> ## Documentation Index
> Fetch the complete documentation index at: https://docs.iqrush.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Prepare a content and technical handoff

> Turn observed page evidence into a clear list of items to review.

Answer: “What do the measured answers use this page for, and what should our content or technical team review?”

## Prepare the scope

Use `list_projects` and `list_runs` to choose the project and completed run. Check readiness, then call `get_results_stability` for the same run and supported filters. For each measurement, preserve the scope, returned confidence interval, and row-quality fields. See [run selection](/developers/guides/07-projects-and-runs) and [decision-grade measurement](/developers/guides/10-stability).

The JSON examples below are MCP `tools/call` parameter objects. Replace ID placeholders and sample selections with values discovered in your account.

## Retrieve the evidence

1. Use `get_placement_targets` to discover cited pages and inspect each page's citation metrics.
2. Choose a returned URL and call `analyze_page_performance` for captured sections and citing statements.
3. Call `get_technical_features` for recorded technical observations.
4. For existing technical recommendations, use the separate [HTTP recommendations route](/developers/http/http-technical-recommendations). There is no named MCP equivalent in this edition.

```json theme={null}
{
  "name": "get_placement_targets",
  "arguments": {
    "project_id": "PROJECT_ID",
    "run_id": "RUN_ID",
    "limit": 20,
    "offset": 0
  }
}
```

## Build the handoff

Use one row per issue: page URL, observed evidence, proposed action, and what needs human review. Link back to the selected run and the answer or page evidence. Separate an existing IQRush recommendation from a new proposal made by the assistant.

The page-content read retrieves captured content. It does not promise a fresh crawl or a measured score for the assistant's proposed edit. The technical read reports observed features without proving causation. Do not manufacture a performance target from their values.

This workflow prepares a handoff. It does not edit Content Playground, publish content, or run a new measurement through the external tools.

Reference: [page targets](/developers/tools/get_placement_targets), [page evidence](/developers/tools/analyze_page_performance), [technical features](/developers/tools/get_technical_features).


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