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hydra_probe

Mounts a website to discover and return typed, callable capabilities for AI agents, separating machine-usable APIs from browser-action fallbacks without execution.

Instructions

Mount a website for browser-as-probe discovery, then return direct machine-usable capabilities separately from browser-action fallbacks without executing a generated capability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNoOptional task context for probe route planning
targetYesURL or domain to probe
credentialsNoOptional scoped credentials for H6 Vault injection
Behavior3/5

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

No annotations are present, so the description carries the full burden. It discloses that the tool does not execute generated capabilities and returns separate capability structures, but it omits safety details like whether it modifies state or requires specific permissions.

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

Conciseness2/5

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

The description is a single, lengthy sentence (46 words) that tries to convey multiple concepts. It lacks breaks and prioritization, making it harder to parse quickly. A more structured format would improve scannability.

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

Completeness2/5

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

Given the complexity (nested objects, no output schema), the description fails to explain the return format or what 'browser-action fallbacks' and 'generated capability' mean. The agent would lack key contextual information to use the tool correctly.

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% and each parameter has a description in the schema. The tool description does not add additional meaning beyond what is already in the schema for 'goal', 'target', and 'credentials'.

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

Purpose3/5

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

The description states a specific action ('Mount a website for browser-as-probe discovery') and distinguishes the tool by mentioning returning capabilities separately from fallbacks. However, the phrasing is convoluted and may confuse agents due to dense terminology ('browser-action fallbacks', 'generated capability').

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

Usage Guidelines2/5

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

The description implies use for probing without executing, but it does not explicitly state when to use this tool versus siblings like 'hydra_execute' or 'hydra_mount'. No exclusions or alternative suggestions are provided.

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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