Multi-source OSINT research pack — GDELT + BBC + HN + Reddit, 4-layer verification layer (existence+recency+multi-source+domain allowlist) + combined relevance scoring. research pack pipeline.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes | Research topic query | |
| domains | No | Optional domain filter allowlist | |
| hours_back | No | Hours back, default 24 | |
| include_sources | No | Sources to include: gdelt, bbc, hn, reddit |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. It discloses a 4-layer verification process and combined scoring but omits specifics like read-only nature, rate limits, or output structure. Adds some value but not enough for a higher score.
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 but redundant with 'research pack' repeated. Could be more concise by merging the trailing phrase. Adequate but not polished.
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?
No output schema, yet description fails to explain what the tool returns. Focuses entirely on process (verification layers) rather than result format (e.g., list of articles, scores). Leaves the agent guessing about the output.
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%, baseline 3. Description mentions sources and domain allowlist which map to parameters, but does not add meaningful extra syntax or constraints beyond what the schema provides.
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?
Description clearly identifies the tool as a multi-source OSINT research pack combining GDELT, BBC, HN, and Reddit. It mentions a verification layer and relevance scoring, distinguishing it from single-source siblings like reddit_search or hn_frontpage.
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?
Implies use for comprehensive cross-source research but lacks explicit when-to-use or when-not-to-use guidance. No alternatives or exclusions are mentioned, though the sibling tools provide obvious contrasts.
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.
Tools cover very diverse domains (weather, FDA, legal, crypto, etc.), so cross-domain confusion is low. However, within domains there is notable overlap: multiple food recall tools (food_recall_check, food_safety), multiple weather tools (weather_current_global, weather_forecast_grid, weather_alerts, weather_bias), and several Polymarket-related tools. This can cause agent misselection.
Naming is inconsistent: some tools use verb_noun (search_arxiv, scrape, validate_agent_manifest), others use noun phrases (smart_money, space_weather, tide_data), and some are long descriptive phrases (cross_platform_arb_scan, polymarket_event_scan). No single pattern is followed, making predictions difficult.
95 tools is excessively high for any coherent purpose. The server appears to be a random aggregation of APIs with no clear scope. Such a large catalog overwhelms agents and dilutes utility; most tools could be split into specialized servers.
Although many domains are touched, each is covered only shallowly. For example, weather lacks historical data, legal lacks case details beyond court opinions, and financial lacks stock prices. There are obvious gaps like no user authentication or data persistence. The tool set feels like a collection of endpoints rather than a cohesive service.