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List the demos

list_demos
Read-onlyIdempotent

Demos this platform keeps online, each a finished lambda showing one way to build something: a REST API over records, registration and login, a websocket game, uploads, live updates. Their keys are public and read only: read the closest one with read_lambda (and list_files, read_logs) before writing similar code. create_lambda with a demo's id as template starts from a copy.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_demos"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is given. The description adds real context beyond that – demo keys are public and read only, so no auth or permission concerns – but says nothing about the size or shape of the returned list or how entries are identified beyond "id" being usable as a template.

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?

Front-loaded with what demos are, then the read-only nature, then the next-step tooling. Every clause carries information, though the enumerated build examples are slightly longer than needed for an agent that only needs to choose the tool.

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

Completeness4/5

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

No output schema exists, and the description partially compensates by implying entries carry ids usable as create_lambda templates and are publicly readable. It does not state what fields each entry exposes (name, description, id), which is the one thing an agent calling this blind would still want.

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?

Zero parameters, so there is nothing for the description to disambiguate; the baseline is 4. The description correctly describes a no-argument index call without inventing filtering options the schema does not support.

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?

States a specific verb and resource ("Demos this platform keeps online") and immediately qualifies what a demo is: a finished lambda showing one way to build something, with concrete examples (REST API, login, websocket game, uploads, live updates). This clearly separates it from siblings like list_files or read_lambda, which return files or code rather than an index of example projects.

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?

Gives explicit follow-up routing: read the closest demo with read_lambda (plus list_files, read_logs) before writing similar code, and start from a copy via create_lambda using a demo's id as template. That is a genuine when/how workflow rather than vague context. It stops short of an explicit when-not or exclusion condition, so it is not a full 5.

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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