Skip to main content
Glama

law.sanctions-check

Fuzzy-match names against the US Treasury OFAC SDN list. Returns ranked matches with similarity scores and sanctions metadata.

Instructions

Fuzzy-match a name (person, company, vessel, aircraft) against the US Treasury OFAC SDN list. Returns ranked matches with similarity scores and sanctions program metadata. List refreshed daily.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYesName to screen.
thresholdNoSimilarity floor (0-1). Default 0.4; ≥0.85 flagged as high-confidence.
sourceListNoOptional source list filter (e.g. SDN).
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses fuzzy matching, ranked results with similarity scores, sanctions program metadata, and daily data refresh. This provides good transparency, though it omits details like pagination or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the action and resource, and every sentence adds value without redundancy. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity and lack of output schema, the description covers the return format (ranked matches, similarity scores, program metadata) and data freshness, making it fairly complete. Minor omission: no mention of how limit or threshold affect results, but threshold is described in schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 75% (3 of 4 parameters described). The tool description adds context about output (ranked matches, scores, metadata) but does not elaborate on parameter usage beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifies the verb 'fuzzy-match', the resource 'US Treasury OFAC SDN list', and the scope 'name (person, company, vessel, aircraft)', making the tool's purpose clear and distinct from sibling tools like business.entity-screen or law.case-search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for sanctions screening against the OFAC SDN list and mentions daily refresh, but does not explicitly state when to use this tool over alternatives or provide exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/2s-io/sdk'

If you have feedback or need assistance with the MCP directory API, please join our Discord server