AML regulatory benchmarks — FinCEN SAR filing rates, OFAC SDN counts and recent additions, BSA enforcement fine history, travel rule thresholds, and compliance staffing benchmarks. For compliance agents and financial institution risk officers.
| Name | Required | Description | Default |
|---|---|---|---|
| focus | No | ||
| institution_type | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful context about the specific data domains included (FinCEN, OFAC, BSA, travel rule, staffing), which goes beyond the annotations and helps the agent understand the tool's scope. However, it does not disclose return format or potential limitations, which would warrant a 5.
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 a single, concise sentence that front-loads the key concept ('AML regulatory benchmarks') and efficiently lists content areas and audience. No wasted words or redundant information.
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 has two optional enum parameters and no output schema. The description provides a good high-level overview of the data content, but it lacks parameter explanations and usage guidance relative to sibling tools. Given the moderate complexity and the absence of an output schema, the description is adequate but leaves clear gaps in parameter semantics and usage context.
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 description coverage is 0%, so the description carries the burden for explaining the parameters. It does not mention 'focus' or 'institution_type' at all, leaving the agent to rely solely on the enum names in the schema. While the enum values are somewhat self-explanatory, the description adds zero value for parameter understanding, making this a notable gap.
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 identifies the tool as providing AML regulatory benchmarks and lists specific data categories (FinCEN SAR filing rates, OFAC SDN counts, BSA enforcement fines, travel rule thresholds, compliance staffing). This distinguishes it from sibling benchmark tools like get_bank_regulatory_benchmark by focusing on AML-specific content.
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 mentions a target audience ('For compliance agents and financial institution risk officers') but provides no guidance on when to use this tool versus alternatives. It does not state exclusions, prerequisites, or compare it with other regulatory benchmark tools, leaving the agent to infer usage from the name and content list.
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.
Multiple tools have overlapping purposes, e.g., get_inflation_benchmark and get_bls_inflation_components, get_commodity_benchmark and get_agricultural_commodity_benchmark. Descriptions provide some differentiation, but many benchmark tools cover similar domains, leading to high potential for misselection.
All tools follow a consistent 'get_' prefix with snake_case nouns, e.g., get_inflation_benchmark, get_ma_multiples_benchmark. No mixing of conventions or irregular naming patterns.
46 tools is excessive for a server focused on financial benchmarks and intelligence. While the domain is broad, many tools could be consolidated. The high count may overwhelm agents and suggests insufficient scoping.
The toolset covers a wide range of financial data—benchmarks, regulatory filings, commodity prices—but lacks granular tools like individual stock prices or sector-specific indices. Some areas (e.g., credit unions) are well-covered, but other common financial operations (e.g., portfolio analytics) are absent.