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Glama

Sanctions Screening

by dev.hatchloop

preview_cost

Read-onlyIdempotent

Return an expected cost estimate, latency estimate, and success-probability estimate for a proposed call before execution. Returns the exact price when it is fixed, and a min/max range when the cost depends on channel or outcome. It does not promise an accuracy percentage - check cost_range.

EXAMPLE USER QUERIES THAT MATCH THIS TOOL: user: "How much will this SMS cost me?" -> call preview_cost({"operation": "send_message", "params": {"preferred_channel": "sms"}}) user: "Estimate the cost of booking via voice fallback" -> call preview_cost({"operation": "schedule_appointment", "params": {"preferred_channel": "voice"}})

WHEN TO USE: Use before any operation when the agent is operating under a budget constraint and needs to decide whether to proceed. WHEN NOT TO USE: Do not use in a hot loop — cache the result for at least 60 seconds if repeating the same preview. COST: free - no key required LATENCY: ~100ms

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYesThe same request body you would pass to the operation
operationYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark the tool read-only/idempotent/non-destructive, and the description adds what the tool returns (exact price vs. min/max range), the cost_range caveat, and free/no-key plus ~100ms latency. This is meaningful behavioral context beyond the structured annotations, and nothing contradicts them.

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 front-loaded with a one-sentence purpose, then uses labeled sections (examples, when to use/not use, cost, latency) so an agent can scan efficiently. Each section carries distinct information and there is no redundancy.

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

Completeness5/5

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

For a simple, well-annotated, two-parameter preview tool without an output schema, the description supplies return behavior, caveats, examples, cost, and latency. The only minor absence is a formal definition of supported operation names, but the examples and 'same request body' instruction make it sufficient.

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

Parameters4/5

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

With only 50% schema coverage (params described, operation not), the description compensates with two fully worked invocation examples using 'send_message' and 'schedule_appointment' with preferred_channel. It clarifies that params are the same request body as the operation, but it does not enumerate valid operation names or per-operation required fields, so compensation is good but not exhaustive.

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 first sentence identifies a specific action ('Return... estimate') for a specific object ('a proposed call before execution'), and the exact-price vs. min/max range detail makes the tool's function unmistakable. No sibling tool (check_compliance, get_outcome, get_status, etc.) appears to overlap with cost estimation, so it is clearly differentiated.

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

Usage Guidelines5/5

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

Explicit 'WHEN TO USE' and 'WHEN NOT TO USE' sections condition the tool on budget constraints and advise caching to avoid hot-loop abuse. Example user queries map natural language to concrete tool calls, making selection unambiguous. No alternative tool is cited because none of the siblings address cost preview.

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

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TDQS

A4.4/5.0
Disambiguation3/5

Most tools target distinct actions, but screen_sanctions and map_trade_restriction both screen parties against OFAC/EU/UK sanctions lists, so the same party-screening request could plausibly route to either. check_compliance also uses a broad 'compliance' name, though its messaging-specific parameters help separate it. The detailed descriptions largely mitigate the ambiguity, but the overlap is real.

Naming Consistency4/5

Seven of eight tools follow a clear snake_case verb_noun pattern (check_compliance, get_status, screen_sanctions, verify_company_record). self_test breaks the pattern as a noun-style name rather than an imperative verb_noun, but it remains lowercase and readable. Overall naming is predictable and consistent.

Tool Count5/5

Eight tools is a well-scoped size for a compliance/screening service, and each tool has a distinct operational role. The supporting helpers (get_status, get_outcome, preview_cost, self_test) are justifiable parts of the full workflow rather than padding.

Completeness4/5

Core due-diligence workflows are covered: sanctions screening, trade-restriction mapping, company verification, and messaging-compliance pre-flight. Notable exclusions such as the UN Consolidated List, PEP/adverse media, and bulk screening are explicitly disclosed rather than hidden, so agents can work around them. The gaps are more like optional enhancements than dead ends.

Resources