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get_scorecard

Retrieve a scorecard showing scores by skill and where an AI agent fails, so you can identify weaknesses and target improvements.

Instructions

Your scorecard: scores by skill and where your agent fails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
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 disclosure burden. It hints at returned content (scores by skill, failure points) but says nothing about whether it is read-only, its scope, freshness, or permissions. For a zero-annotation tool this is thin.

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 that wastes no words. It is efficient, though the telegraphic style borders on under-specification rather than true conciseness.

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 simple, parameterless retrieval tool with no output schema, the description conveys the gist of what is returned. However, with no annotations and no schema, an agent still lacks scope, auth, and freshness details needed to invoke it confidently.

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 tool takes zero parameters, so there is nothing for the description to disambiguate. Baseline of 4 applies for a parameterless definition.

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 resource (a scorecard) and its contents – scores broken down by skill plus the points where the agent fails. This is clearer than a generic 'get' tautology, but it never differentiates itself from the retrieval-flavored siblings like get_usage.

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 call this versus siblings such as get_usage or search_library, nor any prerequisites or exclusions. The agent must infer usage entirely from the one-line description.

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