word_of_the_dayFetch the Wordnik Word of the Day for a given date (YYYY-MM-DD) or today if omitted; returns word, definitions, and example sentences.
| Name | Required | Description | Default |
|---|---|---|---|
| date | No |
| Name | Required | Description | Default |
|---|---|---|---|
| note | No | Additional note | |
| word | No | Word of the day | |
| examples | No | Usage examples | |
| definitions | No | Definitions | |
| publishDate | No | Publish date |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "date": "2024-01-15"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "definitions": {
+ "description": "Definitions",
+ "items": {
+ "properties": {
+ "definition": {
+ "description": "Definition text",
+ "type": "string"
+ },
+ "partOfSpeech": {
+ "description": "Part of speech",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "examples": {
+ "description": "Usage examples",
+ "items": {
+ "properties": {
+ "text": {
+ "description": "Example text",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "note": {
+ "description": "Additional note",
+ "type": "string"
+ },
+ "publishDate": {
+ "description": "Publish date",
+ "type": "string"
+ },
+ "word": {
+ "description": "Word of the day",
+ "type": "string"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, idempotentHint, and destructiveHint=false. The description adds behavioral details: date format (YYYY-MM-DD), default to today if omitted, and return type (word, definitions, example sentences). This adds value beyond 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 a single, front-loaded sentence with no wasted words. Every element ('Fetch', 'Wordnik Word of the Day', date format, default behavior, return content) is necessary and efficiently stated.
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?
The tool has one optional parameter and an output schema (not shown but referenced). The description adequately covers the input (date format/default) and output (word, definitions, example sentences). For a simple tool, this is sufficiently complete.
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?
With 0% schema description coverage, the description compensates by specifying the date format (YYYY-MM-DD) and the default behavior (today if omitted). This adds meaning beyond the raw schema that only shows type string.
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 action ('Fetch'), the resource ('Wordnik Word of the Day'), and the output ('word, definitions, and example sentences'). It distinguishes from siblings like 'random_word' and 'definitions' by specifying it's the 'Word of the Day' for a given date.
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 implies usage for fetching the word of the day, but does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among siblings. The context is clear but lacks exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, especially between Wordnik and Pipeworx domains. However, some overlap exists among data query tools (e.g., ask_pipeworx vs deep_research) and company lookups (entity_profile vs compare_entities), but descriptions are detailed enough to differentiate them in most cases.
Naming conventions are mixed: some tools use snake_case (ai_visibility_check), others use descriptive phrases (ask_pipeworx_grounded), and some are single words (remember, recall). There is no uniform verb_noun pattern, though groups like polymarket_* and scan_* provide some consistency within their subsets.
With 42 tools, the server is overloaded. It combines two distinct services (Wordnik dictionary and Pipeworx data) into one set, making it feel like two servers merged. Many tools are niche (e.g., hyphenation, random_words), increasing count without clear benefit. A split would improve coherence.
The Wordnik coverage is thorough (definitions, examples, pronunciation, frequency, etc.), and Pipeworx covers a wide range of data sources with tools for basic lookups, comparisons, research, and subscriptions. Minor gaps exist (e.g., no update/delete for Wordnik data), but overall the surface is comprehensive for the intended use.