Skip to main content
Glama

ffpipe — video conversion, probe & frames

by dev.ffpipe

Request a capability / report a problem (free)

leave_feedback

Tell us what you needed. If ffpipe does not offer the operation you came for - another output format, extracting a frame, a different transformation entirely - say so here: these requests are aggregated and they drive directly what gets built next, so a one-line "I wanted X" is genuinely useful to us. Also the place for bug reports and any other feedback. Free, unauthenticated, and one-way: nothing is returned but an acknowledgement, and no job is created. Include jobId if a specific job prompted this (context only - it is not checked and is not required), and contact if you want a reply. Message limit 2000 characters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoWhat this is: "feature_request" for a capability ffpipe does not offer yet, "bug" for something broken, "feedback" for anything else. Defaults to "feedback".
jobIdNoOptional job id this relates to. Context only - ownership is NOT checked and no token is needed.
contactNoOptional. An email or handle to reply at, up to 200 characters. Omit it and the submission stays anonymous.
messageYesWhat you wanted, what went wrong, or what you think. Plain text, 1 to 2000 characters. Be concrete: "needed a single frame as a jpeg at a given timestamp" is worth more to us than "more features".

TDQS

A4.9/5.0
Behavior5/5

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

The annotations provide minimal behavioral hints (none are true), so the description carries the full burden. It explicitly states this is free, unauthenticated, one-way, returns only an acknowledgment, and creates no job. This provides comprehensive transparency about the tool's behavior beyond the annotations.

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 densely informative with every sentence adding value: it explains the why, when, and how, plus constraints and side effects. It front-loads the core intent and progressively adds detail, achieving high conciseness without waste at 4 sentences.

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?

Given the tool's simplicity (4 params, no output schema, no nesting) and the rich annotations coverage, the description fully explains the tool's purpose, constraints, and outcomes. No gaps remain—the agent can correctly select and invoke it without additional information.

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?

Schema coverage is 100%, so the baseline is 3. The description adds value by further contextualizing jobId as 'not checked and not required' and describing the message length limit. It reinforces the parameter meanings from the schema, though it doesn't add entirely new semantics, so 4 is appropriate.

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 clearly states the tool is for requesting capabilities, reporting problems, or giving feedback. It uses specific verbs like 'tell us what you needed' and 'report a problem,' and distinguishes it from sibling tools like convert_video or extract_frames by positioning it as a non-operation feedback mechanism.

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

Usage Guidelines5/5

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

The description explicitly explains when to use this tool instead of others: when ffpipe lacks a desired operation, for bug reports, or other feedback. It also tells users to include jobId for context and contact for a reply, providing very clear usage guidance with no ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All ffpipe — video conversion, probe & frames toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources