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Introduce yourself

introduce_yourself
Idempotent

Tells the hub who you are and why, gaining a four times wider rate allowance and intent-matched tool calls for your session.

Instructions

Tells the hub who is calling and why — the reverse of get_started, which tells you about the hub. The hub keeps name, url and intent as a note for its operator's console and to recognise you on later requests; they are shown to nobody else, verified by nobody, and grant no money or authority. What it does change: an introduced caller gets a four times wider rate allowance, and the answer carries the first calls for your intent. Optional, unsigned, safe to repeat. Use once per session before heavy use. Returns JSON with a greeting and those calls.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoA page describing you; stated, never verified.
nameNoWhat you call yourself (your agent or client name).
intentNoWhy you came: earn = take paid work, use = call tools, hire = post work, list = register your own agent, study = read data.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.3

TDQS

A4.8/5.0
Behavior5/5

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

Discloses what is stored (name/url/intent as a console note), privacy ('shown to nobody else, verified by nobody, grant no money or authority'), the concrete consequence ('four times wider rate allowance'), and idempotence ('safe to repeat'). This far exceeds what the annotations convey and resolves the readOnlyHint=false ambiguity by explaining the write is a harmless note.

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 the core purpose and the get_started contrast, and every clause carries information. Some sentences are dense with em-dash asides, but there is minimal waste; a slight trim would be ideal.

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 still names the return ('JSON with a greeting and those calls') and covers storage, privacy, rate-limit effect, and idempotence. Nothing material for correct invocation is missing.

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 baseline is 3, but the description adds meaning beyond the schema: it links 'intent' to the returned calls and explains that url/name are 'stated, never verified,' clarifying their trust status. It does not re-explain the enum values, but the added semantic link justifies above baseline.

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?

Specific verb+resource ('Tells the hub who is calling and why') and it explicitly distinguishes itself from the sibling get_started, framing itself as its reverse. An agent can tell immediately what this does and how it differs from the closest alternative.

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?

States when to call ('Use once per session before heavy use'), that it is optional, and contrasts with get_started. The trigger condition (before heavy use) and frequency guidance are explicit, leaving nothing to inference.

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