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Glama

slideshow_from_images

Converts an ordered list of PNG/JPG images into a GIF, MP4, or WebP slideshow with adjustable timing and dimensions.

Instructions

Build a slideshow (gif/mp4/webp) from PNG/JPG images, in order.

With preset torch and seconds_per_image 0.2 the output is the pre-training form: five 1-bit grey frames per second, legible for text- and code-rich images at a few hundred bytes a frame.

Input Schema

NameRequiredDescriptionDefault
dpiNo
fpsNo
heightNo
imagesYes
outputYes
presetNotorch
db_pathNo
verboseNo
ffmpeg_dirNo
timeout_secondsNo
seconds_per_imageNo
reference_width_inchesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.4

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. It discloses output characteristics (five 1-bit grey frames per second, a few hundred bytes per frame) but says nothing about the long default timeout (7200s), ffmpeg dependency, whether an existing output file is overwritten, or what happens on partial failure.

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?

Short and front-loaded: the core capability is the first sentence and the tuning guidance follows. The second paragraph is dense but not padded; it lacks a short label tying it to the parameters it describes.

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?

For a 12-parameter tool with no annotations and no output schema, the description is thin. It explains one preset recipe but leaves the agent without enough information to set the other ten parameters or anticipate runtime and failure behavior.

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% across 12 parameters, so the description must compensate. It only gives semantic meaning to two of them (preset and seconds_per_image); images, output, dpi, fps, height, db_path, verbose, ffmpeg_dir, timeout_seconds and reference_width_inches are entirely undocumented.

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?

States a clear verb and resource ('Build a slideshow') plus the supported output formats (gif/mp4/webp) and input formats (PNG/JPG), with ordering behavior noted. It does not distinguish itself from the likely-overlapping sibling convert_media, so it falls short of a 5.

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

Usage Guidelines3/5

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

The preset/torch sentence implies a specific use case (the 'pre-training form' for text- and code-rich images), which is useful context. But there is no explicit when-to-use guidance, no statement of when not to use it, and no reference to the closely related convert_media or list_presets siblings.

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