Browse every AI task type AIP can route — chat, image, video, speech, web search, knowledge search — with a short description of each. Call this first to see what's on the menu before you resolve or execute. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool is free ('Free') and that it returns short descriptions for each task type. However, it does not detail output format, ordering, or whether hidden/system intents are excluded. For a straightforward listing tool, this is adequate but not rich.
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?
The description is two sentences, with the first sentence delivering the core purpose and examples, and the second providing usage timing and cost. Every word earns its place; no filler or redundancy.
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 zero-parameter tool with no output schema, the description is nearly complete. It explains what the tool does, when to call it, and the cost factor. It could optionally mention the return format (e.g., a list of intents), but this is inferable and not critical for usage.
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 schema has 0 parameters, and the baseline for 0 params is 4. The description does not add parameter-related information, but none is needed. It does not contradict or confuse parameter usage.
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 tool's function: 'Browse every AI task type AIP can route' and enumerates examples (chat, image, video, speech, web search, knowledge search). This specific verb+resource combination distinguishes it from sibling tools like list_models or discover_agents, which target different entities.
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?
The description provides explicit usage guidance: 'Call this first to see what's on the menu before you resolve or execute.' This indicates the tool is a prerequisite step before using aip_resolve or aip_execute_with_budget. It does not mention alternatives to avoid, but the timing cue is valuable and clear.
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.
Most tools target distinct resources, but aip_estimate_cost and aip_resolve both provide pre-execution pricing, and chat overlaps with the chat intent inside aip_execute_with_budget. Descriptions clarify the differences reasonably well, but an agent could still pick the wrong one when estimating cost or sending a chat.
Tool names mostly follow an imperative snake_case verb_noun pattern such as list_models, search_apis, and discover_agents, with AIP functions sharing an aip_ prefix. Minor deviations like 'chat' and 'aip_resolve' lacking object nouns are easy to predict and do not create confusion.
With 9 tools, the set covers model listing, chat, AIP routing/execution, API discovery, and agent discovery without bloating. Each major workflow has a focused set of tools, and none feel unnecessary.
The AIP lifecycle is well covered — list intents, resolve, estimate cost, and execute with budget — and chat has list_models + chat. However, as an API Marketplace there is no direct call_api or invoke tool, and no publish/management surface, so search_apis and get_api_detail lead to an external action rather than completing the loop in-server.