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aarifmms/keyblind

aarifmms/keyblind

register_agent

Register an AI agent in a registry, binding it to a human sponsor and returning its identity plus an Ed25519 private key for signing its own actions.

Instructions

Register an AI agent in the Know Your Agent registry, bound to a human sponsor. Returns the agent identity and its Ed25519 private key, which the agent holds to sign its own actions.

Input Schema

NameRequiredDescriptionDefault
nameYesHuman-readable agent name (e.g., billing-agent)
scopeNoWhat the agent is authorized to do (e.g., read:invoices)
sponsorYesHuman accountable for this agent (email or name)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.9.2

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full load, and it does disclose the most consequential behavior: this tool returns an Ed25519 private key that the agent holds to sign its own actions — a one-time sensitive credential the caller must handle. It stops short of stating whether the key is shown only once, whether registration is idempotent for the same name, or what permissions are required.

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

Conciseness5/5

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

Two sentences, zero filler, with the core action and the security-critical return value front-loaded. Every clause earns its place.

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?

There is no output schema, so the description must explain return values — and it does (agent identity plus private key). Parameter semantics are fully covered by the schema. The only gap for a credential-minting mutation tool is handling guidance around the returned key.

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%, so name, scope, and sponsor are already fully documented with examples in the schema. The description adds only that the agent is 'bound to a human sponsor', restating rather than extending the schema, so baseline 3 applies.

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?

The description names a specific verb and resource — 'Register an AI agent in the Know Your Agent registry' — plus the binding constraint (human sponsor) and what is returned (identity + Ed25519 private key). It is clearly not a read/list tool, so an agent can distinguish it from list_agents without opening the schema, though no sibling is named explicitly.

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

Usage Guidelines3/5

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

The registration intent is implied well enough that an agent knows this is the creation path, and 'bound to a human sponsor' hints at a prerequisite. However there is no explicit when-to-use vs when-not, no statement about who must authorize registration, and no guidance on what to do afterwards (e.g., list_agents to confirm).

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