get_jokeRetrieve a specific dad joke by ID. Returns the full joke text.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The ID of the dad joke to retrieve. |
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Unique identifier for the joke | |
| joke | Yes | The joke text |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "id": "R7UfaahbfFd"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "id": {
+ "description": "Unique identifier for the joke",
+ "type": "string"
+ },
+ "joke": {
+ "description": "The joke text",
+ "type": "string"
+ }
+ },
+ "required": [
+ "id",
+ "joke"
+ ],
+ "type": "object"
+}Input schema / examplesRemoved value: -[
- {
- "id": "R7UfaahbfFd"
- }
-]Output schema / (root)Previous value: -{
- "properties": {
- "id": {
- "description": "Unique identifier for the joke",
- "type": "string"
- },
- "joke": {
- "description": "The joke text",
- "type": "string"
- }
- },
- "required": [
- "id",
- "joke"
- ],
- "type": "object"
-}New value: +nullOutput schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "id": {
+ "description": "Unique identifier for the joke",
+ "type": "string"
+ },
+ "joke": {
+ "description": "The joke text",
+ "type": "string"
+ }
+ },
+ "required": [
+ "id",
+ "joke"
+ ],
+ "type": "object"
+}Input schema / examplesAdded value: +[
+ {
+ "id": "R7UfaahbfFd"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the core safety profile. The description adds that it 'Returns the full joke text,' which is useful but does not disclose error behavior, rate limits, or other potential edge cases. This is consistent with the reduced burden when annotations are present.
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 sentence, concise, and front-loaded with the verb and resource. Every word conveys essential information without redundancy, making it highly efficient.
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 simple lookup tool with one parameter, full schema coverage, and comprehensive annotations (readOnly, idempotent, non-destructive), the description is complete. The existence of an output schema further reduces the need to explain return values. The tool's behavior is fully captured by the current description.
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 provides 100% coverage with a clear description for the single 'id' parameter ('The ID of the dad joke to retrieve'). The tool description does not add additional parameter semantics beyond what the schema already documents, so the baseline of 3 is appropriate.
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 uses the specific verb 'Retrieve' and clearly identifies the resource as 'a specific dad joke by ID.' It distinguishes itself from siblings like random_joke and search_jokes by focusing on retrieval by ID, making its purpose immediately clear.
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 the appropriate use case: when you have a specific joke ID and want the full joke text. It does not explicitly name alternatives or provide exclusions, but the context ('by ID') gives clear guidance. Without explicit comparison to random_joke or search_jokes, it falls just short of a 5.
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 are clearly distinct, but the three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) are nearly identical, with the beta explicitly matching the stable version. Additionally, ai_visibility_check and scan_competitor_ai_presence overlap in purpose, creating some selection ambiguity.
All tool names follow a consistent snake_case verb_noun pattern (e.g., get_joke, search_jokes, resolve_entity, validate_claim). Even the more noun-like names like entity_profile and pipeworx_feedback fit the readable convention. No mixed camelCase or erratic verb usage.
With 34 tools, the count is far above the typical well-scoped range of 3-15. The server is named 'dadjokes' but only 3 tools actually serve that purpose; the remaining 31 are an unrelated Pipeworx research and prediction-market platform, making the scope feel bloated and misaligned.
For the nominal dad-joke domain, the surface is complete (get, random, search). However, the intended domain is ambiguous given the massive unrelated toolset; it's unclear what a user should expect the server to cover, and the analysis/prediction tools lack obvious CRUD or management counterparts.