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Get corpus stats

get_stats
Read-onlyIdempotent

Return corpus stats: total/free/premium counts, per-category counts, tag count, newest/oldest update dates, the 10 most recently updated resources, feed URLs — plus an editorial block (guide count, words, newest publish) merged at runtime from the static articles index. A small freshness/size signal to poll before deciding whether to re-ingest.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
totalYes
premiumYes
corpus_versionYes
newest_updatedYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "http://json-schema.org/draft-07/schema#",
      +  "additionalProperties": true,
      +  "properties": {
      +    "corpus_version": {
      +      "type": "string"
      +    },
      +    "newest_updated": {
      +      "type": "string"
      +    },
      +    "premium": {
      +      "type": "number"
      +    },
      +    "total": {
      +      "type": "number"
      +    }
      +  },
      +  "required": [
      +    "total",
      +    "premium",
      +    "corpus_version",
      +    "newest_updated"
      +  ],
      +  "type": "object"
      +}
  2. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is pre-covered. The description adds genuinely new behavioral context: the editorial block is 'merged at runtime from the static articles index' and the tool is cheap enough to 'poll'. It does not quantify cost or latency, but that is a minor gap given annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

It is front-loaded with 'Return corpus stats:' and stays to roughly two sentences, but the long enumerations of counts and dates substantially duplicate the output schema, which the agent already has. Those tokens are largely redundant, though the final freshness/polling sentence does earn its place.

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 zero-parameter read tool that already ships an output schema and rich annotations, this is essentially complete: it conveys nature, provenance of the merged editorial block, and intended use. The only loose end is the unexplained 'static articles index' merge, which hints at possible staleness without saying how fresh the data is.

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?

Zero parameters, so the baseline is 4 per the rubric. Nothing about argument semantics needs explaining, and the description correctly avoids inventing any.

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?

States a specific verb and resource ('Return corpus stats') and then enumerates exactly what the payload contains (counts, dates, recent resources, feed URLs, editorial block). This clearly separates it from content-returning siblings like get_corpus, get_full_corpus, and search_resources without the agent needing to open a schema.

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?

The closing clause gives a concrete usage context: 'a small freshness/size signal to poll before deciding whether to re-ingest.' That tells the agent when this tool is the right call. It stops short of naming explicit alternatives or when-not-to-use cases, so it is a strong 4 rather than a 5.

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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