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Gmail

by io.github.pipeworx-io

Gmail List Messages

gmail_list_messages
Read-onlyIdempotent

List messages in your inbox with optional filtering by label or read status. Returns message IDs, thread IDs, and preview text. Use gmail_search for complex queries like date ranges or attachments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoGmail search query to filter messages (e.g., "from:alice subject:meeting")
page_tokenNoToken for fetching the next page of results
max_resultsNoMaximum number of messages to return (default 10, max 100)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoError code if connection not authenticated
messageNoError message if connection not authenticated
messagesNoArray of message summaries
nextPageTokenNoToken for fetching next page of results
resultSizeEstimateNoEstimated total number of matching messages

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and destructiveHint false, so the safety profile is clear. The description adds that the tool returns message IDs, thread IDs, and preview text, which is useful behavioral context beyond annotations. However, no additional constraints like pagination limits or rate limits are mentioned.

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, perfectly front-loaded: first sentence states the core functionality and output, second sentence provides usage guidance for an alternative. No wasted words.

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 list tool with 3 optional parameters and existing output schema, the description covers what the tool does, what it returns, and when to use an alternative. Combined with rich annotations and schema, this is fully complete.

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 100%, so the schema already documents all three parameters. The description mentions filtering by label or read status, which overlaps with the schema's query parameter description. While the description adds a user-friendly summary, it doesn't significantly enhance understanding 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 clearly states the tool lists messages in the inbox with optional filtering by label or read status. It contrasts with gmail_search for complex queries, distinguishing the tool's specific purpose. The verb 'list' and resource 'messages' are specific and unambiguous.

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?

The description explicitly directs to use gmail_search for complex queries like date ranges or attachments, providing a clear when-not-to-use scenario and an alternative tool. This gives excellent guidance on tool selection among siblings.

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

B3.4/5.0
Disambiguation2/5

There is significant overlap among tools, particularly within the Pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and the Polymarket family (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread). These tools have similar purposes, making it hard for an agent to distinguish them at a glance. The Gmail tools are a small, distinct cluster, but the overall set is confusing.

Naming Consistency3/5

All tool names use snake_case, but the verb_noun pattern is inconsistent. Many start with verbs (ask_pipeworx, compare_entities, discover_tools, etc.), but some use noun_verb (bet_research), noun_noun (entity_profile), or adjective_noun (deep_research). This mixed pattern reduces predictability.

Tool Count2/5

With 36 tools, the count is high, but the server name 'Gmail' suggests a focused email service. Only 5 tools are Gmail-related, while the rest cover a vast, unrelated domain (Pipeworx, Polymarket, etc.). This mismatch makes the tool count inappropriate for the server's apparent purpose.

Completeness2/5

For the Gmail domain, the tool surface is incomplete (e.g., missing delete, archive, modify labels). For the broader Pipeworx/Polymarket domain, the tools are extensive but lack clarity in coverage. The server attempts to cover too many domains without sufficient depth in any, leading to notable gaps.

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