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Load a resource

load_resource
Read-only

Fetch a ContexteTech dataset, prompt, or context by short code or author/name. Returns metadata, first rows, templates, variables, system prompts, or examples for fine-tuning and evaluation.

Instructions

Load one ContexteTech resource by short code (e.g. 'jr6t0n') or 'author/name'. Dataset: description, licence and the first rows; prompt: template and variables; context: system prompt and examples.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesShort code or author/name; 'code#v2' for a fixed version
rowsNoDataset rows to return (default 10, max 50)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so safety is covered. The description adds genuinely new behavioral context by describing what payload each resource type yields (dataset -> description/licence/first rows, prompt -> template/variables, context -> system prompt/examples), which goes beyond the annotations.

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?

Two dense sentences with no filler: the first gives the action and identifier forms, the second maps resource types to returned content. Everything is front-loaded and every clause carries information.

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?

With no output schema, the description correctly compensates by explaining the shape of returned data per resource type, and the two parameters are fully covered by the schema. It stops short of covering failure cases (invalid/expired code) or the effect of the rows cap, which is a minor gap for a read tool.

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 description coverage is 100%: both 'code' (including the 'code#v2' fixed-version syntax) and 'rows' (default 10, max 50) are fully documented in the schema. The description only restates the code formats, so it adds little beyond the structural fields — baseline 3.

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

Purpose4/5

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

States a specific verb (load) and resource (ContexteTech resource) plus the identifier forms accepted ('jr6t0n' or 'author/name'). It also enumerates what is returned for each resource type, which helps distinguish it from search_resources, though the sibling split is only implied rather than stated.

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

Usage Guidelines3/5

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

The description implies you already have a short code or author/name in hand, which suggests this follows a search, but it never says when to prefer this over search_resources or how to obtain a code. Usage is inferable but not spelled out.

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