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Glama

Todoist

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

Schema Changelog

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

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already indicate readOnlyHint, idempotentHint, etc. Description adds details about fallback from GDELT to GNews, soft-fail for patents due to API sunset, and the behavior of the `since` parameter. 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.

Conciseness4/5

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

The description is fairly long but front-loaded with examples. Every sentence adds value, though it could be slightly more concise. No 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?

No output schema exists, but the description explains the return structure: changes[] grouped by source, total_changes count, pipeworx:// citation URIs. This is sufficient for an agent to understand what to expect.

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 already provides 100% coverage with descriptions for all parameters. The description adds practical guidance for `since` (ISO date or relative shorthand, recommends '30d'), which is helpful but not essential given the schema.

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 provides a change feed for a company, combining SEC filings, news, and patents. It distinguishes itself from the sibling 'entity_profile' tool, which is for static profiles regardless of window.

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 when to use this tool vs. 'entity_profile' (use this for recent changes, entity_profile for static profile). Also gives example queries like 'What's new with X' and 'latest on Y', clarifying the use case.

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
Disambiguation3/5

Tools have overlapping purposes, e.g., 'ask_pipeworx' and 'validate_claim' both handle factual queries; 'bet_research' and 'polymarket_edges' both analyze betting markets. However, most tools target distinct domains (Todoist, data lookup, betting), so some separation exists.

Naming Consistency3/5

Naming uses snake_case and often follows verb_noun, but prefixes are inconsistent: some tools have 'todoist_', 'pipeworx_', 'polymarket_', while others like 'compare_entities' and 'discover_tools' lack prefixes. This mix reduces predictability.

Tool Count2/5

25 tools is high, and only 5 are Todoist-specific despite the server name. The inclusion of many unrelated tools (Pipeworx, betting, etc.) makes the set feel bloated and misaligned with the server's stated focus.

Completeness2/5

For Todoist, the set lacks create/update/delete operations, leaving gaps. For the broader data domains, coverage is extensive but unfocused. The server's purpose is unclear, leading to an incomplete surface for any single use case.

Resources