# Influencer Deliverable Reconciler (`mehdi_badawi/influencer-deliverable-reconciler`) Actor

Turn a campaign manifest and collected post data into one verdict per creator deliverable: posted, late, missing, edited, removed, requirements failed, or unknown. Does not scrape social platforms.

- **URL**: https://apify.com/mehdi\_badawi/influencer-deliverable-reconciler.md
- **Developed by:** [Mehdi Badawi](https://apify.com/mehdi_badawi) (community)
- **Categories:** Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 1,000 resolved deliverable reconciliations

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Influencer Deliverable Reconciler

Turn a campaign manifest and collected post data into one clear verdict per
creator deliverable: posted, late, missing, requirements failed, edited,
removed, unknown, story unverifiable, or private/auth required.

### Start in 30 seconds

1. Select **Try for free** and run with no input for a labeled demo.
2. Supply `deliverables`, normalized `observations`, and explicit `coverage`
   from your authorized scraper, export, or API.
3. Export the verdict rows or send them into your agency workflow.

**Price:** $0.01 per resolved deliverable, plus a $0.00005 start event.
Unknown, inaccessible, story-unverifiable, failed, and demo results are free.

This Actor reconciles supplied evidence. It does not collect social posts or
claim that incomplete coverage proves a missing deliverable.

### Why it exists

Campaign teams repeatedly compare rosters and posting requirements with collected social posts. This Actor owns the deterministic reconciliation step. It does **not** bypass platform access controls, scrape private accounts, or claim that an absent observation proves a post is missing.

### Quick start

Run with no input for a credential-free demo. For real work, supply:

- `deliverables`: expected creator/platform/content, deadline, and at least one positive identity signal: exact URL, hashtag, mention, or caption fragment.
- `observations`: normalized public-post records from your existing collection source.
- `coverage`: explicit complete creator/platform windows. A `missing` verdict requires complete coverage through the evaluation time.
- `priorState`: the prior `STATE` record when edit detection is wanted.

Dataset rows contain the verdict and reason codes. `OUTPUT` contains counts; `STATE` contains reusable fingerprints.

### Truth boundaries

- Stories are always `stories_unverifiable`.
- Private or authentication-gated observations are `private_or_auth_required`.
- Incomplete collection coverage yields `unknown`, never `missing`.
- Removal requires an explicit removed observation matched to the deliverable.
- This Actor evaluates supplied evidence; upstream collection quality remains visible through coverage attestations.

### Data, state, and support

Use authorized campaign exports only and minimize creator handles, captions,
and contractual details. `STATE` is a campaign-scoped output for explicit
replay; pass it back only with the same `campaignId`. Delete run datasets and
stores under your chosen retention policy. Support owner: Mehdi Badawi through
the Apify Store support channel, with an initial-response target of two business
days.

### Local checks

```sh
npm ci
npm test
npm start
```

Contract version: `1.0.0`. Limits: 500 deliverables, 5,000 observations, 500 coverage attestations.

# Actor input Schema

## `contractVersion` (type: `string`):

Input contract version; currently 1.0.0.

## `campaignId` (type: `string`):

Stable identifier for this campaign reconciliation.

## `evaluationTime` (type: `string`):

ISO-8601 time used for deterministic verdicts.

## `deliverables` (type: `array`):

Expected creator posts, videos, reels, or stories (maximum 500).

## `observations` (type: `array`):

Normalized observations from upstream public-data collection (maximum 5,000).

## `coverage` (type: `array`):

Creator/platform windows known to be complete. Missing is never asserted without complete coverage.

## `priorState` (type: `object`):

Optional prior STATE record used to detect edits.

## `graceHours` (type: `number`):

Delay after the deadline before complete no-match coverage becomes missing.

## `matchingWindowHours` (type: `number`):

How far before the deadline a non-URL observation may match.

## Actor input object example

```json
{
  "contractVersion": "1.0.0",
  "graceHours": 0,
  "matchingWindowHours": 72
}
```

# Actor output Schema

## `verdicts` (type: `string`):

No description

## `summary` (type: `string`):

No description

## `state` (type: `string`):

No description

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("mehdi_badawi/influencer-deliverable-reconciler").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("mehdi_badawi/influencer-deliverable-reconciler").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{}' |
apify call mehdi_badawi/influencer-deliverable-reconciler --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,mehdi_badawi/influencer-deliverable-reconciler"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/XSfJ8fHvZYDkVWUFG/builds/KwZoUNeEo5jwysDuc/openapi.json