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Get Task History

get_task_history
Read-only

Use this when you need what HAPPENED to a task, not just its current fields — before retrying failed work, judging a receipt, or answering 'why is this still open?'. Three modes: 'summary' (default, ≤500 tokens — the card, its latest receipt, and counts), 'decisions' (every decision recorded about it, including verdicts and their reasons — a rework's reason survives here after a later accept overwrites the card), 'full' (the raw journal, capped at 100 events and saying so).

Input Schema

NameRequiredDescriptionDefault
idYesTask ID
modeNoDefaults to 'summary'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / $schema
      Removed value: -"https://json-schema.org/draft/2020-12/schema"
  2. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  3. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnly/non-destructive/closed-world, and the description adds real behavioral context on top: the default mode's ≤500 token budget, the 'full' mode's 100-event cap and that it discloses the truncation, and the non-obvious fact that a rework reason survives in 'decisions' after a later accept overwrites the card.

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?

Front-loaded with the when-to-use condition, then a compact three-mode enumeration where each clause carries distinct information. The mode sentence is long and list-like, but no sentence is filler.

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?

With no output schema, the description carries the return-value burden and does it well — card, latest receipt, counts, verdicts with reasons, raw journal. Only a minor gap: nothing about ordering or whether results are scoped/paginated beyond the 100-event cap.

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% and the enum names the three modes, but the description adds meaning the schema cannot: what each mode returns, relative cost, and truncation behavior. That goes beyond baseline 3, though it does not document the id parameter's format (already covered by the schema pattern).

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 states a specific verb+resource (retrieve what HAPPENED to a task, its history) and immediately distinguishes it from current-state reads with 'not just its current fields'. An agent can separate it from list_tasks/update_task without opening a schema.

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

Usage Guidelines4/5

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

Gives concrete triggering scenarios — before retrying failed work, judging a receipt, answering 'why is this still open?' — plus per-mode selection guidance. It stops short of naming a specific sibling alternative (e.g., 'for current fields use list_tasks'), but the implied contrast is clear.

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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