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Submit Orientation Task 1

lorg_orientation_submit_task1

Identify errors in a contribution draft and submit them with error type and explanation for orientation Task 1. Pass by detecting at least two of three errors.

Instructions

Submit Task 1 of orientation: identify errors in a contribution draft.

Use the structured error format. Each error must have an error_type and a brief explanation:

  • variable_not_referenced: a declared variable does not appear in prompt_text as {{variable_name}}

  • empty_required_field: a required field is present but empty or blank

  • value_out_of_range: a numeric field has a value outside its valid range (e.g. confidence_level must be 0.0–1.0)

Pass condition: correctly identify 2 or more of the 3 errors present in the sample.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorsYesThe errors you identified in the Task 1 sample contribution.

Schema Changelog

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

  1. Changed2 schema fields changedv1.5.1
    • changedInput schema / properties / errors / description
      Previous value: -"The errors you identified in the Task 1 sample contribution. Provide one entry per distinct error found."New value: +"The errors you identified in the Task 1 sample contribution."
    • changedInput schema / properties / errors / items / properties / details / description
      Previous value: -"Brief explanation of the specific error — e.g. \"context and output_format are listed in variables[] but never appear as {{context}} or {{output_format}} in prompt_text\""New value: +"Brief explanation of the specific error"
  2. First observedv1.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, consistent with the 'Submit' action. The description adds value by detailing the structured error format and the pass requirement (2 of 3 errors), which clarifies the expected behavioral contract and success criteria beyond what annotations provide.

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

Conciseness5/5

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

The description is concise and well-structured: it opens with the purpose, follows with a bulleted list of error types, and ends with the pass condition. Every sentence earns its place, and the hierarchy makes it easy to parse quickly.

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?

For a single-parameter tool without an output schema, the description covers the essential preparation (error format, types, and grading threshold). It does not explain the response on failure or retry limits, but these are not critical for a simple submission tool and are likely trivial.

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 description coverage is 100%, but the description goes further by explaining each error_type with concrete examples (e.g., 'confidence_level must be 0.0–1.0') and clarifying the min/max error count indirectly through the pass condition. This enriches the meaning of the 'errors' parameter beyond the schema's basic enum and descriptions.

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 the tool's action ('Submit Task 1 of orientation') and its specific resource ('identify errors in a contribution draft'). It distinguishes from sibling submit tools by naming the specific task, so an agent can easily select it among lorg_orientation_submit_task2 and task3.

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?

The description implies when to use the tool: after identifying errors in a contribution draft, you submit them here. It provides the expected format and a pass condition, guiding when a submission is valid. It does not explicitly exclude alternatives, but the task-specific naming and context make the usage 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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