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ffpipe — video conversion, probe & frames

Get job status (free)

get_job_status
Read-onlyIdempotent

Free status lookup for a job accepted by convert_video / probe_media / extract_frames. Requires the job's ownership token - the t query parameter of the statusUrl returned at acceptance (store the whole statusUrl; it cannot be regenerated). Status goes [awaiting_upload ->] queued -> finished | error; awaiting_upload jobs report uploadExpiresAt but NEVER the uploadUrl (that credential is handed out exactly once, in the acceptance result); finished jobs carry resultUrl/thumbnailUrl/durationMs (served by this gateway, free to re-download within 24 hours of completion; GET them following redirects); a failed charged job carries retryVoucher. A bad token and an unknown jobId both answer not_found, deliberately.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYesJob id from the acceptance
tokenYesOwnership token - the `t` query parameter of statusUrl

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already signal readOnlyHint, idempotentHint, and destructiveHint. The description goes far beyond by detailing the status lifecycle (including awaiting_upload, queued, finished, error), explaining what each state returns (e.g., uploadExpiresAt, resultUrl, retryVoucher), and even noting that bad tokens vs unknown jobIds both return not_found deliberately. No contradictions.

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 a single dense paragraph that packs a lot of information without wasted words. It front-loads the purpose and token requirement, then efficiently covers the status lifecycle. While it's somewhat long, every sentence adds value, so it earns a high score for conciseness given the complexity.

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

Completeness5/5

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

Despite no output schema, the description fully documents what the response contains for each status (uploadExpiresAt, resultUrl, thumbnailUrl, durationMs, retryVoucher), including the 24-hour free re-download window and redirect behavior. It also covers edge cases like awaiting_upload not having an uploadUrl. For a tool with this complexity, the description is complete.

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

Parameters5/5

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

Schema coverage is 100% with descriptions for jobId and token. The description adds critical context: it explains that the token is the 't' query parameter of the statusUrl and warns that the token cannot be regenerated, which is essential for correct usage and not evident from the schema alone.

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 explicitly states it is a 'Free status lookup for a job accepted by' and lists three specific sibling tools (convert_video, probe_media, extract_frames), making the verb+resource highly specific and clearly distinguishing it from other tools.

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?

The description explains when to use the tool (after job acceptance), what is required (ownership token from statusUrl), and provides critical guidance on storing the token because it cannot be regenerated. It does not explicitly state when not to use it, but the context is clear enough for an agent to decide.

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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TDQS

A4.6/5.0
Disambiguation4/5

Each tool targets a distinct capability: convert_video, extract_frames, probe_media, get_job_status, get_balance, and leave_feedback are clearly separated. However, there is a minor overlap potential between convert_video and extract_frames for users wanting to get video stills, but descriptions clarify the difference well.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (convert_video, extract_frames, get_balance, get_job_status, leave_feedback, probe_media). The verbs are descriptive and the nouns clearly indicate the resource or action, making them predictable and easy to navigate.

Tool Count5/5

With 6 tools, the set is well-scoped for a video processing service. Each tool serves a core function: two for processing (convert, extract), one for analysis (probe), one for status tracking, one for account management, and one for feedback. No tool is superfluous, and the count feels proportional to the domain.

Completeness4/5

The toolset covers essential video operations: conversion, frame extraction, media probing, with robust status tracking and account management. Obvious gaps include the lack of a cancel_job tool for stopping queued jobs and no explicit download management tool beyond the 24-hour window, but the core lifecycle is well-covered.

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