# Apify Actor Idea Validator (`zinin/apify-actor-idea-validator`) Actor

Assess one proposed Apify Actor idea against public Store similarity, activity, quality, competition and visible pricing evidence. Public Store API only, no LLM.

- **URL**: https://apify.com/zinin/apify-actor-idea-validator.md
- **Developed by:** [Tim Zinin](https://apify.com/zinin) (community)
- **Categories:** MCP servers, Developer tools
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Apify Actor Idea Validator

Assess one proposed Apify Actor idea against the public Apify Store. The Actor uses
only `GET https://api.apify.com/v2/store`, applies the contract-scoped local scoring
rules, and returns one report row when the idea has enough evidence.

### What you get

- Compares your idea to public Store actors by title, description, keywords and categories.
- Scores the Store cohort with the shared market formula from the Wave 3 contract.
- Returns a single dataset report row with:
  - the closest public actors
  - the similarity threshold outcome
  - a `validate` / `refine` / `reject` recommendation
  - the derived opportunity score and source metrics
- Writes the compact run summary to default KVS key `OUTPUT`.

### How to use

1. Click **Try for free** and provide a proposed Actor idea.
2. Set a unique `requestId`, then choose compact or evidence detail.
3. Start the run and read the useful report row from the dataset or the compact summary from `OUTPUT`.

### Limits

- Public Store API only
- No LLM
- No login, token, proxy or browser
- `requestId` is required for replay/conflict semantics
- `maxResults` caps the detailed evidence list, not the number of dataset rows
- `freshnessMinutes=0` bypasses report-cache reuse

### Pricing

Pay-per-event:

- `apify-actor-start`: $0.005
- `result-found`: $0.05

Only a confirmed useful report emits the `result-found` event. Failed validation,
missing evidence, source errors, budget denial, and an indeterminate delivery do not
emit a second charge. The business envelope is written to KVS key `OUTPUT`; replaying
the same `requestId` never writes or charges again.

### Input

```json
{
  "schemaVersion": "1.0",
  "requestId": "idea-001",
  "maxResults": 10,
  "freshnessMinutes": 60,
  "detailLevel": "compact",
  "idea": {
    "title": "Apify Store Opportunity Scanner",
    "description": "Scan public actors and rank market opportunities.",
    "keywords": ["store", "pricing", "opportunity"],
    "categories": ["MCP_SERVERS", "DEVELOPER_TOOLS"]
  }
}
```

### Output

Dataset row example:

```json
{
  "schemaVersion": "1.0",
  "requestId": "idea-001",
  "reportType": "idea_validation",
  "generatedAt": "2026-07-31T00:00:00.000Z",
  "sampleConfidence": "low",
  "idea": {
    "title": "Apify Store Opportunity Scanner",
    "description": "Scan public actors and rank market opportunities.",
    "keywords": ["store", "pricing", "opportunity"],
    "categories": ["MCP_SERVERS", "DEVELOPER_TOOLS"]
  },
  "assessment": {
    "recommendation": "refine",
    "closestSimilarity": 0.42,
    "matchedActorCount": 7,
    "opportunity": {
      "score": 58.4
    },
    "closestActors": []
  }
}
```

The result row is derived only from public Store evidence. Missing fields stay null.
No revenue, profit, or private-account data is inferred.

#### Related tools

Related tools for adjacent workflows in in-house factory tooling.

| Actor | What it does |
|---|---|
| [Apify Market Gap Finder](https://apify.com/zinin/apify-market-gap-finder) | Pair it in the in-house factory tooling workflow: Compare user-declared niches against the public Apify Store and rank evidence-backed market gaps |
| [Apify Pricing Benchmark Advisor](https://apify.com/zinin/apify-pricing-benchmark-advisor) | Pair it in the in-house factory tooling workflow: Summarize visible public Apify Store event-price distributions for a declared cohort |
| [Apify Niche Demand Radar](https://apify.com/zinin/apify-niche-demand-radar) | Pair it in the in-house factory tooling workflow: Produce a current demand-direction snapshot for one declared niche using observed public Apify Store user... |
| [Apify Portfolio Expansion Planner](https://apify.com/zinin/apify-portfolio-expansion-planner) | Pair it in the in-house factory tooling workflow: Rank user-supplied candidate niches by public Store opportunity and textual adjacency to a user-supplied... |

### FAQ / Support

**Does it invent market facts?** No. Scores and recommendations use only fields observed in the public Store response.

**What this is NOT.** It is not a revenue forecast, product-success guarantee, or private-account auditor. Report bugs through the Actor page.

# Actor input Schema

## `schemaVersion` (type: `string`):

Contract version for the business input.

## `requestId` (type: `string`):

Idempotency key for replay/conflict handling.

## `maxResults` (type: `integer`):

Maximum number of matched actors to keep in the detailed report.

## `freshnessMinutes` (type: `integer`):

Age limit for report-cache reuse. Set to 0 to bypass cache hits.

## `detailLevel` (type: `string`):

Compact or evidence-heavy output in the dataset row.

## `idea` (type: `object`):

Proposed Apify Actor concept to score against the public Store.

## Actor input object example

```json
{
  "schemaVersion": "1.0",
  "requestId": "idea-daily-prefill-001",
  "maxResults": 10,
  "freshnessMinutes": 60,
  "detailLevel": "compact",
  "idea": {
    "title": "Apify Store Opportunity Scanner",
    "description": "Scores public Store opportunities.",
    "keywords": [
      "store",
      "pricing"
    ],
    "categories": [
      "MCP_SERVERS"
    ]
  }
}
```

# Actor output Schema

## `OUTPUT` (type: `string`):

Compact business OUTPUT envelope stored in the default key-value store.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "schemaVersion": "1.0",
    "requestId": "idea-daily-prefill-001",
    "maxResults": 10,
    "freshnessMinutes": 60,
    "detailLevel": "compact",
    "idea": {
        "title": "Apify Store Opportunity Scanner",
        "description": "Scores public Store opportunities.",
        "keywords": [
            "store",
            "pricing"
        ],
        "categories": [
            "MCP_SERVERS"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("zinin/apify-actor-idea-validator").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "schemaVersion": "1.0",
    "requestId": "idea-daily-prefill-001",
    "maxResults": 10,
    "freshnessMinutes": 60,
    "detailLevel": "compact",
    "idea": {
        "title": "Apify Store Opportunity Scanner",
        "description": "Scores public Store opportunities.",
        "keywords": [
            "store",
            "pricing",
        ],
        "categories": ["MCP_SERVERS"],
    },
}

# Run the Actor and wait for it to finish
run = client.actor("zinin/apify-actor-idea-validator").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "schemaVersion": "1.0",
  "requestId": "idea-daily-prefill-001",
  "maxResults": 10,
  "freshnessMinutes": 60,
  "detailLevel": "compact",
  "idea": {
    "title": "Apify Store Opportunity Scanner",
    "description": "Scores public Store opportunities.",
    "keywords": [
      "store",
      "pricing"
    ],
    "categories": [
      "MCP_SERVERS"
    ]
  }
}' |
apify call zinin/apify-actor-idea-validator --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=zinin/apify-actor-idea-validator",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/JeyRrGG9gh6sUyaZf/builds/f0C3EHAivvNdn8are/openapi.json