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run_goal

Execute complex multi-page crawling tasks by providing a natural-language goal. The agent autonomously plans, navigates, and extracts structured data.

Instructions

Execute a high-level crawl goal autonomously. The agent plans, navigates, and extracts data using its own LLM loop. Returns structured results when done. Use this for complex multi-page tasks; use individual tools (navigate, click, etc.) for fine-grained control.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
allowed_toolsNoRestrict which built-in tools the agent can use (optional)
goalYesNatural-language crawl goal
max_stepsNoMaximum agent steps (optional; default from settings)
modelNoModel to use (optional; uses default from credentials if omitted)
Behavior3/5

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

No annotations were provided, so the description carries full burden. It discloses autonomous behavior, LLM loop usage, and structured output, but lacks details on potential side effects like cost, rate limits, or that it may invoke other tools internally.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences: core action, how it works, usage guidance. No redundancy, every sentence adds value and is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (autonomous goal execution) and absence of an output schema, the description is fairly complete. It covers purpose, behavior, and usage context, though it could mention that the agent can be restricted via the allowed_tools parameter (already in schema). Minor omission.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for all parameters. The tool description does not add additional meaning beyond what the schema already provides, earning the baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it executes a high-level crawl goal autonomously, using an LLM loop to plan, navigate, and extract data. It contrasts itself from sibling tools like navigate, click, etc., making its unique purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states to use this for complex multi-page tasks and to use individual tools for fine-grained control. Provides clear context on when this tool is appropriate versus alternatives.

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

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