Moltline Creator Studio

Analyze Writing

analyze_writing

Read-onlyIdempotent

Analyze a draft for readability, passive voice, cliches, and hedging. FREE.

Also measures sentence variety and keyword density, and produces a prioritized fix list. Typical input {"text": ""} returns {"readability_grade": 9.2, "passive_voice_count": N, "cliches_found": [...], "hedging_words": [...], "sentence_count": N, "avg_words_per_sentence": N, "top_repeated_words": [...], "priority_fixes": ["..."]}.

Use on body prose to find readability and style problems. Not for ranking titles (headline_analyzer) and not for platform limits (social_length_check). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""} (for example {"error": "empty text"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`text`	Yes	The draft to analyze — at least one full sentence; plain text, any length.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.9/5.0

Behavior5/5

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

The description adds crucial behavioral details beyond readOnly and idempotent annotations: it never raises protocol errors but returns an error object, and includes sample output structure. This enriches the agent's understanding of expected behaviors.

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 well-structured with a clear purpose, example output, usage notes, and error handling, all in a compact form. Every sentence provides value, and key points are front-loaded.

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 single-parameter tool with full schema coverage and an output schema, the description is comprehensive: it covers usage, errors, retry safety, and sample output, leaving little ambiguity.

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?

The schema covers 100% of the parameter, and the description reiterates the typical input format and adds constraints like 'at least one full sentence' and 'plain text', which go beyond schema essentials.

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 clearly states the tool analyzes drafts for readability, passive voice, cliches, and hedging, and lists additional metrics. It distinguishes itself from siblings by explicitly noting it's not for titles or platform limits.

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?

It explicitly says to use on body prose and not for ranking titles or checking social length limits, naming alternatives (headline_analyzer, social_length_check). This is clear when-to-use and when-not-to-use guidance.

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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TDQS

A4.7/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: prose analysis, headline scoring, reading stats, platform length check, product listing, free/paid skill retrieval, and full product details. There is no ambiguity between any pair of tools, and descriptions explicitly note what not to use them for.

Naming Consistency5/5

All tool names use consistent snake_case verbs followed by nouns (e.g., analyze_writing, list_products, get_free_skill). Even reading_time and social_length_check follow the pattern, albeit with nouns first, but the style is uniform and predictable.

Tool Count5/5

With 8 tools, the server is well-scoped. It covers both content analysis (4 tools) and product catalog access (4 tools) without overloading or underrepresenting either domain. The number feels appropriate for a focused studio toolkit.

Completeness4/5

The tool set covers the core functions of a Creator Studio: writing analysis, headline optimization, reading time, social length checks, plus full product catalog introspection. Minor gaps like grammar checking or content generation exist but are outside the stated scope. The set has no dead ends for the intended workflows.

Resources

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