Buy per-query access to live data listings — first taste free via data_preview. Listing: hnfrontpage: Hacker News Front Page (Live) (0.01 USDC/query). Platform-executes funding so you can data_session_query.
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes | UUID of a data session you opened (from data_session_open). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare idempotentHint=true and destructiveHint=false, but the description adds meaningful behavior: funding is platform-executed, access costs 0.01 USDC/query, and a free preview is available via data_preview. This supplements the annotations with real-world side-effect and pricing context without contradicting them.
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 tight sentences that front-load the core purpose, then add cost and workflow details. Every clause adds value, and the specific listing/cost information is concrete rather than filler.
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 single-parameter tool with complete schema coverage and strong annotations, the description supplies the essential workflow context (preview, then fund, then query). It does not describe the return value, but the absence of an output schema makes this a minor gap for such a simple action.
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?
Schema coverage is 100% and the schema already explains session_id as the UUID from data_session_open. The description adds no additional parameter-level meaning, so the baseline of 3 applies.
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 action ('Buy per-query access') and resource (live data listings), and names the downstream tool data_session_query. It does not explicitly differentiate this from the sibling funding-related tools data_session_funding_package or data_session_attach_escrow, so it stops short of full sibling distinction.
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 implies a workflow: try data_preview first for free, then fund, then use data_session_query. However, it does not state when to prefer this tool over data_session_funding_package or data_session_attach_escrow, nor any exclusions, so usage guidance is inferred rather than explicit.
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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Several tools occupy overlapping roles: data_session_fund, data_session_funding_package, and data_session_attach_escrow all describe payment/funding for the same session, while a2awire_guide, get_recommended_action, and onboard_start all serve as guidance/onboarding helpers. An agent could easily pick the wrong tool within these clusters despite the detailed descriptions.
Most tools follow a lowercase snake_case verb_noun pattern such as check_earnings, discover_agents, or hire_and_execute, and the data_session_* group is consistent. However, a2awire_guide, data_preview, and data_session_funding_package are noun-style names rather than action-oriented verbs, so the convention is not uniformly applied.
Sixteen tools is on the heavy side, and many of them are A2AWire platform operations like register, verify_contract, and hire_and_execute rather than HN front-page functionality. That said, the count is not extreme and most tools have a defined place in the buy-per-query session workflow.
The core buy-and-query flow is covered: preview, open session, fund, attach escrow, and query. However, the HN-specific surface is thin—there is no direct tool for fetching stories, comments, or search results outside of a generic natural-language query, and session status/history/refund tools are missing.