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Glama

Microsoft Todo

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

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint. Description adds that it returns top-N tools with full schemas and curated examples, ready to call directly, without contradicting annotations.

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?

Well-structured with front-loaded purpose, examples, return details, and usage guidance. Slightly long but each sentence adds value; no waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 parameters, no output schema, but description explains returned content (names, descriptions, schemas). Missing security or rate limit info but acceptable.

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 coverage is 100% with descriptions for all 6 parameters; description adds natural language context and aliases but doesn't significantly extend meaning.

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 specific verb 'find' and resource 'tools', and lists many domains. It clearly distinguishes itself from sibling tools as the discovery mechanism, not a task-specific tool.

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 states 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' Provides clear when-to-use and implies when-not-to (already know tool).

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
Disambiguation1/5

The set is dominated by overlapping Pipeworx and prediction-market tools, with ask_pipeworx and ask_pipeworx_beta explicitly described as currently identical, and ask_pipeworx_grounded, deep_research, and discover_tools serving heavily overlapping lookup purposes. The four Microsoft To Do tools are buried among 31 unrelated tools, making it very hard for an agent to select the right tool for the server's apparent domain.

Naming Consistency2/5

Most names are snake_case, but the naming conventions are otherwise mixed: there are verb_noun tools like list_tasks and get_task, bare verbs like remember/forget/recall, prefixed families like polymarket_*, and noun-phrase names like entity_profile, recent_changes, and pipeworx_trending. The lack of a consistent pattern across the set, especially relative to the Microsoft To Do server name, makes naming unpredictable.

Tool Count1/5

35 tools is already heavy, but the bigger problem is that only 4 of them are for Microsoft To Do, the server's stated name and purpose. The remaining 31 tools belong to unrelated Pipeworx data, prediction-market, and memory-management domains, which is an extreme scope mismatch.

Completeness1/5

For a Microsoft To Do server, the surface is severely incomplete: list_task_lists, list_tasks, get_task, and find_due_tasks cover reading and browsing only, with no create, update, complete, or delete operations. Even the broader Pipeworx functionality is scattered and redundant rather than forming a coherent domain surface.

Resources