Skip to main content
Glama

tasks_context

Creates a conversation-ready snapshot of all open tasks across every list, grouping overdue, upcoming, undated, later, and earlier-created items for prioritization and completion.

Instructions

Snapshot of all open tasks across every list for use as conversation context: overdue, due within days_ahead days, without a due date, later, and the open tasks Claude created earlier (candidates for automatic completion).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
days_aheadNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It does disclose the useful behavioral trait of which buckets are included and flags that agent-created open tasks are surfaced as completion candidates, but it says nothing about read-only safety posture, ordering, volume limits, or paging across all lists.

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?

A single dense sentence that front-loads the core purpose (snapshot of open tasks across every list) before enumerating buckets. No filler, though the bucket enumeration is compressed into a hard-to-parse list.

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

Completeness3/5

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

An output schema exists, so return shape needs no explanation, and the description adequately conveys what content is aggregated. The remaining gap is routing: with six sibling tools including list_tasks, the agent is left to infer when this snapshot is preferable.

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?

The single parameter days_ahead is undocumented in the schema (0% coverage), and the description only implicitly defines it as the window for the 'due within' bucket. It does not state the unit convention beyond 'days' or note that omitting it falls back to the default of 7.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource (open tasks across every list) and specifies the exact composition of the snapshot: overdue, due within a window, no due date, later, and agent-created tasks. This makes it distinguishable in substance from list_tasks, though it never explicitly contrasts itself with that sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'for use as conversation context' implies the scenario, and the parenthetical about automatic-completion candidates hints at a downstream action. However, there is no explicit guidance on when to choose this over list_tasks, nor any stated conditions or exclusions.

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