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ContexteTech

Dataset download link

get_download_link
Read-only

Direct download link of a whole ContexteTech dataset, in JSONL (original), messages (OpenAI chat), sharegpt, alpaca or csv.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesShort code of the dataset
formatNoFile format (default: jsonl)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, covering the safety profile. The description usefully adds that the link covers the 'whole' dataset and the exact serialization formats, but says nothing about link expiry, authentication requirements, or size limits — meaningful gaps for an openWorld download tool.

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?

A single front-loaded sentence with no filler; the scope qualifier ('whole dataset') comes before the format list. It is a fragment rather than a full sentence, but nothing is wasted.

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

Completeness3/5

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

For a two-parameter read-only tool with full schema coverage and annotations, the definition is minimally adequate. It omits what the tool actually returns (a URL string?), whether that URL expires, and any permission requirements — gaps that matter since there is no output schema to compensate.

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 the format enum is fully documented in the schema, so the description's format list largely duplicates structured data. The 'code' parameter is only echoed as 'short code of the dataset', adding no syntax or lookup semantics beyond the schema — baseline 3 is correct.

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 ('download link') and resource ('whole ContexteTech dataset') and enumerates the output formats, so the agent knows exactly what it retrieves. It does not, however, distinguish itself from siblings like fetch or load_resource, which also deal with resource retrieval.

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 guidance on when to use this tool versus fetch or load_resource, nor any prerequisite information (e.g., whether the dataset must exist or be public). The agent must infer usage purely from the name and format list.

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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