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read_cvlac_detail

Read-only

Read the full CvLAC item page to see stored fields such as role, dates, institution, and financing omitted from list views. Find the item by label, case- and accent-insensitive.

Instructions

Read the full record page of one CvLAC item. The list views only show a couple of columns, so this is the only way to see the fields a write actually stored (role, dates, institution, financing). Finds the row by label, case- and accent-insensitive.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labelYesName/title as it appears in the section list, e.g. the degree for formacion
sectionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.6

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds matching semantics (finds the row by label, case- and accent-insensitive) and enumerates what is revealed (role, dates, institution, financing), 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.

Conciseness4/5

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

Three short sentences, front-loaded with the core purpose and the reason to prefer it over list views. No wasted filler, though the parenthetical field list is slightly list-heavy.

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 read-only detail tool with no output schema, the description conveys the return content and matching behavior. The main gap is lack of documented semantics for the section enum, which the schema leaves bare.

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 50%: label is described in the schema but section is only an enum. The description clarifies that section identifies the list and that label is the name/title as it appears there (e.g. degree for formacion), adding modest value but not fully compensating for the undocumented section values.

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: 'Read the full record page of one CvLAC item.' It distinguishes itself from the list views by contrast, though it doesn't name the sibling tool (read_cvlac) explicitly, leaving differentiation partly implicit.

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

Usage Guidelines4/5

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

Provides clear context for when to use it — to see the fields a write actually stored, since list views only show a couple of columns. No explicit when-not or named alternative, but the intended use case is unambiguous.

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