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Agent Broker

by dev.hatchloop

mint_key

Agent self-serve API key issuance. An autonomous agent that has no email inbox can obtain a free-tier API key by proving it holds the MACHINE_MINT_SECRET via HMAC-SHA256. Returns a usable key immediately with no human action required.

EXAMPLE USER QUERIES THAT MATCH THIS TOOL: user: "I need an API key to call AgentBroker tools" -> call mint_key({"agent_id": "my-agent-abc123", "timestamp": 1725100000, "nonce": "4f8a2c1d", "signature": "<HMAC-SHA256(agent_id+timestamp+nonce, MACHINE_MINT_SECRET)>"})

WHEN TO USE: Use when an AI agent needs to self-provision a write-capable API key without a human email address. The caller must know the MACHINE_MINT_SECRET (available from hatchloop.dev/docs/#machine-mint). WHEN NOT TO USE: Do not use if the agent has a human operator who can complete the email flow at /keys/request. Do not use for paid plans — this endpoint issues free-tier keys (100 ops/day) only. COST: free - no key required LATENCY: ~100ms

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nonceYesRandom value (UUID or hex). Prevents replay attacks — use a fresh nonce each call.
agent_idYesA stable unique identifier for this agent (e.g. a UUID). The issued key is deterministically tied to this ID.
signatureYesHMAC-SHA256(agent_id + str(timestamp) + nonce, MACHINE_MINT_SECRET) as lowercase hex. The HMAC input is the raw concatenation with no separators.
timestampYesUnix epoch seconds at signing time. Must be within 60s of server time.

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=false, idempotentHint=false, destructiveHint=false. The description adds important behavioral context: requires the MACHINE_MINT_SECRET, yields a free-tier key with 100 ops/day, has no human action, and returns the key immediately with documented cost and latency. No contradiction exists with annotations.

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?

The definition is structured with a clear opening summary, a concrete example, and labeled WHEN/COST/LATENCY sections. Every sentence carries useful information; despite length, it is front-loaded and easy to scan.

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 no-output-schema tool, it explains the security prerequisite, the returned key, the rate tier, and alternatives. It does not enumerate possible failure responses (e.g., invalid signature or expired timestamp), but the schema already covers timestamp validity and the HMAC formula.

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 the schema already fully documents agent_id, timestamp, nonce, and signature including the HMAC concatenation format. The description's example call duplicates this rather than adding new parameter semantics; baseline 3 is appropriate.

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 opens with a specific verb and resource ('Agent self-serve API key issuance') and explains the exact autonomous-agent scenario: no email inbox, proving possession of MACHINE_MINT_SECRET via HMAC-SHA256. This clearly distinguishes it from siblings like check_quota or get_status and leaves no ambiguity about what the tool produces.

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?

The WHEN TO USE and WHEN NOT TO USE sections are explicit: use for self-provisioning a write-capable key without a human email, and do not use for the human operator email flow or paid plans. It even names the alternative endpoint '/keys/request' and the free-tier 100 ops/day constraint.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools target distinct resource+action pairs (find_business vs verify_business, check_booking_link vs import_booking_url, get_status vs get_outcome). The main confusable pairs are send_message vs send_transactional_confirmation and verify_business vs verify_company_record, but their descriptions draw clear boundary lines.

Naming Consistency4/5

The set overwhelmingly follows lower_snake_case verb_noun naming (call_business, check_quota, find_business, send_message, verify_company_record). Minor deviations like self_test and mint_key, plus inconsistent verb choices (lookup_ vs get_ vs find_), prevent a perfect score.

Tool Count3/5

At 23 tools, the server falls into the heavy range and bundles several unrelated domains: SMB booking/messaging, trade and sanctions compliance, company verification, and platform operations. Each tool is individually reasonable, but the set feels like multiple servers merged into one.

Completeness3/5

Core SMB workflows are well covered: find/verify/import/book, messaging with conversation handling, and compliance preflights. Notable gaps include no consent-record management even though send_message requires consent_record_id for marketing, no update/delete lifecycle for leads or businesses, and no webhook configuration despite webhooks being referenced.

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