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Glama

Onedrive

by io.github.pipeworx-io

Discover Tools

discover_tools
Read-onlyIdempotent

Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for query.
taskNoAlias for query.
limitNoMaximum number of tools to return (default 20, max 50)
queryYesNatural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries"). Accepts task, q, description, search as aliases.
searchNoAlias for query.
descriptionNoAlias for query.

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations declare readOnlyHint, idempotentHint, and no destructiveness. The description adds that results are 'ready to call directly, no second schema lookup needed,' which provides useful behavioral insight beyond the annotations. However, it does not elaborate on rate limits or pagination.

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 dense but well-structured. It starts with a concise purpose statement, then details return value, usage context, and parameter aliases. A minor improvement could be splitting into two shorter paragraphs, but it's informative without redundancy.

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 complexity of tool discovery, the description covers all necessary aspects: what it does, what it returns, when to use it, and parameter details. The absence of an output schema is adequately compensated by explaining the result format (names, descriptions, full schemas).

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%, so the baseline is 3. The description adds value by listing aliases for the query parameter (task, q, description, search) and explaining the limit parameter. This clarifies the flexible input format.

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: 'Find tools by describing the data or task.' It specifies the return value (top-N tools with full schemas) and distinguishes itself from sibling tools by being the discovery gateway to call first.

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?

Explicit guidance to 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' This tells the agent when to use the tool and provides context for prioritization.

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

All Onedrive toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

The set mixes near-synonymous routers (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded), overlapping discovery tools (discover_tools, suggest_questions), and several prediction-market scanners (polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_edge_tracker) whose boundaries are easy to blur. The six onedrive_* tools are distinct, but they are buried in an unrelated toolkit where multiple tools appear to address the same task.

Naming Consistency2/5

Naming is split across several conventions: onedrive_*, polymarket_*, and pipeworx_* form consistent clusters, but top-level tools use bare verbs (remember, recall, forget), noun phrases (entity_profile, compare_entities), and varied styles (deep_research, generate_llms_txt, validate_claim). The pattern is readable within clusters, but not predictable across the server.

Tool Count2/5

37 tools is heavy, and the vast majority have nothing to do with the server's name 'Onedrive' — only 6 of 37 target OneDrive, while 31 span Pipeworx data, Polymarket betting, memory, and web utilities. This is a sprawling multi-domain bundle rather than a focused server.

Completeness1/5

As a OneDrive server, the surface is severely incomplete: it offers read-only coverage (list, search, get, profile, shared) but no upload, create, update, move, copy, delete, or share operations, and binary Office/PDF content returns unreadable bytes. The Pipeworx tools are individually comprehensive, but they do not fill the basic lifecycle gaps for the server's apparent file-management domain.

Resources