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Xero

by io.github.pipeworx-io

What Can I Ask Pipeworx?

suggest_questions
Read-onlyIdempotent

What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, government & patents, science & academia, news) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools. Call with no arguments for the full spread, or pass topic (e.g. "finance", "pharma", "betting") to focus. Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoOptional focus area: finance | pharma | economics | real-estate | betting | weather | government | science | news. Omit for a cross-category spread.

Schema Changelog

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

  1. Added

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already indicate readOnly, openWorld, idempotent, and non-destructive. Description adds that it returns example questions with tool shapes, which is useful behavioral context beyond annotations. No contradictions, but could mention that the tool has no side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph that front-loads the core purpose and includes all necessary details. While slightly verbose, it remains clear and efficient, earning its sentences.

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 (one optional parameter, no output schema), the description fully covers what the tool does, its return format, and when to use it. No gaps remain.

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

Parameters5/5

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

Schema coverage is 100% and description adds value by explaining the effect of omitting vs. providing the topic parameter (full spread vs. focused). The description clarifies semantics beyond the schema's brief description.

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 it is the onboarding entry point, returning category-bucketed example questions with exact tool + argument shapes. It distinguishes from siblings by being the first tool to use when the agent doesn't know what Pipeworx can do.

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?

Explicitly says 'Use this FIRST when you do not yet know what Pipeworx can do for you'. Also explains optional topic parameter to focus the results, providing clear when-to-use guidance.

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

A3.8/5.0
Disambiguation4/5

Most tools have distinct purposes, but there is some overlap (e.g., ai_visibility_check and scan_competitor_ai_presence are related; memory tools remember/recall/forget form a clear subgroup). Descriptions are detailed enough to differentiate, but the broad scope may cause occasional mis-selection.

Naming Consistency2/5

Naming is inconsistent: some tools use verb_noun (list_accounts, get_profit_and_loss), others are single words (forget, recall), and some use snake_case with mixed verbs (ai_visibility_check, ask_pipeworx, bet_research). No uniform pattern makes the set harder to navigate.

Tool Count3/5

25 tools is high but not extreme given the broad scope (accounting, betting, data queries, npm, memory, etc.). However, the server tries to cover too many domains, making it feel bloated. Each tool is individually useful, but the count is borderline excessive for coherence.

Completeness2/5

The Xero accounting subset is incomplete: only list and get operations, no create/update/delete for invoices, contacts, or accounts. Other domains (betting, npm) are covered well, but the core accounting purpose has significant gaps that will hinder agents.

Resources