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write_proposal

Write a learning proposal document to the workspace root for user review, enabling AI agents to suggest rules or skills based on session history.

Instructions

Write a learning_proposal.md file to the workspace root for user review.

Args: content: The full markdown content of the proposal. workspace_path: Optional path to the workspace root.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes
workspace_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations provided, so description carries full burden. It does not disclose overwrite behavior, error handling, permissions needed, or side effects beyond writing. Minimal behavioral disclosure.

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?

Description is short with an Args list. Could be more concise by integrating param descriptions into flowing text, but overall efficient and front-loaded.

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?

Output schema exists but not shown; description lacks key details like overwrite policy, success/failure conditions, and prerequisites. Not fully complete for a write tool.

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 has 0% description coverage, but the description explains both parameters: content as full markdown and workspace_path as optional path. This adds significant meaning beyond the schema's type/title.

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 action (write), the specific resource (learning_proposal.md), and the location (workspace root). It is distinct from siblings which deal with customizations.

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 user review' implies use case but no explicit when-to-use vs alternatives or when-not-to-use. Siblings are about customizations, so context makes it usable but not explicit.

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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