security note) and may return an anti-bot challenge (indicating potential interaction requirements). It also mentions 'free' (cost implication). This adds value beyond the structured annotation fields.
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, well-structured sentence that efficiently conveys purpose, security consideration, output overview, and cost. Every part serves a purpose, with no extraneous words.
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 (navigate to URL) and absence of an output schema, the description adequately covers return values (url, status, title, anti-bot challenge) and mentions security (SSRF-guarded). It does not explain 'status' or how to handle challenges, but sibling tools like browse_solve_challenge fill that gap. Overall sufficient for a navigation 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?
Schema coverage is 100%, with both parameters (url, browser_id) already described in the input schema. The description adds no additional semantic meaning beyond what the schema provides (e.g., url description matches schema). Per guidelines, baseline 3 is correct.
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 (navigate), the resource (an open session to a URL), and key features (SSRF-guarded, returns url/status/title + anti-bot challenge). The verb 'navigate' is specific and the resource is well-defined, distinguishing it from sibling tools like browse_open (which opens a session) and browse_back (which goes back).
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 the need for an existing browser session via the 'browser_id' parameter, but does not explicitly state when to use this tool versus alternatives like browse_open, browse_back, or browse_click. No guidance on when not to use or prerequisites beyond having a browser session.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools serve similar purposes (e.g., web_read vs browse_read, web_discover vs browse_discover, research vs web_search + browse). Descriptions help differentiate, but the overlap is notable.
Most tools use a consistent verb_noun snake_case pattern (e.g., archive_message, browse_navigate). Minor deviations like standalone 'browse' and 'identity' are acceptable.
57 tools is very high for a single server, even with discover_tools. The broad domain coverage does not justify the count; it feels overloaded.
Covers identity, memory, browsing, human tasks, errands, messaging, and research comprehensively. Minor gaps might exist (e.g., no explicit agent-to-agent contract tools), but core workflows are well-supported.