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PhononX

Carbon Voice

by PhononX

run_ai_action_for_shared_link

Execute AI prompts on shared Carbon Voice links to analyze conversations or voice memos and generate responses in specified languages.

Instructions

Run an AI Action (Prompt) for a shared link. You can run an AI Action for a shared link by its ID or a list of shared link IDs. You can also provide the language of the response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
prompt_idYes
share_link_idsYes
languageNo
Behavior2/5

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

Annotations indicate this is not read-only and not destructive, but the description adds minimal behavioral context. It mentions the action runs on shared links and allows language specification, but doesn't disclose what 'running an AI Action' entails (e.g., processing, side effects, response format, or rate limits). With annotations covering basic safety, the description should do more to explain the tool's behavior.

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?

The description is two sentences, front-loaded with the core action, and avoids redundancy. Each sentence adds value: the first states purpose and inputs, the second adds optional language parameter. It's appropriately sized with minimal waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 3 parameters with 0% schema coverage, no output schema, and annotations only covering basic hints, the description is incomplete. It doesn't explain what 'running an AI Action' produces, error conditions, or how results are returned. For a tool that likely generates AI responses, more context on behavior and outputs is needed.

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?

Schema description coverage is 0%, so the description must compensate. It mentions 'prompt_id' (implied as AI Action ID), 'share_link_ids' (ID or list), and 'language' (response language), adding basic meaning. However, it lacks details on parameter formats, constraints, or examples (e.g., what a prompt_id looks like, valid languages). This partially compensates but leaves significant gaps.

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 action ('Run an AI Action'), the target resource ('for a shared link'), and the input methods ('by its ID or a list of shared link IDs'). It distinguishes from sibling 'run_ai_action' by specifying the shared link context, though it doesn't explicitly contrast them. The purpose is specific but could be more differentiated.

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?

The description provides no guidance on when to use this tool versus alternatives like 'run_ai_action' or 'get_ai_action_responses'. It mentions what you 'can' do but offers no context about appropriate scenarios, prerequisites, or exclusions. Usage is implied through parameter description only.

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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