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Hispanic Legacy

by com.hispanic-legacy
OverviewDiscussionsAdmin

Latest verified Hispanic Legacy objects

get_latest
Read-onlyIdempotent

Most recently verified knowledge objects (freshness signal). Use this to judge how current the corpus is, or to see what changed since you last read it. It ranks by verification date and ignores your topic entirely — use search or get_topic when you want objects that are relevant rather than recent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many recently verified objects to return, newest verification first.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYes
resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedOutput schema / properties / results / items / properties / x
      Added value: +{
+  "additionalProperties": {
+    "additionalProperties": {},
+    "propertyNames": {
+      "type": "string"
+    },
+    "type": "object"
+  },
+  "description": "Indexed instance-specific attributes, grouped by namespace — the same fields api/index.json publishes. Absent when the instance declares none.",
+  "propertyNames": {
+    "type": "string"
+  },
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / properties / limit / description
      Added value: +"How many recently verified objects to return, newest verification first."
  3. First observed

TDQS

A4.5/5.0
Behavior4/5

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

The annotations already declare the tool read-only, idempotent, and non-destructive. The description adds valuable behavioral context beyond that: it ranks by verification date, serves as a freshness signal, and ignores topic relevance, which is a critical behavioral trait for agent selection.

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?

Two sentences with no wasted words. The primary purpose and freshness signal are front-loaded, followed by practical usage guidance and a clear pointer to alternatives.

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

Completeness5/5

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

For a simple tool with one optional parameter, full annotations, and an output schema, the description covers everything an agent needs to invoke it correctly. It explains purpose, ordering behavior, topic-agnostic behavior, and when to prefer sibling tools.

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?

The input schema fully documents the single optional limit parameter with its default, range, and meaning. The description adds no parameter-specific detail, but schema coverage is 100%, so this meets the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: it returns the most recently verified knowledge objects, ranked by verification date. It also explicitly distinguishes itself from topic-relevant tools by stating it ignores topic entirely.

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

Usage Guidelines5/5

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

The description clearly states when to use the tool: to judge corpus currency or see recent changes. It also gives explicit alternatives, telling the agent to use search or get_topic when relevance matters instead of recency.

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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