Writing Style Checker
Server Details
Prose linter + AI-slop detector: weasel words, passive voice, hedging, and research-cited AI tells
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- theserverlessdev/wsc
- GitHub Stars
- 5
- Server Listing
- WSC - Writing Style Checker
Available Tools
3 toolscheck_textCheck text for writing style issuesARead-onlyInspect
Analyze text for writing style issues: weasel words, passive voice, duplicate words, long sentences, nominalizations, hedging, filler adverbs, and research-cited AI tells. Read-only and stateless — text is analyzed in memory on the hosted server and never stored. Returns a plain-text report with each issue's line and column, the matched text, surrounding context, and the reason for AI tells; texts over 100,000 characters return an error message. This hosted server has no filesystem access — the wsc-mcp npm package adds a check_file tool for local files. It only reports issues — to auto-remove duplicate words, follow up with fix_duplicates.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to analyze for writing style issues | |
| config | No | Optional config to enable/disable detectors or add/remove word-list entries; same schema as .wscrc.json (https://wsc.theserverless.dev/schema.json) | |
| format | No | Set to "markdown" to mask code blocks, inline code, tables, and headings so they are not linted as prose; default "plain" lints everything |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses read-only and stateless nature, in-memory processing, no storage, return format details, error condition, and lack of filesystem access. Annotations already indicate read-only, but description adds comprehensive behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured and front-loaded with purpose. Slightly verbose but each sentence adds value. No redundancy, but could be marginally shortened without losing information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters (one nested object) and no output schema, the description fully explains return format (plain-text report with specific fields), error handling (over 100k chars), and constraints (no filesystem access). Completely sufficient for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description does not add significant new meaning for parameters; it references the config schema link but the schema already provides descriptions. No additional clarity beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it analyzes text for writing style issues, listing specific issue types. Distinguishes from sibling tools (fix_duplicates, check_file) directly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly mentions when to use check_file for local files and fix_duplicates for auto-removal. Also notes the 100k character limit and error behavior, providing clear contextual guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fix_duplicatesRemove duplicate adjacent wordsARead-onlyInspect
Remove duplicate adjacent words (case-insensitive, including across line breaks) and return the cleaned text plus the list of words that were removed. Read-only with no side effects: the fix is returned in the response, nothing is written anywhere. Use after check_text reports duplicate words; other issue types are report-only and have no auto-fix.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to clean by removing duplicate adjacent words |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, and the description reinforces this with 'Read-only with no side effects'. It adds context about the return value (cleaned text plus list of removed words) but does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loads the core action, and every phrase adds value. No redundant or extra words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (single parameter, no output schema), the description covers the action, safety, return behavior, and usage context. It does not address edge cases like empty input, but the schema expects a string, so it's adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the description does not add extra meaning beyond the schema's description of the 'text' parameter. The description focuses on output and usage, not parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool removes duplicate adjacent words with specific details (case-insensitive, across line breaks), and distinguishes from the sibling tool check_text by noting it is used after check_text reports duplicates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly instructs when to use this tool: 'Use after check_text reports duplicate words', and when not: 'other issue types are report-only and have no auto-fix'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_word_listsList detector word listsARead-onlyInspect
Return every detector word/phrase list with its entry count, config key, and sample entries, plus a link to the full browsable library. Read-only, takes no parameters, and returns the same catalog for a given release. Use it to see what the detectors match before tuning a config for check_text; not needed for ordinary checking.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. The description adds that it is read-only, takes no parameters, and returns the same catalog for a given release, providing behavioral context beyond annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first defines output clearly, second provides usage guidance. No wasted words, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters, no output schema, and simple function, the description covers all necessary aspects: output, behavior, and usage context. Complete for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters with 100% coverage. The description explicitly states 'takes no parameters,' aligning with schema. Baseline for zero parameters is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns every detector word/phrase list with entry count, config key, sample entries, and a link. It specifies the resource and distinguishes from sibling tools like check_text by mentioning its use before tuning.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to use it before tuning a config for check_text and notes it is not needed for ordinary checking, providing clear context and an implicit alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
- Changed
check_text2 fields changed- changed
Input schema / properties / config / descriptionPrevious value: -"Optional WscConfig to customize which detectors run and their settings"New value: +"Optional config to enable/disable detectors or add/remove word-list entries; same schema as .wscrc.json (https://wsc.theserverless.dev/schema.json)" - changed
Input schema / properties / format / descriptionPrevious value: -"Set to \"markdown\" to skip code blocks, tables, and headings when analyzing"New value: +"Set to \"markdown\" to mask code blocks, inline code, tables, and headings so they are not linted as prose; default \"plain\" lints everything"
3 tool updates
- First observed
check_text - First observed
fix_duplicates - First observed
list_word_lists
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TDQS
Each tool has a unique, clearly defined purpose: check_text analyzes text for various issues, fix_duplicates specifically removes duplicate words, and list_word_lists provides metadata about the detection lists. No overlap or ambiguity.
All tool names follow a consistent verb_noun pattern using snake_case (check_text, fix_duplicates, list_word_lists), making them predictable and easy to distinguish.
Three tools is an appropriate count for a focused writing style checker: analysis, one targeted fix, and introspection. The number feels neither too sparse nor excessive for the domain.
The set covers the core use case of detecting writing issues and provides one automated fix (duplicates) plus lookups of detection rules. Missing are auto-fixes for other issue types and a tool to configure detectors, but the descriptions explicitly note that only duplicates have auto-fix, so the surface is intentionally scoped.