> ## Documentation Index > Fetch the complete documentation index at: https://docs.promptingcompany.com/llms.txt > Use this file to discover all available pages before exploring further. # How does my product do on TPC Benchmarks? > Ask your agent for your product's TPC Benchmarks results, trend and suggestions, and see which MCP tool it uses to answer. Ask your agent this, with `` replaced by your product's name: ```text theme={null} How does my product do on TPC Benchmarks, and what should we fix first? ``` The agent answers with your product's results on the public TPC Benchmarks leaderboard, which measures whether AI coding agents can go from a product's documentation to a first working integration. This is product data for signed-in TPC users. It is not the public TPC Benchmarks plugin for ChatGPT, which anyone can use without signing in. For that plugin, see [TPC Benchmarks in ChatGPT](https://docs.promptingcompany.com/mcp/benchmarks.md). ## Before you ask * Connect the server and sign in. See [Connect the MCP server](https://docs.promptingcompany.com/mcp/connect.md). * If you belong to more than one organization, put your organization slug in the same message. See [Find your organization slug](https://docs.promptingcompany.com/mcp/connect.md#find-your-organization-slug). * Use the product name as it appears in TPC. The agent searches for it. * The product needs a website domain that matches a benchmarked vendor, or a link to one. Suggestions need the link: a product that matches only by domain gets results but no suggestions until your team claims it on the product's Benchmarks page in TPC. ## What the agent does The agent chooses its own calls. A typical answer uses these steps in this order. **1. Find the product** If you did not give your organization slug, `list_organizations` finds it. Then `list_products` with your `organizationSlug` and the product name as `query` returns the product's slug and ID, which the next call needs. **2. Get the results and history** `get_product_benchmarks` takes a `view`. The `summary` view returns the matched vendor, whether it matched by link or by domain, completion rate, experience and readiness scores, the last tested date, and a per-task breakdown. The `trend` view returns daily readiness scores and, for each harness and model setup, daily runs with completion rate, experience score and the tested task titles. **3. Look at the suggestions** `get_product_benchmarks` with `view: "suggestions"` returns open and closed readiness and experience suggestions for a linked product. A product that is not benchmarked returns a null vendor. ## What you get back The agent writes a summary from those calls. Depending on which views it reads, the summary can include: * The vendor your product matches and how it matched * Completion rate, experience score, readiness score, and when the product was last tested * How each task did * How readiness and run results moved over time, and which days used a different set of tasks * Open suggestions grouped by effort, each with the fix and how recent its evidence is * Closed suggestions Each experience suggestion is either a Spec requirement, meaning a cited specification requires it and its links are listed, or Optional, meaning it goes beyond the specification and earns TPC readiness credit. Experience suggestions are AI-generated from the vendor's benchmark runs. Each one shows how many runs it is based on and your team's response, if any. Readiness suggestions come from the vendor's latest site readiness scan. The tool only reads. Responding to a suggestion, claiming a vendor, and requesting a benchmark are done in TPC. The same data is available from the terminal. See [Benchmark](https://docs.promptingcompany.com/cli/commands/benchmark.md) in the CLI reference. This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.