> ## Documentation Index > Fetch the complete documentation index at: https://docs.guidinghand.ai/llms.txt > Use this file to discover all available pages before exploring further. # What a procedure’s runs cost > At list price. A run is a conversation (or a task on its own) that got the procedure: the chat replies that read it, the tasks that followed it and its AI Review checks. `revisions`: each revision’s runs and average run (`avg_cents` null when none got it), oldest first. `last_30_days`: the last 30 days’ runs split by what for (`replies`, `tasks`, `qa`) and by model (tokens and price before each reply and task is rounded up to a whole cent). ## OpenAPI ````yaml /api-reference/openapi.json get /v1/agents/{agent_id}/procedures/{procedure_id}/costs openapi: 3.1.0 info: title: Eager API version: 1.0.0 description: >- Train AI agents like new hires: hand an agent your files and coach it, and it writes its own procedures and works in any software, even without an API. Talk to your agents one message at a time (POST /v1/agents/{agent_id}/responses): they answer from their files, procedures and your HTTP tools, and run tasks on their own cloud browser or your linked computers when an answer needs a website or a desktop app. Manage agents (versioned: save a draft, publish it), their procedures, browser and computers; follow conversations and tasks, answer approvals, and fetch history and recordings. Run tasks yourself on a session: a customer’s computer through an invite link, or a cloud browser. Test agents with evals: chat, browser and desktop test cases, run several times against your agents and judged on the answer. Every change is in the org’s audit log. servers: - url: https://guidinghand.ai description: Production - url: https://dev.guidinghand.ai description: Development (Stripe test mode) security: - bearerAuth: [] tags: - name: Agents - name: Agent files - name: Agent tools - name: Agent folders - name: Computers description: >- Computers your org links with the Eager app, and pools of them, for agents’ desktop tasks. Attach them to an agent in its `resources.computers`. - name: Phone numbers description: >- Bring your own Twilio numbers: connect the account, add its numbers, and pick the agent that answers each. Calls are answered by the agent's published version. - name: Sessions - name: Tasks - name: Webhooks - name: Audit log - name: Test cases - name: Test sets - name: Test runs - name: Start states - name: Runners - name: Responses description: >- Talk to an agent: each call is one turn of a conversation. The agent answers with its files, procedures and tools (and, with Run code, its own sandbox), asks for details with forms, and runs browser and desktop tasks when an answer needs a website or a desktop app. - name: Conversations description: >- The history of each conversation: messages, tool calls and the tasks the agent started, in order. - name: Uploads description: >- Files for conversations: attach them to a message, and download what the agent’s code made. Kept as long as their conversation. - name: Procedures description: >- An agent’s playbooks: when to use each and its steps. The agent finds and follows them; ones it writes from a first run are marked written_by: agent. - name: Categories description: The kinds of request an org’s procedures and test cases are sorted into. - name: Escalations description: >- What needs your team: an approval only the team can give or a question only it can answer, in a real conversation; a procedure run that failed; and one that worked another way, with the procedure rewritten to match (a proposed change). Test chats never escalate; evals do, without webhooks. - name: Schedules description: >- Run an agent’s procedure on a cron expression, in a time zone, with the inputs it needs. Each run is a conversation of its own with nobody in it (`channel` `schedule` in its variables): the procedure’s steps without AI run outright when it has them, else the model follows it to its end. Its record says how it ended, what the agent said last and what it cost; the team hears by webhook (`schedule.run_completed`, `schedule.run_failed`), email and Slack or Teams, as the schedule says. paths: /v1/agents/{agent_id}/procedures/{procedure_id}/costs: parameters: - name: agent_id in: path required: true description: The agent’s id. schema: type: string - name: procedure_id in: path required: true schema: type: string get: tags: - Procedures summary: What a procedure’s runs cost description: >- At list price. A run is a conversation (or a task on its own) that got the procedure: the chat replies that read it, the tasks that followed it and its AI Review checks. `revisions`: each revision’s runs and average run (`avg_cents` null when none got it), oldest first. `last_30_days`: the last 30 days’ runs split by what for (`replies`, `tasks`, `qa`) and by model (tokens and price before each reply and task is rounded up to a whole cent). operationId: getProcedureCosts responses: '200': description: Its costs. content: application/json: schema: type: object properties: object: type: string enum: - procedure_costs procedure_id: type: string revisions: type: array items: type: object properties: revision: type: integer saved_at: type: string format: date-time nullable: true current: type: boolean runs: type: integer total_cents: type: number avg_cents: type: number nullable: true last_30_days: type: object properties: runs: type: integer total_cents: type: number avg_cents: type: number nullable: true replies: type: object tasks: type: object qa: type: object models: type: array items: type: object '404': description: No such procedure. components: securitySchemes: bearerAuth: type: http scheme: bearer description: An org API key (`gh_live_…`) from Settings → API keys in the console. ```` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.