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Kiln

Kiln

by codeofaxel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

get_started

Read-only

Returns an onboarding summary for AI agents to discover Kiln's tools, core workflows, and the most useful tools to call first, helping unfamiliar agents start a session.

Instructions

Quick-start guide for AI agents using Kiln.

        Returns an onboarding summary: what Kiln is, how to discover
        its tools, core workflows, and the most useful tools to call
        first.  Call this at the start of a session if you're
        unfamiliar with the available capabilities.

        Args:
            chat_app: The chat app the person is writing to you from,
                when there is one (``telegram``, ``discord``,
                ``whatsapp``, ``imessage``, ``signal``, ``slack``,
                ``wechat``, etc.).  Say it once per session; leave it
                out when they are typing in this app itself.  Kiln
                uses it to lead with the way of approving a print
                that suits someone on a phone.

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": "get_started"
  }
}

Input Schema

NameRequiredDescriptionDefault
chat_appNoThe chat app the person is writing to you from, when there is one (``telegram``, ``discord``, ``whatsapp``, ``imessage``, ``signal``, ``slack``, ``wechat``, etc.). Say it once per session; leave it out when they are typing in this app itself. Kiln uses it to lead with the way of approving a print that suits someone on a phone.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.5.1
    • addedInput schema / properties / chat_app / description
      Added value: +"The chat app the person is writing to you from, when there is one (``telegram``, ``discord``, ``whatsapp``, ``imessage``, ``signal``, ``slack``, ``wechat``, etc.).  Say it once per session; leave it out when they are typing in this app itself.  Kiln uses it to lead with the way of approving a print that suits someone on a phone."
  2. Changed1 schema field changedv1.5.0
    • addedInput schema / properties / chat_app
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "title": "Chat App"
+}
  3. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavior: what the response contains (onboarding summary, tool discovery, core workflows) and why chat_app is consumed ('to lead with the way of approving a print that suits someone on a phone'). This matters because there is no output schema.

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?

Purpose and return contents are front-loaded in the first two paragraphs, and the per-session instruction is explicit. The embedded 'Args:' block restates the schema verbatim, which is minor redundancy, and docstring indentation carries over into the prose.

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?

For a zero-required-parameter onboarding tool with no output schema, the description covers what it returns, when to call it, and how to use the optional argument, so an agent can invoke it without guessing. Only the response format and size remain unspecified.

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

Parameters3/5

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

Schema description coverage is 100% and the single parameter carries the same text as the description; the description adds no syntax or format detail beyond it. Baseline 3 applies since the schema does all the parameter work.

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

Purpose4/5

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

States a specific verb+resource: returns an onboarding summary covering what Kiln is, how to discover its tools, core workflows, and which tools to call first. This clearly separates it from capability-listing siblings such as get_skill_manifest or consumer_onboarding, though it does not name an alternative explicitly.

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 a clear trigger: 'Call this at the start of a session if you're unfamiliar with the available capabilities,' plus a per-session rule for the chat_app argument ('say it once per session; leave it out when they are typing in this app itself'). It lacks an explicit 'do not call if...' exclusion, but the context is unambiguous.

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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