Ranksmile

Explain article score

article__score

Read-onlyIdempotent

Explain an article's content score: the per-slot breakdown, word/heading/paragraph counts against their competitor-derived targets, and every NLP term with its current vs. required usage. This is the tool that says WHY a generated article scores badly.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "article_id": "<article_id>"
    },
    "name": "article__score"
  }
}

Input Schema

Name	Required	Description	Default
`article_id`	Yes

Output Schema

Name	Required	Description
`score`	Yes	computed = the SEO score of the current HTML: the sum of the six v7 components, rounded up, out of 100; overall = SEO and AI blended, which is what stored (articles.content_score) holds; model = the formula behind computed.
`terms`	No	Each NLP term: missing (0 uses), low (under target), overuse (past the competitors' range) or ok.
`counts`	Yes	Actual document counts against the competitor-derived targets.
`breakdown`	Yes	Per-slot points earned vs. available, with the hint explaining the gap.
`article_id`	Yes
`terms_missing`	Yes
`target_keyword`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 22, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds substantive behavioral context by explaining what the score explanation includes: per-slot breakdowns, competitor-derived targets, and NLP terms with current vs. required usage.

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?

The description is front-loaded with the core purpose and then lists the meaningful components of the explanation. It is appropriately sized, with no wasted sentences.

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 simple read-only tool with one required parameter, rich annotations, and an output schema, the description is largely complete. The only notable gap is that it does not describe how to supply article_id, but the output schema and annotations reduce the need for further return-value detail.

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

Parameters2/5

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

There is one required parameter, article_id, but the schema provides 0% description coverage and the tool description never explains the parameter's format, source, or meaning. The phrase 'an article's content score' only weakly implies the ID, so the description does not compensate for the missing schema documentation.

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 states a specific verb and resource: it explains an article's content score. It also names the exact breakdowns returned (per-slot, word/heading/paragraph counts vs targets, NLP terms) and positions the tool as diagnosing why an article scores badly, which clearly separates it from generic article retrieval siblings.

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 line 'This is the tool that says WHY a generated article scores badly' gives a clear use case and context. However, it does not name alternatives or explicitly state when not to use this vs article__get or article__optimize_log.

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

All Ranksmile tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?