Latest published stories on the data economy (data markets, alt data, AI training data, licensing & legal, deals & funding). Each item includes the original source it cites.
| Name | Required | Description | Default |
|---|---|---|---|
| beat | No | Optional beat filter. | |
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. States content and source inclusion, but does not disclose ordering, pagination behavior, or rate limits. Adequate but sparse.
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?
Description is concise and front-loaded with the primary purpose. One sentence with bullet-like topic list, no wasted words.
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?
Missing output schema and no annotations. Describes content but not return format or structure. Adequate for a simple list tool, but could be more complete.
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 describes beat filter with enum values, and limit parameter with defaults. Description adds no extra meaning beyond schema. With 50% schema coverage, description should compensate but does not.
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?
Clearly states it returns 'latest published stories on the data economy' with specific topics, distinguishing from siblings like search_news and get_article. Includes detail that each item includes the original source.
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?
Usage is implied for browsing latest news, but no explicit guidance on when to use this tool versus alternatives like search_news for querying or get_article for specific articles.
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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Each tool has a clearly distinct purpose: fetching content, searching, interacting via notes, managing submissions/edits, and checking account details. Even get_open_questions and get_stale_claims target different needs.
Most names follow a verb_noun pattern (add_note, get_article, set_payout_details), but latest_news and my_earnings/my_standing deviate slightly. Overall consistent and readable.
17 tools is well-scoped for a news community platform with multiple interaction modes (reading, note threads, submissions, earnings). No tool feels superfluous.
Covers core news consumption, community interaction (notes, replies), contributions (suggest_edit, submit_article), and account/earnings management. No obvious gaps for the stated domain.