postFetch a single fake blog post by numeric id from DummyJSON. Returns title, body, tags, reaction counts, and the authoring userId.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Post ID | |
| body | No | Post body content | |
| tags | No | Post tags | |
| title | No | Post title | |
| userId | No | User ID of post author | |
| reactions | No | Number of reactions |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "id": 1
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "body": {
+ "description": "Post body content",
+ "type": "string"
+ },
+ "id": {
+ "description": "Post ID",
+ "type": "number"
+ },
+ "reactions": {
+ "description": "Number of reactions",
+ "type": "number"
+ },
+ "tags": {
+ "description": "Post tags",
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ },
+ "title": {
+ "description": "Post title",
+ "type": "string"
+ },
+ "userId": {
+ "description": "User ID of post author",
+ "type": "number"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and destructiveHint. Description adds return fields (title, body, tags, etc.) which adds some value beyond annotations, but no additional behavioral details like error handling or auth.
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?
Single sentence that front-loads the action and purpose, with no wasted 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?
Tool is simple with one parameter and an output schema. Description covers purpose and return fields adequately, though it omits what happens on missing id or error conditions.
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 0% for the only parameter 'id'. Description merely restates it is numeric, adding no extra semantics like range, format, or usage constraints.
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 fetches a single fake blog post by numeric id and lists returned fields. Implicitly distinguishes from sibling 'posts' by specifying 'single'.
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?
No explicit guidance on when to use this tool versus alternatives like 'posts' for multiple posts. Does not mention prerequisites or context.
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.
Many tools have overlapping purposes, e.g., multiple tools for data retrieval (ask_pipeworx, ask_pipeworx_grounded, deep_research, entity_profile) that differ only in nuance, and the inclusion of both DummyJSON and Pipeworx tools creates confusion about which domain to use for what. Agents will struggle to select the correct tool.
Naming conventions are mixed: Pipeworx tools use diverse patterns (verb_noun like 'validate_claim', noun like 'entity_profile', verb like 'forget'), while DummyJSON tools use simple nouns (posts, comments). No consistent pattern across the set.
43 tools is excessive for a server named 'Dummyjson'. The majority are Pipeworx tools unrelated to fake data, making the set feel bloated and unfocused. The count is too large for the apparent scope.
For a fake data API, the set is incomplete: it only provides read operations (fetch, search) with no create, update, or delete capabilities. However, for the Pipeworx portion, the read coverage is extensive, so it's not severely lacking overall.