Return entities added or updated since a given ISO date for a chosen source list. The four official lists do not all expose a public delta feed, so this filters the cached snapshot by listedOn.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum matches to return. Defaults vary per tool. | |
| since | Yes | ISO date string (e.g. 2026-01-01) to compute the delta from. | |
| source | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable non-obvious behavior: the tool filters a cached snapshot by listedOn because not all official lists expose a public delta feed, which sets expectations about data freshness and implementation.
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 sentences with no filler. The core purpose is front-loaded, and the second sentence efficiently conveys an important implementation caveat. Every clause earns its place.
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 simple filtered list tool, the description, schema, and annotations together cover the required parameters, source enum, read-only behavior, and data-source caveat. There is no output schema, so return shape is not described, and pagination/default limit behavior is not detailed, but this is sufficient for correct invocation in most cases.
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 67%, with since and limit already described. The description adds the 'listedOn' filter concept, which helps explain the semantics of the delta mechanism. It does not materially enrich the limit parameter or provide additional date-format details beyond the schema.
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 states a specific verb and resource: 'Return entities added or updated since a given ISO date for a chosen source list.' This clearly differentiates the tool from sanctions_get_entity, sanctions_screen_*, and sanctions_search_alias by focusing on delta changes over time. It is immediately obvious what the tool does and how it is distinct among the sanctions siblings.
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 first sentence makes the intended use case clear: retrieving entities added or updated since a date for a chosen source list. It does not explicitly name alternatives or give when-not-to-use guidance, but the context is strong enough that an agent can infer this is the delta/changes tool.
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.
Many tools overlap heavily across domains: caselaw_search vs court_case_search vs court_opinion_search, caselaw_citation_lookup vs court_citation_resolver, and a cluster of company due-diligence tools (company_trust_check, counterparty_risk_score, entity_dossier, issuer_diligence_dossier, kyb_aml_evidence_case_file) that all screen a company for sanctions/risk/standing. With 290 tools, an agent will frequently face multiple equally plausible choices for the same user intent.
The vast majority of tools follow a clean domain-prefix + snake_case pattern (census_, eia_, fmcsa_, npi_, cfpb_, etc.), but there are notable exceptions: entity_resolve and resolve_entity are reversed duplicates, reg_search (Federal Register) sits next to reg_cfr_search (CFR) with confusingly similar names, and carrier_monitor_recheck deviates from the carrier_vetting_* family.
290 tools is an extreme count under any rubric, far exceeding even the 50+ threshold for the lowest score. While the group-filtering mechanism and meta-tools like list_tool_groups and search_available_datasets mitigate the practical burden, the raw surface is still massively oversized for an agent to select from accurately and efficiently.
For a read-only data-aggregation server, coverage is remarkably comprehensive across 59 domains, and generic fallbacks like cdc_dataset_query, eia_series_lookup, fred_observations, and bls_series prevent most dead ends. Minor gaps exist (a single GitHub tool, demo-only property_lookup coverage, no write/update operations anywhere), but the stated data-access purpose is well served.