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Glama

Bounce

bounce
Read-onlyIdempotent

Fetch full details for a single Postmark bounce record by numeric id, including bounce type, recipient email, description, and raw bounce content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
IDNoBounce identifier
TypeNoBounce type (Permanent or Transient)
EmailNoBounced email address
DetailsNoBounce details message
InactiveNoWhether address is marked inactive
BouncedAtNoISO timestamp of bounce
DumpAvailableNoWhether message dump is available

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds useful context by specifying what the full details include (bounce type, recipient email, description, raw bounce content), giving the agent a better sense of the return payload. No contradiction with annotations.

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 a single, well-structured sentence. It leads with the verb, states the resource and qualifier, and lists contents. Every word earns its place with no redundancy or filler.

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 single-parameter fetch tool with an output schema and comprehensive annotations, the description is complete. It covers the action, object, input qualifier, and the nature of the returned data. No additional context (e.g., error conditions, rate limits) is necessary for this straightforward read operation.

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?

The schema has only a 'id' string property with no description (0% coverage). The description compensates by stating 'by numeric id', clarifying that the parameter expects a numeric identifier despite the schema type being string. This adds meaningful semantic value beyond the schema's bare type definition.

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 uses a specific verb ('Fetch') and clearly identifies the resource ('a single Postmark bounce record by numeric id'). It also lists the key fields returned (bounce type, recipient email, description, raw bounce content), making the tool's function unambiguous and distinguishing it from siblings like 'bounces' (list) and 'bounce_activate' (activation).

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

Usage Guidelines4/5

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

The description clearly implies usage context: fetch full details for a single bounce when you have a numeric id. However, it does not explicitly mention alternatives or exclusions (e.g., 'for listing bounces, use bounces'). The context is clear but lacks explicit when-not guidance, so it falls short of a 5.

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

B3/5.0
Disambiguation2/5

The tool set mixes multiple domains (Postmark email, Pipeworx data queries, Polymarket betting, memory utilities) with several overlapping tools. ask_pipeworx and ask_pipeworx_beta are essentially identical, send/send_batch and bounces/bounce are similar, and multiple polymarket analysis tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker) could be confused. Despite detailed descriptions, the sheer number of query and analysis tools increases the chance of misselection.

Naming Consistency3/5

All tool names use lowercase_with_underscores, so the casing is consistent. However, there is no uniform verb_noun pattern: some start with verbs (ask, send, bounce, resolve, validate), while others are noun phrases (server, bounces, recent_alerts, entity_profile). This mixed semantic structure makes it less predictable, but the names are still readable.

Tool Count2/5

41 tools is far above the typical well-scoped range of 3-15. The server combines multiple unrelated domains—email, data lookup, prediction markets, memory, and subscriptions—resulting in a heavyweight and unfocused surface. Most of the tools would be better split into separate, purpose-specific servers.

Completeness2/5

For a server named Postmark, the email side is incomplete: there is no update server configuration, message stream management, or inbound email handling. The Pipeworx data tools provide good read coverage but lack write/management operations for entities. The inclusion of unrelated tools makes the surface feel arbitrary rather than complete for any single domain.