get_data_tracker
The Data Economy Tracker: auto-computed, dated statistics on news flow per segment, source-outlet diversity, and latest analysis columns. Citable.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
The Data Economy Tracker: auto-computed, dated statistics on news flow per segment, source-outlet diversity, and latest analysis columns. Citable.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. States the tool is 'auto-computed' and 'citable', implying read-only and stable. Lacks explicit statement of no side effects or authentication needs, but adequate for a typical data retrieval tool.
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?
Single sentence, front-loaded with the core identity, uses specific terms without waste. Every element ('auto-computed', 'dated', 'citable') adds value.
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?
Covers the tool's contents and nature but omits output format details (no output schema). For a simple read tool with no parameters, this is nearly complete; a slight gap on what the returned data looks like.
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?
Input schema has no parameters (schema coverage 100%). Baseline 4 applies. Description adds no param info, but none needed. Implicitly clear that tool returns a fixed dataset without inputs.
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?
Describes the specific resource ('Data Economy Tracker') and its contents with precise terms: auto-computed, dated statistics on news flow per segment, source-outlet diversity, and latest analysis columns. Distinguishes from sibling tools like get_leaderboard or get_beats by its unique focus.
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?
No explicit when-to-use or when-not-to-use guidance. The purpose is implied for obtaining the tracker, but no alternative tools are suggested or excluded. Given siblings like get_beats and get_leaderboard, some differentiation would help.
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: 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.