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DarkLvrd

agentic-linkedin

by DarkLvrd

Dry-run actions

dry_run

Preview planned LinkedIn actions and their expected outcomes without storing data or allowing approvals. Validate automation steps before executing them.

Instructions

Produces the same plan and previews as plan, but nothing is stored and nothing can be approved.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionsYes
Behavior4/5

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

With no annotations, the description must carry behavioral disclosure on its own. It clearly states the key side-effect-free behavior: nothing is stored and nothing can be approved. It does not cover authentication or error behavior, but for a dry-run the critical guarantees are present.

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?

Only one sentence; the key non-storage/approval caveat is front-loaded. No filler.

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 no output schema and no annotations, the description should do more. It adequately explains behavior and outcome ('same plan and previews as plan'), but lacks any mention of how to structure `actions` or what the preview output contains. It is minimally viable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The `actions` parameter is not mentioned in the description, and schema description coverage is 0%. The agent must rely on the raw schema (array of tool/args objects with an enum) without any guidance on how actions relate to 'plan', ordering, or validation semantics.

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 states a specific verb ('Produces') and resource ('same plan and previews as plan'), and immediately differentiates itself from the sibling 'plan' by noting nothing is stored or approvable. This leaves no ambiguity about the tool's core role.

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?

It provides clear context by contrasting with 'plan' and explicitly stating that nothing can be approved, which signals safe preview use. It lacks an explicit 'use when' formula or list of when-not to use, but the contrast is enough to guide selection.

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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