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thebenlamm
by thebenlamm

moltbook_downvote_post

Downvote posts on the Moltbook social platform to express disagreement or decrease visibility. Use the force parameter to toggle off previous downvotes.

Instructions

Downvote a post.

Args: post_id: The post UUID to downvote force: Set True to intentionally toggle off a previous downvote

Returns: Vote result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
post_idYes
forceNo
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the 'force' parameter's toggle behavior, which is useful, but doesn't cover important aspects like authentication requirements, rate limits, side effects on post visibility or user reputation, error conditions, or what constitutes a successful downvote. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.

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 efficiently structured with a clear purpose statement followed by organized parameter and return value sections. Every sentence earns its place: the first states the core action, the Args section explains parameters concisely, and the Returns section acknowledges the output. No wasted words or redundant information.

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?

Given this is a mutation tool with no annotations and no output schema, the description provides adequate basic information but lacks completeness. It covers the core action and parameters well, but doesn't address authentication, error handling, side effects, or what the 'Vote result' actually contains. For a tool that modifies data, more behavioral context would be beneficial despite the concise structure.

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?

The description explicitly documents both parameters with meaningful explanations: 'post_id' as 'The post UUID to downvote' and 'force' as 'Set True to intentionally toggle off a previous downvote'. With 0% schema description coverage, this provides essential semantic context that the bare schema lacks. The explanation of the toggle behavior for 'force' is particularly valuable beyond basic parameter documentation.

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 states the verb 'downvote' and resource 'a post', making the purpose immediately understandable. It distinguishes from siblings like 'upvote_post' by specifying downvote action, though it doesn't explicitly contrast with other voting or post-modification tools beyond the obvious directional difference.

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

Usage Guidelines2/5

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

No guidance is provided about when to use this tool versus alternatives. While the name implies it's for downvoting (vs upvoting), there's no mention of prerequisites, appropriate contexts, or comparison to sibling tools like 'delete_post' or other post-modification options. The description simply states what it does without usage context.

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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