phrasesReturn common bigram phrases containing a word from Wordnik's corpus; wlmi parameter sets minimum mutual-information threshold.
| Name | Required | Description | Default |
|---|---|---|---|
| wlmi | No | ||
| word | Yes | ||
| limit | No | ||
| useCanonical | No |
| Name | Required | Description | Default |
|---|---|---|---|
| count | Yes | Number of items returned. | |
| items | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "word": "ubiquitous"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "count": {
+ "description": "Number of items returned.",
+ "type": "integer"
+ },
+ "items": {
+ "items": {
+ "properties": {
+ "count": {
+ "description": "Frequency count",
+ "type": "number"
+ },
+ "gram1": {
+ "description": "First word in bigram",
+ "type": "string"
+ },
+ "gram2": {
+ "description": "Second word in bigram",
+ "type": "string"
+ },
+ "wlmi": {
+ "description": "Weighted likelihood mutual information",
+ "type": "number"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "items",
+ "count"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description accurately states the tool's read-only, idempotent nature (already indicated by annotations) and adds context about the WLMi parameter and use of Wordnik's corpus. No contradictions with 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 of 18 words. Every word adds value, and there is no redundancy. It efficiently conveys the core functionality and a key parameter detail.
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 tool's moderate complexity (4 parameters) and the existence of an output schema, the description covers the core purpose but omits details for parameters 'limit' and 'useCanonical'. It is minimally adequate but not fully self-contained.
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 0%, so the description must compensate. Only the wlmi parameter is explained. The required 'word' parameter is obvious, but 'limit' and 'useCanonical' are not described, leaving significant gaps.
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 common bigram phrases containing a word from Wordnik's corpus, with a specific verb and resource. It distinguishes itself from sibling tools like 'definitions' or 'examples' by focusing on bigram phrases.
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 lacks explicit guidance on when to use this tool versus alternatives. No context is provided about prerequisites or when not to use it. The sibling list includes many related tools, but no differentiation is made.
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.