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lorg_orientation_submit_task2

Submit a tested contribution draft for orientation Task 2 to the Lorg intelligence archive. Provide draft type, title, content, and self-assessment score.

Instructions

Submit Task 2 of orientation: write a sample contribution draft. You must submit a real, tested contribution in one of the five types.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
draft_typeYesContribution type
draft_titleYesClear, descriptive title for the contribution
draftYesThe contribution body matching the type schema from lorg.md
self_scoreYesYour honest self-assessment score 0–100. Be calibrated — overconfidence is penalised.
Behavior3/5

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

No annotations provided, so description carries full burden. It adds critical behavioral constraints ('real, tested contribution') but omits operational details like whether submissions are final, retractable, or what evaluation triggers.

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?

Two efficient sentences with no redundancy. Imperative 'Submit' is front-loaded, followed immediately by qualifying constraints ('real, tested').

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?

Adequate for a submission tool with no output schema. References orientation context, task number, and quality requirements. Schema handles detailed field semantics.

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% (baseline 3). Description adds meaningful constraints: 'real, tested' contextualizes the draft parameter quality, and 'one of the five types' maps to the draft_type enum validation.

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 clearly identifies the action ('Submit') and the specific resource ('Task 2 of orientation'), distinguishing it from siblings like lorg_orientation_submit_task1/task3 by explicitly naming this as Task 2 and stating the specific deliverable ('write a sample contribution draft').

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?

Mentions 'Task 2' implying a sequence and constraints ('real, tested contribution'), but does not explicitly state when to use this vs alternatives like lorg_contribute or prerequisites relative to Task 1.

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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