Start free sign-up for the user: email them a six-digit code. The user must read the code from their own inbox and give it to you, then call redeem_code. This is how an agent gets the user an API key (5,000 free tokens, no card).
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | The user's email address. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description reveals that the tool sends an email (side effect), is part of a two-step signup process, and yields an API key with free tokens. This provides useful behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no redundant words, front-loaded with action. Every sentence adds value, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description fully covers the purpose, process, and next step (redeem_code). No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'email' is fully described in the schema (100% coverage). The description adds that the email is used to send the code, but no additional semantic meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'start free sign-up' and the resource 'user' with the action of emailing a six-digit code. It distinguishes from sibling tools like 'redeem_code' by mentioning the follow-up step.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells the agent that the user must read the code and then call redeem_code, providing clear context for when to use this tool. It does not explicitly state when not to use it, but the guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: blocks_in_area provides per-block travel times, isochrone gives reachable areas, nearby_pois gives times to specific POIs, walkability_summary gives times to destination categories, and the rest handle place lookup, catalog, tokens, and authentication. No two tools overlap in functionality.
Tool names mix styles: some start with verbs (find_place, get_catalog, redeem_code, request_sign_in), others are noun phrases (blocks_in_area, isochrone, nearby_pois, walkability_summary). There is no consistent verb_noun or noun pattern, making it harder for an agent to predict tool names.
With 10 tools, the server covers core travel time analysis, place lookup, authentication, and membership. The count is well-scoped for the domain—neither too few to be useful nor too many to be confusing.
The tool surface covers the major workflows: finding places, getting base data, computing travel times in various forms (blocks, isochrones, POIs, summaries), and managing API keys. Minor gaps exist (e.g., no direct tool for single-point travel time to arbitrary coordinates), but the set is largely complete for the stated purpose.
