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Start Design Session

convoopen

Begin infrastructure design by opening a session with the AI assistant. Receive an intro message and session ID for subsequent conversation.

Instructions

WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). ⚠️ The session_id includes a ?token=... suffix (format: sess_v2_xxx?token=yyy) which is part of the session credential — without it, downstream tools fall back to a tokenless connect URL that 401s. Always pass session_id verbatim to subsequent tools and to the user; do NOT shorten, paraphrase, or strip the ?token= portion when summarizing the session in chat or in your own scratch notes. Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup.

OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceNoIDE/tool identifier so the connect screen can show the right 'Open {IDE}' button. Use lowercase: 'claude-code', 'codex', 'antigravity', 'kiro', 'cursor', 'vscode', 'windsurf', 'zed', 'aider', 'copilot', 'web', 'mcp'.
github_usernameNoGitHub username used for deploy commit attribution; pre-fills the GitHub username field on the connect screen.
project_contextNoOptional tech-stack summary so Riley can skip discovery questions (e.g. 'Next.js 14 + Postgres on AWS, ~50k MAU'). No PII, secrets, file paths, or source code — only general metadata useful to a cloud architect.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses critical behavior: returns session_id with ?token= suffix, without which downstream tools 401; explains Riley will ask questions; details response content. Annotations only provide openWorldHint and destructiveHint, so description adds extensive context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with clear sections (WORKFLOW, CRITICAL, OPTIONAL, IMPORTANT, TIP). Slightly verbose in token explanation, but given the critical nature, it is justified. Front-loaded with purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema, description explains response contains Riley's message and metadata with session_id. Covers all parameters and workflow integration. Complete for its role as initial step.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% parameter description coverage, but description enriches each: for 'source' adds auto-detection and requiredness; for 'project_context' adds do's and don'ts with example; for 'github_username' explains attribution. Adds significant value beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is 'Step 1 of 4 - Start infrastructure design conversation' and 'Open an InsideOut V2 session'. It distinguishes from sibling tools like convoreply and tfgenerate by placing it as the first step.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit keywords for when to use ('setup my cloud infra', etc.), warns not to answer Riley's questions on behalf of the user, and emphasizes the necessity of passing session_id verbatim to downstream tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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