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get_context

Retrieve relevant personal information for any topic, including profile, projects, education, experience, or skills.

Instructions

Return relevant information for a given topic: profile, projects, education, experience, skills, or all.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'Return relevant information,' which implies a read operation, but it does not describe aggregation behavior, error handling for invalid topics, permissions, or any side effects.

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?

A single sentence that front-loads the action and immediately lists the acceptable topics. There is no filler, and every word contributes to understanding the tool's purpose.

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?

The tool is simple, has one required parameter, and an output schema exists, so basic invocation is covered. However, the absence of sibling differentiation and behavioral details leaves an agent uncertain about when to choose get_context over the individual getters or what happens with an unsupported topic.

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

Parameters4/5

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

The input schema only defines topic as a string with 0% description coverage. The description compensates by listing valid values: 'profile, projects, education, experience, skills, or all.' This adds meaningful semantics beyond the raw schema, though it omits the singular 'project' and does not formally declare an enum.

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?

The description uses a specific verb ('Return') and names the resource ('relevant information for a given topic'), then enumerates the accepted topics. It is clear enough to understand what the tool does, though it does not explicitly contrast itself with the sibling get_* tools.

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?

No guidance is provided on when to use this tool versus the individual sibling tools like get_profile, get_education, or get_experience. The phrase 'or all' hints at aggregation, but the description never states when a caller should prefer get_context over the more specific tools.

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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