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luthersystems

insideout-mcp

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.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.1

TDQS

A4.6/5.0
Behavior5/5

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

The description discloses critical behaviors beyond the annotations: the session_id format with a ?token= suffix and its necessity to avoid 401s, the instruction to never strip or paraphrase it, and the warning that Riley will ask questions the agent must forward rather than answer. It also notes the source parameter controls the 'Open {IDE}' button. These add substantial behavioral detail that annotations (openWorldHint: true, destructiveHint: false) do not convey.

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?

The description is longer than typical but each section serves a purpose: workflow label, session handling, usage trigger, and per-parameter guidance. It is structured with headers and bolded warnings, making it scannable. Minor redundancy exists (e.g., session_id importance repeated), but overall it is efficient for a complex tool.

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?

With no output schema, the description explains the expected response ('clean message from Riley' and 'session_id in the response metadata'). It covers the full context: initialization, user interaction, downstream tool requirements, parameter semantics, and even points to 'workflow.usage prompt' for further guidance. For a session-starting tool with 3 optional parameters, this is complete.

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

Parameters4/5

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

Schema coverage is 100%, so a baseline of 3 applies. The description enriches each parameter: project_context includes a detailed example and explicit exclusions (no credentials/PII), source includes auto-detection guidance and a list of accepted values, and github_username explains its pre-fill behavior. This goes beyond the schema's short descriptions, though the schema already handles basic meaning.

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 explicitly states 'WORKFLOW: Step 1 of 4 - Start infrastructure design conversation' and 'Open an InsideOut V2 session and receive the assistant's intro message.' This clearly identifies the verb (start/open), resource (infrastructure design conversation/session), and how it differs from siblings like convoreply or tfgenerate (it is the initial session setup step).

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

Usage Guidelines4/5

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

The description provides explicit when-to-use guidance: '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.' It also gives workflow context (step 1 of 4) and indirectly distinguishes it from alternatives by requiring the session_id for subsequent tools. However, it does not explicitly state when NOT to use this tool versus others, and relies on 'Examine workflow.usage prompt' for broader context.

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