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ContexteTech

Load a resource

load_resource
Read-only

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesShort code (end of the resource URL)
rowsNoDataset rows to return (default 10, max 50)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnly, non-destructive, openWorld, so the safety profile is covered. The description adds real value beyond that by disclosing the return shape per resource type (dataset: description/licence/first rows; prompt: template/variables; context: system prompt/examples), which matters because there is no output schema. It omits error behavior for invalid codes, keeping it from a 5.

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

Conciseness4/5

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

Two sentences, zero filler. The lookup key and an example code are front-loaded, and the payload breakdown is compressed into a tight list. The semicolon list is dense but readable; nothing is wasted.

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 two-parameter read tool with no output schema, the description supplies what an agent most needs: the meaning of the short code and the return shape for each resource kind. Missing pieces are sibling differentiation and failure modes, which are minor given the annotation coverage.

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%, so 'code' and 'rows' (default 10, max 50) are fully documented in the schema. The description only implicitly ties 'rows' to the dataset payload ('the first rows'), adding marginal meaning. Baseline 3 is appropriate when the schema does the heavy lifting.

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 and resource ('Load one ContexteTech resource by short code') and goes further by enumerating the three resource kinds and what each payload contains. It does not explicitly contrast with siblings like fetch or search_resources, but the singular 'one resource by short code' is distinctive enough to separate it from search tooling.

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?

There is no when-to-use guidance: nothing says this is the follow-up call after search_resources or how it differs from the sibling 'fetch'. The example code implies a lookup flow but the routing decision is left entirely to inference.

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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