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Moltline Creator Studio

by com.moltlinestudio

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
NameRequiredDescriptionDefault
textYesThe draft to analyze — at least one full sentence; plain text, any length.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description reinforces this ('Every call is read-only and idempotent') and adds critical context about error behavior: on invalid input it returns an error object rather than a protocol error, which is beyond what annotations cover.

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

Conciseness4/5

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

The description is somewhat long but well-structured with clear sections: what it does, typical input/output, usage guidance, error behavior. Every sentence adds value. Could be slightly more concise, but still efficient.

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?

Given the tool has only one parameter with full schema coverage and an output schema, the description fully covers the tool's purpose, usage, error behavior, and output format. It includes a representative output example and error handling details, leaving no gaps for an agent.

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

Parameters3/5

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

Schema coverage is 100% and the description echoes the schema requirement ('at least one full sentence; plain text, any length'). The description adds a typical input example, but this is a minor addition. Baseline 3 is appropriate as schema already explains the parameter well.

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 uses specific verbs and resources: 'Analyze a draft for readability, passive voice, cliches, and hedging.' It clearly distinguishes from siblings by stating 'Not for ranking titles (headline_analyzer) and not for platform limits (social_length_check).'

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?

Explicitly states when to use ('Use on body prose to find readability and style problems') and when not to use ('Not for ranking titles... Not for platform limits...'). Also provides guidance on error handling and retry safety, making it easy for an agent to decide.

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

All Moltline Creator Studio toolsInspect
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TDQS

A4.6/5.0
Disambiguation5/5

Each tool targets a distinct function: writing analysis, headline ranking, reading time, social length check, product listing, free skill retrieval, full product retrieval, and paid skill retrieval. There is no overlap, and the descriptions clearly differentiate them.

Naming Consistency3/5

Tool names use mixed conventions: imperative verbs (get_, list_) for product tools, but descriptive nouns for writing tools (headline_analyzer, reading_time, social_length_check). While not chaotic, the lack of a uniform pattern could cause minor confusion.

Tool Count5/5

With 8 tools covering two related areas (writing analysis and product catalog), the count is well-scoped. Each tool serves a clear purpose without redundancy, fitting the server's 'creator' theme.

Completeness4/5

The writing tools cover major content needs (draft quality, headlines, reading time, platform limits). The product tools provide complete read-only access to the catalog. A minor gap is the lack of search or filtering, but list_products returns all 20 products, which is adequate.

Resources