Academic Writer MCP

Analyser le style d'écriture

analyze_writing_patterns

Read-onlyIdempotent

Detect repetitive sentence, paragraph, and transition patterns in French, Russian, or English documents to reveal stylistic uniformity and section-level style shifts.

Instructions

Indices stylistiques (fr/ru/en) : régularité des phrases, formules génériques, transitions systématiques, paragraphes uniformes, listes étiquetées, ruptures de style entre sections. Niveaux descriptifs non calibrés.

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": {
      "document_id": "<document_id>"
    },
    "name": "analyze_writing_patterns"
  }
}

Input Schema

Name	Required	Description	Default
`document_id`	Yes

Output Schema

Name	Required	Description	Default
`words`	Yes
`limits`	Yes
`language`	Yes
`segments`	Yes
`sentences`	Yes
`indicators`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Nov 9, 2026

TDQS

C2.7/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and closed-world scope, so the safety profile is covered by structured data. The description contributes one genuinely useful behavioral note: results are descriptive and not calibrated against thresholds, which tells the agent not to treat outputs as pass/fail verdicts. It says nothing about coverage limits, section-spanning behavior, or what happens with documents in unsupported languages.

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 a single compact sentence with the language scope front-loaded, which is efficient, but the comma-separated feature list reads as shorthand and the closing caveat 'Niveaux descriptifs non calibrés' is cryptic without elaboration. No sentence is wasted, but the density comes at the cost of readability.

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

Completeness3/5

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

An output schema exists, so return values need not be explained, and the annotations cover safety. Still, for an analysis tool the definition omits how the detected patterns are grouped or scored and provides no guidance on the undocumented document_id, leaving meaningful gaps for an agent deciding whether and how to call it.

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?

The single parameter document_id has 0% schema description coverage, so the description carries the full burden of explaining it, yet the description never mentions the parameter at all. It also does not state whether the document must be pre-extracted or in which formats an ID is valid, leaving the agent to guess what to pass.

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

Purpose3/5

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

The description enumerates the stylistic signals the tool surfaces (sentence regularity, generic formulas, systematic transitions, uniform paragraphs, labelled lists, style breaks between sections) and names a language scope (fr/ru/en), so the resource is inferable. However it never states an explicit verb or that it operates on a document, relying on the tool name to supply the action, and it does not distinguish itself from nearby siblings such as detect_ai_indicators or check_consistency.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no prerequisites, and no named alternative. The only hint, 'Niveaux descriptifs non calibrés', is a caveat about the nature of the output rather than a condition for selecting this tool over another analysis tool.

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

Deploy Server