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tool_seo_check

Analyze a markdown draft for CSDN SEO issues before publishing, checking title, keywords, headings, word count, code hints, alt text, and tags, and returning a 0-100 score with warnings.

Instructions

Analyze a draft markdown file for CSDN SEO issues before publishing.

Checks title length & keyword placement, summary, keyword density, H2/H3 hierarchy, word count, code-block language hints, image alt text, and tag count. Returns a 0-100 score with actionable warnings.

Args: file_path: Absolute path to the draft .md file.

Returns: dict with {ok, score, checks, fail_count, warn_count, suggestions, summary}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the burden and mostly discharges it: it discloses the full set of checks, that the result is a 0-100 score with warnings, and the response keys. It leaves implicit that the file is not modified (an agent could infer 'Analyze' is read-only, but it is not stated) and says nothing about error behavior on a missing/invalid path.

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?

Front-loaded purpose sentence, then a compact list of what is checked, then the return shape. Every sentence adds information and nothing is padded.

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?

No output schema exists, so spelling out the returned dict keys (ok, score, checks, fail_count, warn_count, suggestions, summary) is necessary and sufficient. Combined with the enumerated checks, an agent knows what it gets back and what the tool does.

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?

Schema coverage is 0%, so the description must compensate, and it does: file_path is qualified as an absolute path to a draft .md file, which is more than the schema's bare 'string'. No format examples or constraints beyond that.

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 (Analyze) plus resource (draft markdown file) and an explicit scope (CSDN SEO checks before publishing), then enumerates the exact checks performed. It is clearly distinguishable from write_blog/publish_csdn siblings because it is purely an assessment step.

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?

"before publishing" gives a clear trigger point in the workflow, positioning it relative to publish_csdn, and the enumerated checks imply when it is useful. It does not, however, name an alternative or state what to do if the score is low, so no explicit exclusions.

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