exploreBrowse curated Wiro AI models grouped by category, then select a model and check its schema before running it.
Browse curated Wiro models grouped by category. Choose a model and call get_model_schema before run_model.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| categories | Yes | ||
| nextAction | No |
Changes observed during successful MCP inspections.
v1.4.1Output schema / properties / categories / items / properties / models / items / properties / discountPercentAdded value: +{
+ "description": "Your discount on this model, in percent. It comes off the part of a charge paid from deposits; coupon credit and store revenue pay first, at the list price in pricing.",
+ "type": "number"
+}Output schema / properties / categories / items / properties / models / items / properties / estimatedCostUsd / descriptionAdded value: +"Estimated USD cost of one run: the average of past runs for a model billed by run time, or the listed estimate of a price set when the run ends. Null when there is no such estimate, as for a model priced by its options: see pricing."v1.2.3Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Output schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"v1.2.1Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "http://json-schema.org/draft-07/schema#",
+ "additionalProperties": false,
+ "properties": {
+ "categories": {
+ "items": {
+ "additionalProperties": false,
+ "properties": {
+ "models": {
+ "items": {
+ "additionalProperties": false,
+ "properties": {
+ "categories": {
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ },
+ "description": {
+ "type": "string"
+ },
+ "estimatedCostUsd": {
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "pricing": {
+ "type": "string"
+ },
+ "slug": {
+ "type": "string"
+ },
+ "title": {
+ "type": "string"
+ }
+ },
+ "required": [
+ "slug",
+ "title",
+ "categories"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "title": {
+ "type": "string"
+ },
+ "total": {
+ "minimum": 0,
+ "type": "integer"
+ }
+ },
+ "required": [
+ "title",
+ "total",
+ "models"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "nextAction": {
+ "additionalProperties": false,
+ "properties": {
+ "arguments": {
+ "additionalProperties": {},
+ "type": "object"
+ },
+ "reason": {
+ "type": "string"
+ },
+ "tool": {
+ "type": "string"
+ }
+ },
+ "required": [
+ "tool",
+ "arguments",
+ "reason"
+ ],
+ "type": "object"
+ }
+ },
+ "required": [
+ "categories"
+ ],
+ "type": "object"
+}v1.1.4Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is fully covered without the description. The description adds the workflow constraint (schema lookup required before running), which is genuine behavioral context, but says nothing about catalog size, freshness, or filtering behavior.
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?
Two short sentences with zero waste: the first establishes what is returned, the second establishes the required next steps. The core purpose is front-loaded.
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?
With no parameters, rich annotations, and an output schema that carries the return structure, the description covers what an agent needs to call it. The only gap is the absence of any routing hint versus search_models, which would matter given how many model-related siblings exist.
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 tool takes zero parameters, so there is no parameter semantics to explain and the baseline of 4 applies. The description correctly implies no input is needed by framing this as a pure browse action.
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?
States a specific verb ('Browse') and resource ('curated Wiro models grouped by category'), which tells the agent the result is an organized catalog rather than a raw search. It does not explicitly distinguish itself from sibling tools like search_models or recommend_model, so the agent must infer that boundary.
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?
Provides clear downstream guidance: pick a model, then call `get_model_schema` before `run_model` — an explicit, useful sequence. However, it gives no condition for choosing this tool over search_models or recommend_model, which are the closest alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.