todosFetch a paginated list of fake todo items from DummyJSON. Supports limit and skip. Returns todo text, completion status, and userId.
| Name | Required | Description | Default |
|---|---|---|---|
| skip | No | ||
| limit | No |
| Name | Required | Description | Default |
|---|---|---|---|
| skip | No | Number of todos skipped | |
| limit | No | Limit of todos returned | |
| todos | No | List of todos | |
| total | No | Total todo count |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "limit": 10
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "limit": {
+ "description": "Limit of todos returned",
+ "type": "number"
+ },
+ "skip": {
+ "description": "Number of todos skipped",
+ "type": "number"
+ },
+ "todos": {
+ "description": "List of todos",
+ "items": {
+ "properties": {
+ "completed": {
+ "description": "Completion status",
+ "type": "boolean"
+ },
+ "id": {
+ "description": "Todo ID",
+ "type": "number"
+ },
+ "todo": {
+ "description": "Todo task",
+ "type": "string"
+ },
+ "userId": {
+ "description": "User ID",
+ "type": "number"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "total": {
+ "description": "Total todo count",
+ "type": "number"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds value by detailing pagination support (limit/skip) and returned fields (text, completion status, userId), enhancing transparency 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 two sentences with no extraneous words. The primary purpose is front-loaded in the first sentence, followed by essential parameter and return field details. Every sentence earns its place.
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 list tool, the description covers key aspects: data source, pagination, and returned fields. The existence of an output schema compensates for missing metadata details. More context on use cases or result structure would improve completeness.
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 coverage, the description mentions 'Supports limit and skip' but lacks detailed semantics such as meaning, defaults, or ranges. This provides minimal guidance, leaving agents to infer parameter behavior.
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 verb 'Fetch' and resource 'paginated list of fake todo items from DummyJSON', which is specific and clearly distinguishes it from sibling tools like 'posts' or 'products'.
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 indicates usage for fetching todo items, providing clear context. However, it does not explicitly exclude alternatives or mention when not to use this tool compared to siblings.
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.