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WYRE-AI

avanan-legacy-mcp

by WYRE-AI

avanan_update_exception

Update an existing whitelist or blacklist entry by entity ID, adjusting match criteria and actions for email security exceptions.

Instructions

Update an existing whitelist or blacklist entry by its entity ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
excIdYesException entity ID.
commentNoWhy this exception exists.
excTypeYesException list: whitelist or blacklist.
subjectNoEmail subject.
senderIpNoSender IP address.
recipientNoRecipient email address.
senderNameNoSender display name.
linkDomainsNoLink domain(s) in the email body.
senderEmailNoSender email address.
actionNeededNoAction to apply on match (as accepted by the portal).
senderDomainNoSender domain.
attachmentMd5NoAttachment MD5 hash.
quarantineAllNoQuarantine all matches (blacklist).
senderClientIpNoSender client IP address.
matchOnlyFutureNoApply only to future emails.
subjectMatchingNo
ignoringSpfCheckNoIgnore SPF check for this exception.
recipientMatchingNo
linkDomainMatchingNo
senderNameMatchingNo
senderEmailMatchingNo
senderDomainMatchingNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.3.0

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only indicates that an update occurs; it does not disclose whether this is a partial update or full replacement, what happens to unspecified fields, error behavior, or response details. This is a significant gap for a mutation tool.

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?

A single sentence with no filler, front-loaded with the core action and target. Every word earns its place.

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

Completeness2/5

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

For a 22-parameter mutation tool with no annotations and no output schema, this description is far too minimal. It does not explain update semantics, the role of optional parameters, whether existing values are overwritten or merged, or what response to expect. An agent would need to infer too much.

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

Parameters2/5

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

Schema description coverage is 73%, so the schema does most of the parameter documentation work. The description only restates the concept of whitelist/blacklist and entity ID, adding no meaning beyond the schema. It also does not compensate for the several parameters that lack schema descriptions, such as the matching-mode fields.

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 states a specific verb ('Update'), a precise resource ('existing whitelist or blacklist entry'), and the key identifier ('entity ID'). It clearly distinguishes this tool from siblings like add_exception, delete_exception, get_exception, and list_exceptions.

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: use it when you have an existing exception ID and want to modify that entry. However, it does not explicitly name alternatives or state when not to use it, so the guidance is implied rather than explicit.

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