Return the last N days of NorthPoint's competitor + regulatory + narrative signal feed. Daily-rebuilt digest of what moved in crypto marketing/regulation.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Lookback window in days (default 7, max 90). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It adds context about the feed's content (competitor, regulatory, narrative) and that it is 'Daily-rebuilt,' but it does not disclose the return format, pagination, potential rate limits, or whether the operation is read-only. This leaves significant gaps for a tool that likely returns a non-trivial dataset.
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 concise: two sentences that front-load the action and resource, with no filler words. Every sentence adds value—first defines the core function, second clarifies the feed's nature and content.
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?
The tool is simple (1 parameter, no nested objects, no output schema), and the description provides sufficient context about the feed's content and time window. However, without an output schema, a brief note about the return shape (e.g., 'returns a list of signals') would improve completeness. As is, it is adequate for the tool's simplicity.
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 description covers 100% of the single parameter 'days,' including default, minimum, and maximum. The description's phrase 'last N days' aligns with the schema but adds no extra meaning. Since schema coverage is high, the baseline of 3 is appropriate.
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 action: 'Return the last N days of NorthPoint's competitor + regulatory + narrative signal feed.' It specifies the resource (signal feed) and the scope (time window), and the mention of 'Daily-rebuilt digest' distinguishes it from sibling tools like search_signals, which likely performs searches rather than serving a feed.
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 clear use case: retrieving recent signal feed data. However, it does not explicitly state when to prefer this tool over alternatives like search_signals or other run_* check tools. There is no mention of exclusions or contrasting scenarios, so the guidance is moderately implied but not fully explicit.
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 targets a distinct resource or action: signal retrieval, search, ruleset listing, and regime-specific audits. The run_*_pro_check tools are parallel but clearly differentiated by jurisdiction names, and get_latest_signal vs search_signals serve different purposes.
All tool names follow a consistent verb_noun pattern with lowercase and underscores. The verbs get, list, search, and run are used predictably, and the run_*_pro_check pattern is uniform across all audit tools.
13 tools is well within the ideal 3-15 range and each tool earns its place for a marketing compliance server. The count covers discovery (list_regimes), free resources (get_lite_ruleset), signal monitoring, and comprehensive audits across multiple jurisdictions and specialized checks.
The tool set provides thorough coverage of the marketing compliance domain: free ruleset for self-audit, full pro checks for major regulatory regimes (EU, UK, US, Singapore, UAE), specialized audits for ad creative, AEO visibility, and TGE readiness, plus signal feed access and search. No obvious gaps or dead ends exist.
