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HyperRouteAI

hyperroute-mcp

Official
by HyperRouteAI

fetch_result

Retrieve large result sets in bounded slices via slice, json_path, or search. Access complete server-side overflow data without missing information.

Instructions

Page through a LARGE result that execute spilled (its return carried overflow.ref). The full result is retained server-side and parsed in an isolated sandbox; you read it in bounded slices. ops: slice(offset,limit lines) for text · json_path(path=[key/index,…]) to pull a JSON node · search(query) to find text. Keep paging until you have what the task needs — an overflow is never missing data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opNoslice
refYes
pathNo
limitNo
queryNo
offsetNo
Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure. It reveals that the full result is retained server-side, parsed in an isolated sandbox, read in bounded slices, and that overflow never means missing data. It could add details like ref expiry or consistency guarantees, but the provided behavior is substantial and useful.

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?

The description is compact but information-dense. It front-loads the core purpose, then efficiently lists the three operations with their parameter usage, and closes with practical guidance. No filler or redundancy.

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?

For a moderately complex tool with no annotations and no output schema, the description covers the core workflow, operation modes, and safety/reassurance. It stops short of detailing result formats or edge cases, but the essential context for correct use is present.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It explains all meaningful parameters: `ref` comes from execute's overflow.ref, `op` supports slice/json_path/search, `offset`/`limit` control line slicing, `path` is a key/index list, and `query` is for search. This fully compensates for the bare schema.

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 the tool pages through a LARGE result spilled by `execute` via `overflow.ref`. It names a specific action ('Page through') and resource (result from execute), and distinguishes itself from sibling tools by directly referencing its predecessor `execute` and the overflow mechanism.

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

Usage Guidelines4/5

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

It explicitly says to use this when `execute` returns `overflow.ref`, and instructs to keep paging until the needed data is retrieved. It does not explicitly contrast with non-overflow cases, but the context makes the intended usage unmistakable.

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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