render_cancel
Cancel a queued video render job or kill the running ffmpeg process to halt output immediately.
Instructions
Cancel a queued job, or kill its running ffmpeg.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes |
Cancel a queued video render job or kill the running ffmpeg process to halt output immediately.
Cancel a queued job, or kill its running ffmpeg.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It transparently signals destructive behavior via 'kill,' and it distinguishes between canceling a queued job and killing a running process. However, it does not disclose consequences like whether partial output is cleaned up, whether cancellation is idempotent, or what error occurs for an unknown job_id.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short clauses with no filler. Every word contributes meaning: the action, the object, and the two distinct operational states are all front-loaded and immediately scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter cancellation tool, the description is nearly complete. It tells the agent what the tool does and which state it affects. The main gaps are return/error behavior and job_id provenance, but the simplicity of the tool makes those less critical; there is no output schema to complicate interpretation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description should compensate by explaining the parameter. It never mentions job_id or where to obtain it (e.g., from render_start), leaving the parameter's meaning almost entirely to inference from the tool name and purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific action verb ('Cancel'/'kill') with a concrete resource ('a queued job'/'its running ffmpeg'), clearly differentiating render_cancel from render_start, render_status, and render_history. The queued-vs-running distinction adds useful precision.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool: when a job is queued and should be canceled, or when it is running and its ffmpeg process should be killed. However, it does not explicitly name alternatives or state exclusions, such as what to do for already-completed jobs, so an agent must infer the routing from sibling names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.