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task_evaluation_context

Read-only

Returns the data for evaluating a task stage when the user asks for a work evaluation, together with the workspace's evaluation rules for the task type and stage (rules: content and the rulesRevision an evaluation carries): spec and result, the stage assignee with level, rates, time and cost, plan and time by status, returns, bugs and regressions with fix cost, commits and the previous evaluation. Money requires task:costs for the task, otherwise null; null salary and bonus are hidden. Rates and amounts are for the assessment, not for the evaluation comment.

Input Schema

NameRequiredDescriptionDefault
IDNoTask ID; preferred over key.
keyNoTask number without #, if the ID is unknown.
stageNoStage: work - execution (default), review, or testing.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedInput schema / properties / key / maximum
      Removed value: -9007199254740991
    • removedInput schema / properties / key / minimum
      Removed value: --9007199254740991
  2. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already establish readOnly/non-destructive behavior, and the description adds real value on top: money fields require the task:costs permission else null, null salary and bonus are hidden, and rates/amounts are scoped to the assessment rather than the comment. These are concrete masking/permission behaviors not derivable from annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The information is valuable but delivered as one dense run-on sentence with a heavy parenthetical list of returned fields. It is not front-loaded into scannable units, though nothing is outright wasted.

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-shape burden and largely does so by enumerating spec/result, assignee, rates, plan-by-status, bugs, commits and prior evaluation. Permission-driven nulling is also covered, leaving only pagination/size behavior unaddressed.

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% and all three parameters (ID, key, stage) are documented in the schema with the ID-vs-key preference and the stage enum. The description adds no syntax or format detail beyond what the schema already provides, so the baseline 3 applies.

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?

States a specific verb ('Returns') and resource ('the data for evaluating a task stage' plus workspace evaluation rules), and enumerates the returned fields. An agent can tell this is a read-context helper, distinct from the write-oriented sibling task_evaluate, though the description never names that sibling to make the contrast explicit.

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?

Provides an implied trigger ('when the user asks for a work evaluation'), which is genuine but thin. There are no exclusions, no prerequisites, and no pointer to task_evaluate as the alternative for actually submitting an evaluation, so the routing decision is left to inference.

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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