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Gmail

by io.github.pipeworx-io

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Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

TDQS

A4.7/5.0
Behavior5/5

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

Annotations provide basic hints (idempotent, not destructive, not read-only). The description adds valuable behavioral details: key-value pair scoped by identifier, persistence differences (authenticated vs anonymous, 24-hour retention), and pairing with companion tools. No contradictions 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?

Four sentences with no filler. First sentence states purpose, second covers usage, third adds technical context, fourth mentions companion tools. Efficient and well-structured.

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?

Given the tool's simplicity (2 parameters, no output schema), the description is complete: it covers purpose, when to use, behavioral traits, parameter semantics, and interaction with related tools. No gaps.

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?

Schema coverage is 100% with descriptions for key and value. The description adds meaning beyond the schema by explaining scoping and providing example key formats ('subject_property', 'target_ticker'), which aids selection and invocation.

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's purpose: 'Save data the agent will need to reuse later' and provides specific examples like resolved ticker, target address, user preference. It distinguishes from sibling tools recall and forget by mentioning them explicitly.

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 explains when to use ('discover something worth carrying forward') and pairs with recall/forget. Although it doesn't give explicit when-not scenarios, the context is clear and sufficient.

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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