kinocut

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

No annotations are supplied, so the description carries the full burden. It usefully documents the input shape and that the return is a dict with success/output_path, but it never states overwrite behavior for an existing output_path, error/failure semantics, or any sample-rate/channel constraints on mixing.

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?

Front-loaded with the core action, then Args/Returns blocks that are easy to scan. The first two sentences restate each other slightly ('layer multiple tracks with volume mixing' vs 'mix multiple WAV files with individual volume control'), which is the only waste.

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?

An output schema exists so return details need not be repeated, and the parameter documentation is thorough despite 0% schema coverage. The remaining gap is behavioral: with no annotations on a write tool that produces a file, overwrite and failure behavior should be stated.

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?

Schema description coverage is 0% and the tracks item schema defines no properties, so the description is the sole source of field semantics. It fully compensates by naming file (absolute WAV path), volume (0-1 multiplier), start (seconds offset), loop (default false), plus duration and output_path. It loses a point for not stating volume's default or whether duration must cover track starts plus lengths.

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 opens with a specific verb+resource pair ('Layer multiple audio tracks with volume mixing') and clarifies the concrete form ('Mix multiple WAV files together with individual volume control'). It is easy to tell apart from synthesis tools like audio_synthesize or effect tools like audio_effects, though it never explicitly names a sibling to route against.

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?

There is no when-to-use guidance, no prerequisites (do the source WAVs need to exist? same sample rate?), and no mention of alternatives such as audio_sequence or video_mix_audio. The agent must infer the appropriate context entirely.

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

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

With no annotations, the description carries the full behavioral burden. It discloses the write to output_path and the return shape (success status and output_path), which is genuine context, but says nothing about overwrite behavior, supported sample rates/format limits, permission requirements, or failure modes.

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?

Front-loaded purpose followed by clean Args/Returns sections that make it easy to scan. The second sentence ('Process audio through a chain of effects like reverb, filtering, normalization') largely restates the first and is the one redundant element.

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?

An output schema exists so return values needn't be explained, and parameter coverage from the description is good. However, for a three-parameter mutation tool with zero annotations and zero schema coverage, the absence of any usage or side-effect guidance leaves clear gaps an agent must guess around.

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?

Schema description coverage is 0%, so the description must compensate, and it does: it clarifies both paths are absolute and WAV-specific, and describes effects as a list of configs with a type field enumerating valid values (lowpass, reverb, normalize, fade). It stops short of spelling out the additional per-effect parameters, keeping it from a 5.

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?

States a specific verb+resource: applying an effects chain to a WAV file, and enumerates concrete effects (reverb, filtering, normalization). It's clear what the tool does, but it does not distinguish itself from audio-adjacent siblings such as video_filter, audio_preset, or video_normalize_audio, leaving differentiation to inference.

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?

Offers no when-to-use, when-not-to-use, or alternative-tool guidance. A caller cannot tell from the text whether to reach for audio_effects versus audio_compose, audio_sequence, or video_normalize_audio. Only implied usage from the purpose statement is available.

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

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

No annotations are provided, so the description carries the full burden. It does disclose the return shape ('Dict with success status and output_path') and that output goes to a WAV path, which is useful. But it omits side-effect detail such as what happens when output_path is null, whether an existing file is overwritten, and any permission or duration limits.

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?

Front-loaded with the purpose, then a compact preset catalogue and arg list. The preset enumeration is long but earns its place because the schema exposes no enum for preset. Slightly verbose formatting but no filler sentences.

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?

With an output schema present, the description need not detail return values, and it covers all parameters well. The remaining gap is behavioral edge cases (default behavior when output_path is null, overwrite semantics) and any routing guidance versus the many sibling audio tools.

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?

Schema description coverage is 0%, so the description must compensate, and it does: it enumerates all valid preset values, defines pitch as low/mid/high (an enum the schema lacks), explains duration as a seconds override, gives intensity's 0-1 range and default 0.5, and specifies output_path as an absolute WAV path. All five parameters are meaningfully documented.

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?

States a specific verb+resource ('Generate preset sound design elements') and clarifies with 'pre-configured sound effects for common use cases.' It is clearly distinct from a general synthesizer, but it never names or contrasts against siblings like audio_synthesize or audio_compose, so differentiation is left implicit.

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 preset categories (UI, Ambient, Notifications, Data) imply when the tool is useful, and 'No external audio files needed' hints at its convenience. However, there is no explicit when-to-use/when-not guidance and no mention of the alternative audio-generation tools an agent should compare against.

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

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

With no annotations provided, the description carries the full behavioral burden. It does disclose the output type (WAV file), that output_path must be absolute, and that the call returns a success dict, which is useful. However it omits side effects (does it overwrite an existing file?), any length or rate constraints, and permission requirements.

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?

Front-loaded purpose sentence followed by a structured Args/Returns block; every line maps to a real parameter or return value. The second sentence rephrases the first with little added information, which is minor waste.

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 two-parameter composition tool with an output schema, the parameter documentation is thorough and the return description, while redundant with the output schema, is harmless. The main gap is the absence of selection guidance against the many audio-related siblings.

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?

Schema description coverage is 0% and the sequence items are untyped (additionalProperties: true), so the description must compensate — and it does, enumerating item fields (type in tone/preset/whoosh, at, duration, freq, name, volume, waveform). It stops short of documenting value ranges or defaults beyond volume 0-1, and output_path format is only qualified as 'absolute'.

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?

States a specific verb+resource: 'Compose multiple audio events into a timed sequence,' with a clarifying restatement about layering timed sound events. It is distinguishable from generative siblings like audio_synthesize or audio_preset, but it never explicitly contrasts itself with audio_compose, which sounds nearly identical.

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?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives, despite nearby siblings such as audio_compose, audio_synthesize, and video_mix_audio that an agent could easily confuse with this one.

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

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

No annotations are provided, so the description carries the full burden. It does disclose the generation approach (procedural waveforms, self-contained) and enumerates the effect processing chain, which is genuine behavioral context. However, it omits key operational facts for a file-writing tool: whether an existing file at output_path is overwritten, and what happens when the optional output_path is omitted (schema default is null).

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?

Well front-loaded: the opening two sentences establish purpose before the Args block, and the Args/Returns structure is scannable. Minor waste in the near-duplicate first two sentences and a Returns line that partly restates the output schema, but overall efficient.

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?

An output schema exists, so the Returns section is largely redundant, and the parameter surface is fully covered. The remaining gap is the null-default output_path semantics for a mutating file operation with no annotations to fall back on, but the description is otherwise complete enough to invoke the tool correctly.

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?

Schema description coverage is 0%, so the description must compensate entirely, and it does: every one of the 6 parameters is documented with type/format/units and defaults (Hz for frequency, seconds for duration, 0-1 amplitude for volume, waveform names). It goes further by detailing the nested effects keys (ADSR envelope, fade_in/fade_out, reverb room_size/damping/wet_level, lowpass cutoff) that the schema leaves as an opaque additionalProperties object.

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 gives a concrete verb+resource ('Generate audio procedurally', 'Creates WAV files from scratch using mathematical waveforms') and clarifies the key differentiator from input-consuming siblings: no external audio files are needed. It never names a specific sibling (e.g. audio_compose, audio_sequence, hyperframes_tts) to sharpen the contrast, so it stops 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.

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

Usage is only implied through 'No external audio files needed,' which suggests this is the choice when you have no source audio, but no explicit when-to-use or when-not-to-use statement is given. With dozens of audio siblings (audio_compose, audio_sequence, audio_effects, sound_voice_batch), a routing sentence would have been valuable.

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

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

No annotations are provided, so the description carries the full behavioral burden. It confirms the effect writes to a separate output_path (implying a non-destructive transform) and returns a success status, but says nothing about overwrite behavior, permission needs, performance cost, or whether the input is modified. The Returns statement largely duplicates the existing output schema.

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?

Front-loaded with the effect and its purpose, then a tidy Args/Returns structure. The 'trendy ... tech/glitch aesthetics' line is flavor rather than functional, and the Args block partly echoes the schema, but nothing is bloated.

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?

Given an output schema exists, the return description is unnecessary, and parameter coverage is handled. However, for a mutation tool with no annotations, it omits the when-to-use routing among many similar glitch/effect siblings and any behavioral caveats, leaving it only minimally complete.

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?

Schema description coverage is 0%, so the description must compensate, and it does: it defines input/output as absolute paths, intensity as 'pixel offset amount' with a default of 2.0, and angle as 'separation direction in degrees' with a default of 0 (horizontal). The default restatements add little, but the semantic meanings of intensity and angle go beyond the bare schema titles.

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?

States a specific verb+resource ('Apply chromatic aberration - RGB channel separation') and even clarifies the aesthetic it produces. It is not differentiated from near-identical siblings like glitch_rgb_shift, glitch_cmyk_split, or effect_scanlines, so an agent cannot tell which effect tool to pick from the description alone.

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?

No guidance on when to use this vs the many sibling glitch/effect tools, and no preconditions, exclusions, or context triggers. It only describes the visual result, leaving the agent to infer selection entirely on its own.

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

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

With no annotations, the description carries the full load, and it does disclose the return shape ('Dict with success status and output_path') and that the effect is a render to a separate output path (implying the input is not mutated). It does not state overwrite behavior, permission needs, or whether output_path must be pre-existing.

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?

Front-loaded one-line summary followed by a clarifying sentence, then compact Args/Returns blocks. Slightly verbose but every line earns its place; no filler.

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 5-parameter effect with zero schema descriptions and no annotations, the description supplies the parameter constraints and return shape an agent needs. An output schema exists, so the Returns block is redundant but harmless; missing behavioral notes on overwrite/validation keep it short of complete.

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?

Schema description coverage is 0%, so the description must compensate, and it largely does: it documents all five parameters, adds unit semantics ('Blur radius in pixels'), numeric ranges ('Glow strength 0-1', 'Brightness threshold 0-1'), and defaults. Only the path parameters are described minimally as 'Absolute path'.

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?

States a specific verb and resource ('Apply bloom/glow effect') and clarifies the visual intent with 'Creates a soft glow around bright areas of the video.' This clearly distinguishes it from named siblings like effect_vignette or effect_noise, though it never explicitly references those alternatives.

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?

No when-to-use guidance, no prerequisites, and no routing to adjacent tools (e.g., video_filter, still_grade). The agent must infer relevance purely from the effect name, leaving selection against ~150 siblings unguided.

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

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

With no annotations, the description carries the full behavioral burden. It discloses that the tool mutates a video into an output_path and returns a success dict, but says nothing about permissions, reversibility, overwrite behavior, or rate/processing constraints. It is factual but thin on behavioral traits.

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?

Purpose and aesthetic framing are front-loaded in two short sentences, followed by a clean Args/Returns block. Every line earns its place, though the docstring formatting is slightly heavier than strictly needed.

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?

All parameters are covered and an output schema exists so return values are already specified. What remains missing is minor operational context (input format expectations, whether output is overwritten), but for a single-effect transform tool this is close to complete.

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?

Schema description coverage is 0% – the schema only carries titles like 'Mode' and 'Animated'. The description compensates fully by documenting all five params: meaning, the 0-1 intensity range and 0.05 default, the mode values (film, digital, color), and what 'animated' does.

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 gives a specific verb+resource ('Apply film grain or digital noise') and adds a use-case framing ('vintage or lo-fi aesthetics'). It distinguishes itself from other effect/glitch siblings implicitly through the effect type, but never names an alternative or scope boundary.

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?

It supplies context for why one would use it ('vintage or lo-fi aesthetics'), which implies usage, but there is no explicit when-to-use vs when-not, no mention of prerequisites, and no comparison to sibling effects like effect_scanlines or glitch_*.

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

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

With no annotations, the description carries the full burden but provides minimal behavioral context. It describes the visual effect and mentions flicker as optional, which is useful. However, it doesn't disclose whether this overwrites the output file, the expected output format, performance characteristics, or processing requirements. The return statement is generic.

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 front-loaded with the core purpose, followed by a brief behavioral detail and then a clean Args/Returns structure. It's efficient and every sentence earns its place, though the 'Simulates...' sentence is somewhat redundant with the first.

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?

Given no annotations, a 5-parameter tool, and a 0% schema description coverage, the description does a decent job of documenting parameters but leaves significant gaps: no behavioral transparency about file handling, processing requirements, or error conditions. It mentions the return as a dict with success and output_path, but the output schema already exists so that's redundant. It's adequate but not complete.

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?

Schema description coverage is 0%, so the description must compensate. It describes all five parameters: input_path/output_path as absolute paths, line_height as pixels per scanline with default 2, opacity as 0-1 with default 0.3, and flicker as 0-1 with default 0.1. This adds essential semantic meaning not present in the title-only schema. However, it doesn't specify valid ranges for line_height or format constraints for paths.

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?

States a specific verb and resource: 'Apply CRT-style scanlines overlay.' It clearly describes a video-effect tool that simulates old CRT monitor scanline effects. This is distinct from sibling effects like effect_noise or effect_vignette and from glitch_scanline_jitter.

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?

No usage guidelines are provided. The description doesn't indicate when to use this tool vs alternatives like glitch_scanline_jitter or other glitch effects, nor does it mention any exclusions or prerequisites.

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

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

With no annotations, the description carries the full behavioral burden. It discloses the visual effect, numeric ranges/defaults, and that an output video is produced, but it does not state permissions needed, overwrite behavior, whether output_path is optional, or other operational side effects.

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?

Front-loads the effect name and visual result, then uses structured Args/Returns sections. It is efficient and readable, with only slight redundancy between the opening line and the following sentence.

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 video-effect mutation tool with no annotations, the description covers the core visual behavior and all parameters. However, it omits usage context and operational details such as output overwrite semantics, and its Returns section is unnecessary because an output schema exists.

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?

Schema description coverage is 0%, so the description must compensate. It documents all five parameters meaningfully, including the 0-1 ranges and defaults for intensity, radius, and smoothness, which substantially exceeds the bare schema.

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?

States a specific verb and visual effect: 'Apply vignette effect - darkened edges' and explains the darkened border intent. It is clear what the tool does, but it does not distinguish itself from sibling effects such as effect_glow, effect_noise, or effect_scanlines.

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?

Provides no guidance on when to use this effect versus alternatives, nor any prerequisites, exclusions, or creative contexts. Usage is only implied by the effect description.

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

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

With no annotations, the description carries the full behavioral burden. It discloses the return shape ('Dict with success status and output_path') and parameter defaults/units, but omits side effects such as file overwrite behavior, permissions, or what happens when output_path is omitted. This is minimally transparent but insufficient for a write/effect tool.

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 front-loaded with the effect and mechanism, then structured into Args and Returns sections. Given the 0% schema coverage, the parameter list earns its place, though the Returns section slightly duplicates the output schema.

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?

An output schema exists, so the return value explanation is not strictly needed. The description covers parameter semantics well but lacks usage guidance versus sibling glitch effects and does not clarify optional output_path behavior, leaving gaps for correct invocation in a crowded toolset.

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?

Schema description coverage is 0%, so the description must compensate. It documents all five parameters with meaning, units, and defaults: input_path, output_path, amount in pixels, angle in degrees, and noise amplitude range 0-1. It does not clarify that output_path is optional with a null default, preventing a perfect score.

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 states a specific verb and effect resource: 'Apply CMYK split glitch effect,' then explains the mechanism as shifting RGB channels at 90-degree intervals to simulate print registration errors. This distinguishes it from generic glitch siblings by naming the precise effect and its visual intent.

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?

There is no explicit guidance on when to use this tool versus alternatives such as glitch_rgb_shift, glitch_scanline_jitter, or transition_glitch. The effect description implies a use case, but the agent is left to infer selection criteria from the name alone.

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

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

With no annotations, the description carries the full burden. It usefully discloses the artifact mechanism (drifting displacement that resets at intervals) and the return shape, but omits key behavioral facts: what happens when output_path is omitted (schema default is null), whether an existing output file is overwritten, and the required input format. Partial disclosure.

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?

Front-loads the effect and its mechanism in the first two lines, then cleanly separates Args and Returns. The Args block is slightly verbose given the schema already lists the parameters, but every line carries usable semantics.

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?

An output schema exists, so return values needn't be spelled out (the description does so anyway). The critical gap is behavioral: output_path defaults to null with no explanation of where the result then goes, which is material for correct invocation of a rendering tool.

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?

Schema description coverage is 0%, yet the description documents all four parameters, including units ('max displacement drift in pixels'), defaults (20, 30), and the expected absolute-path format for both paths. This meaningfully compensates for the bare schema, though it doesn't clarify the null-default behavior of output_path.

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?

Names a specific effect (datamoshing glitch) and the underlying mechanism (P-frame corruption with periodic displacement resets), which distinguishes it from generic glitch siblings like glitch_rgb_shift or glitch_scanline_jitter. However, it never explicitly contrasts itself against those siblings, so an agent must infer the distinction from the mechanism description alone.

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?

No guidance on when to choose this tool over the many adjacent glitch/transition siblings (transition_glitch, glitch_macroblocking, glitch_turbulent_displacement). It describes what the effect looks like but not the context, prerequisites, or constraints under which an agent should invoke it.

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

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

With no annotations, the description carries the full burden. It usefully discloses a hard environment requirement (Node.js + GPU), the processing mechanism, and the output shape, but says nothing about reversibility, error conditions, performance cost, or what happens with invalid parameters.

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?

Front-loads the effect and its prerequisite, then mechanism, then args, then return shape in a clean scannable structure. The formatting is slightly verbose but every line carries information.

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 six-parameter effect tool with no annotations, the parameter and output coverage is adequate and an output schema exists so return values needn't be detailed. The definition remains thin on usage context and behavioral edge cases, leaving gaps an agent would want filled.

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?

Schema description coverage is 0%, so the description must compensate, and it does: all six parameters are documented with meaning and the four tunables include defaults plus added range info ('threshold (0-1)'). It stops short of explaining interaction between depth_scale, spread, and point_size, but coverage is substantially better than the bare schema.

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?

States a specific verb and resource ('Apply depth-based point splatting effect') and explains the mechanism (pseudo-depth from luminance rendered as scattered points). An agent can distinguish this from generic siblings like glitch_point_cloud or effect_glow, though it doesn't explicitly contrast itself with those alternatives.

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 gives no when-to-use guidance or named alternatives within the large glitch_*/effect_* family. The only contextual cue is the prerequisite '(requires Node.js + GPU)', which is a constraint rather than usage selection advice.

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

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

No annotations are provided, so the description carries the full burden. It discloses the Node.js + GPU runtime requirement and the processing mechanism, which is genuinely useful, but says nothing about whether it overwrites output, permission needs, or write behavior beyond the implicit 'output_path'.

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?

Front-loaded purpose, then a compact mechanism paragraph, then a clean Args/Returns block. Every part is relevant, with only mild redundancy in the Returns line duplicating the output schema.

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 moderately complex effect tool, it covers the mechanism, runtime requirements, and all six parameters with defaults. It doesn't clarify that output_path is optional/nullable or give sibling routing, but since an output schema exists, return values need not be explained further.

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?

Schema description coverage is 0%, so the description must compensate, and it largely does: it gives ranges and units for feedback_mix (0-1), scale (UV scale for previous frame), rotation (degrees), and decay (ghost trail opacity), plus defaults. Only input_path/output_path are near-restatements of the field names.

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?

States a specific verb+resource ('Apply digital feedback glitch effect') and explains the distinguishing mechanism (iterative frame feedback with scale/rotation transforms producing ghost trails). This clearly separates it from sibling glitch effects like glitch_rgb_shift or glitch_scanline_jitter, though it never names an alternative explicitly.

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 parenthetical 'requires Node.js + GPU' is a useful environment prerequisite, but there is no guidance on when to choose this effect over the many sibling glitch tools or transitions. Usage is only implied by the effect name.

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

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

With no annotations, the description carries the full burden and does add real behavioral context: it describes the underlying operation (codec artifacting simulation) and gives defaults for all effect parameters. However it omits key operational facts for a file-writing mutation tool – that it writes a new video (does it overwrite? is input preserved?), and what happens when the optional output_path defaults to null.

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?

Purpose is front-loaded in the first sentence, followed by a compact technical explanation and a clean Args/Returns block. Slight redundancy in restating defaults that also appear in the schema, but overall it is tight and well organized.

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?

An output schema exists, so the Returns line is largely redundant and the description need not explain return values. The parameter coverage is good, but for a 5-param file-transforming tool with zero annotations, the absence of any usage/routing guidance or file-write semantics leaves a noticeable gap.

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?

Schema description coverage is 0%, so the description must compensate, and it largely does: it documents all five parameters, adds units (block_size in pixels), value ranges (0-1 for intensity and color_reduction), and the default for each. The one gap is that output_path's null default behavior is not explained.

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?

States a specific verb and effect ('Apply macroblocking glitch effect') and explains the mechanism (downscale/upscale pixelation plus posterization), so the agent knows exactly what visual result to expect. It does not, however, distinguish itself from the many glitch_* siblings (glitch_rgb_shift, glitch_scanline_jitter, transition_pixelate), so selection among them requires external knowledge.

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?

There is no when-to-use guidance, no prerequisites, and no named alternative among the numerous sibling glitch/pixelate effects. Usage is only implied by the word 'effect'. An agent cannot tell from this text why it would pick macroblocking over transition_pixelate or glitch_rgb_shift.

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

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

No annotations are provided, so the description carries the full behavioral burden. It notes the requirement for Node.js + GPU but doesn't disclose whether the operation is destructive, what happens to the input file, whether it's reversible, or any rate limits or permissions needed. For a mutation tool with no annotation coverage, this is a significant gap.

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 well-structured with a clear purpose statement, visual explanation, and parameter list. It's concise and front-loaded, though the 'Args' and 'Returns' sections are somewhat boilerplate. Every sentence serves a purpose.

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?

With output schema present, the description needn't explain return values in detail, but it does mention 'Dict with success status and output_path', which is helpful. However, for a mutation tool with no annotations, it should disclose more about behavioral traits (e.g., whether it modifies the input, error handling, GPU memory usage). The description is adequate but incomplete for its complexity.

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?

Schema description coverage is 0%, so the description must compensate. It documents all six parameters (input_path, output_path, density, point_size, rotation, depth) with brief explanations and defaults, which is helpful. However, the descriptions are minimal (e.g., 'Point sampling density (0-1)') and don't add much depth beyond what's inferable from parameter names. Baseline 3 is appropriate given the coverage gap is partially addressed.

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 states a specific effect ('point cloud rendering effect') and explains what it does visually ('samples the image as scattered points arranged in a 3D-rotated grid, with depth-based displacement'). This is clear, but it doesn't explicitly differentiate from siblings like glitch_depth_splatting or glitch_turbulent_displacement, which may share similar visual characteristics.

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 mentions 'requires Node.js + GPU' as a prerequisite, but provides no guidance on when to use this tool versus alternatives (e.g., glitch_depth_splatting, glitch_turbulent_displacement) or in what scenarios it's appropriate. There's no explicit when-to-use or when-not-to-use information.

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

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

No annotations are provided, so the description must carry the behavioral burden. It discloses the core transformation and that a dict with success/output_path is returned, but it does not mention overwrite behavior, codec handling, permissions, or what happens when output_path is omitted.

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?

Front-loads the effect summary, then separates Args and Returns cleanly. It is appropriately sized for five parameters, though the blank-line formatting is slightly loose.

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?

The description covers the effect and parameter semantics well, and an output schema exists so return details are less critical. However, for a mutation tool with no annotations, it leaves usage context, output_path optionality, and side-effect behavior unstated.

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?

With 0% schema description coverage, the description usefully documents all five parameters, including units (pixels for amount, degrees for angle), defaults, and the 0-1 noise range. It misses that output_path is optional/nullable in the schema, but otherwise compensates well for the undocumented schema.

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?

States a specific verb and effect: 'Apply RGB channel shift glitch effect,' then explains red/blue channel separation. It clearly identifies the operation, though it does not explicitly differentiate itself from similar sibling effects such as glitch_cmyk_split.

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?

No when-to-use guidance, no prerequisites, and no alternatives are named. The description only says the effect can optionally add noise, leaving the agent to infer when this tool is appropriate versus other glitch or effect tools.

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

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

No annotations are provided, so the description must carry the behavioral burden. It does disclose the effect semantics (random displacement, CRT look, animated) and implies a file-to-file transform, but never covers overwrite behavior, permissions, reversibility, or processing cost. The "Returns" line is redundant given an output schema exists.

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?

Front-loads the purpose in the first sentence, then cleanly separates Args and Returns. Efficient overall, though the Returns sentence adds little beyond the existing output schema.

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 6-parameter effect tool with an output schema, parameter and return coverage are adequate, but the absence of any annotation or usage context leaves the definition short on when/when-not guidance in a very crowded sibling set. It is minimum-viable rather than complete.

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?

Schema description coverage is 0%, so the description properly compensates: it documents all six parameters with meaning, defaults, and units (jitter_amount in pixels default 15, frequency fraction 0-1 default 0.3, speed multiplier default 5, row_height in pixels default 4). The only gap is output_path behavior (nullable/default) is not explained.

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?

States a specific verb and resource ("Apply scanline jitter glitch effect") and elaborates with the mechanism ("displaces random horizontal rows of pixels for a CRT malfunction look"). Clear on its own, but it never differentiates from heavily overlapping siblings like effect_scanlines, glitch_screen_tearing, or glitch_vhs_tracking.

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?

There is no when-to-use, when-not-to-use, or alternative-selection guidance at all. In a sibling space packed with other glitch effects, an agent gets no help deciding between this and, say, glitch_rgb_shift or effect_scanlines.

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

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose the visual behavior (tear bands at varying Y positions shifting over time) and implies a file-to-file transformation via input/output paths plus a success/output_path return. However it omits whether the source is modified, overwrite semantics, required permissions, or performance characteristics.

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?

Front-loaded with the effect summary before the structured Args/Returns block, and every line is informative. Slightly verbose in restating defaults that the schema already carries, but overall tight and well organized.

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?

An output schema exists, so the return-value line is a bonus rather than a necessity. Combined with full parameter documentation and a clear effect description, the definition is nearly complete; the missing piece is routing guidance among the many sibling glitch effects.

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?

Schema description coverage is 0%, so the description must compensate, and it does: all five parameters are documented with meaning and defaults (tear_count 'Number of tear bands', offset_range 'Max horizontal offset in pixels', speed 'Animation speed'). Only minor gaps remain, e.g. units/valid ranges and behavior of the optional output_path.

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 states a specific verb and resource ('Apply screen tearing glitch effect') and even explains the visual mechanism (horizontal tear bands shifting left/right over time). It clearly distinguishes itself from non-glitch siblings, but does not differentiate from the many other glitch_* siblings (glitch_rgb_shift, glitch_scanline_jitter, glitch_vhs_tracking, etc.).

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?

There is no guidance on when to use this effect versus the other glitch tools or any other alternative, and no prerequisites or exclusions are stated. Usage is only implied by the tool name and the effect description.

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

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

No annotations are supplied, so the description carries the full behavioral burden. It usefully discloses the runtime prerequisite (Node.js + GPU) and that it returns a dict with success status and output_path, but it omits what happens when output_path is left at its null default, overwrite behavior, and any performance/processing-time expectations.

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?

Front-loaded with the effect name and mechanism, then a compact Args/Returns block. Every line adds usable information; there is no filler or repetition of the title.

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 4-parameter GPU effect tool with an output schema present (so return values need not be re-explained), the definition covers purpose, environment requirement, and every parameter. The one notable gap is the behavior of the null-defaulted output_path, which the agent still has to guess at.

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?

Schema description coverage is 0%, so the description must compensate, and it does: it names all four parameters, gives an absolute-path requirement for input/output, supplies the depth range (1-120) with default 30, and decodes direction as a 0-3 enum with labels and default. This is information the schema does not carry.

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?

States a specific verb and effect ('Apply slit-scan temporal displacement effect') and then explains the mechanism ('each row/column sampled from a different past frame'), which cleanly separates it from the many neighboring glitch_* tools such as glitch_scanline_jitter or glitch_rgb_shift.

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 conveys the visual intent and a hard prerequisite ('requires Node.js + GPU'), which implies when the tool is appropriate, but it never states when to choose it over siblings like transition_glitch or glitch_turbulent_displacement, nor any exclusion criteria.

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

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

With no annotations, the description carries the full burden. It discloses the noise algorithm and that the return is a dict with success status and output_path, but says nothing about whether existing files are overwritten, what happens when output_path is omitted (it is nullable with default null), error modes, or performance cost. Useful context, but key behavioral gaps remain.

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?

Front-loaded with the effect name, then a brief technical rationale, then a clean Args/Returns block. Every line earns its place; no redundant restatement of the tool name.

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 6-param tool with zero schema descriptions and no annotations, the description covers all parameters, the technique, and the return shape. The main omissions are the nullable output_path behavior and any error/overwrite semantics.

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?

Schema description coverage is 0%, so the description must compensate, and it does: it explains input_path/output_path as absolute paths, gives amount in pixels, scale as base noise frequency, speed as animation speed, and constrains octaves to 1-5, all with defaults. It only omits the semantics of the optional/nullable output_path.

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?

States a specific verb and effect ('Apply turbulent displacement glitch effect') and even explains the underlying technique (layered sin/cos approximating fBm noise), which is enough to distinguish it from glitch siblings like glitch_rgb_shift or glitch_scanline_jitter. It never explicitly names or contrasts those siblings, 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.

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

There is no when-to-use guidance, no prerequisites, and no routing to or away from the many alternative glitch/effect tools. The agent must infer the use case purely from the effect name.

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

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

With no annotations, the description carries the full burden, and it does disclose the return shape ("Dict with success status and output_path") and the nature of the visual effect. However, it omits operational traits an agent would want for a video mutation: re-encode behavior, supported input formats, processing cost, and what happens when output_path is omitted (null default).

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?

Front-loaded with the effect statement, then a compact Args/Returns block with no redundant prose. The extra sensory sentence about the effect is short and earns its place, though the Returns line is somewhat redundant given an output schema exists.

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 6-parameter effect tool with an output schema present, the description covers purpose, all parameters, and return shape, so an agent can call it correctly. The absence of any behavioral/permission/performance context is the main remaining gap, partly excused by the existing output schema.

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?

Schema description coverage is 0%, so the description must compensate, and it largely does: all six parameters are named with meaning, units, and defaults (tracking 0-1, noise_amount 0-1, color_bleed in pixels, roll_speed). The only gap is the semantics of output_path being optional/null, which is not explained.

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 names a specific verb and effect ("Apply VHS tracking error glitch effect") and elaborates with concrete visual traits (color bleed, rolling bands, analog noise), which cleanly separates it from sibling glitch tools like glitch_rgb_shift or glitch_scanline_jitter. It does not explicitly name those siblings, 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.

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

There is no statement of when to choose this tool over the many other glitch/effect siblings, no prerequisites, and no exclusions. The reader must infer applicability from the effect name alone.

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

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

No annotations are provided, so the description carries the full behavioral burden for a mutation tool. It does not say that files are written into the project, whether existing files are overwritten, whether the project must be initialized, or what happens when block_name is not in the catalog. Only the bare action is disclosed.

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?

Front-loaded purpose followed by a compact Args block; there is little waste. The formatting is slightly boilerplate ('Args:' list) but each line carries information.

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 filesystem-mutating tool with no annotations, the description omits prerequisites, overwrite behavior, error conditions, and the meaning of the optional no_clipboard flag. The existence of an output schema excuses it from explaining return values, but the behavioral gaps remain significant.

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?

Schema description coverage is 0%, so the description must compensate. It usefully documents 2 of 3 parameters (project_path as absolute directory, block_name with concrete examples like claude-code-window). The third parameter, no_clipboard, is left unexplained in both the schema and the description, so compensation is partial.

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?

States a specific verb and resource: 'Install a block from the Hyperframes catalog.' An agent knows this adds a catalog block to a project. However, it does no sibling differentiation — nothing distinguishes it from hyperframes_catalog, hyperframes_init, or hyperframes_render in the Hyperframes family.

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?

There is no when-to-use guidance, no prerequisites (does the project need hyperframes_init first?), and no pointer to hyperframes_catalog for discovering valid block names. Usage is only implied by the verb 'install'.

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

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

No annotations are provided, so the description carries the full burden. It does not disclose that benchmarking likely performs repeated renders (costly, possibly minutes), whether it writes files to output_path, or whether it mutates the project. Only the high-level intent is stated.

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?

A single front-loaded sentence with no filler; it states the tool's purpose immediately. It is arguably too terse rather than padded.

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?

An output schema exists so return values need not be explained, but with no annotations, 0% parameter coverage, and no usage context, the definition is thin for a four-parameter tool that presumably runs repeated renders. Key operational context is missing.

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?

Schema description coverage is 0% for all four parameters. The description mentions speed and file size but says nothing about runs, json_output, output_path, or project_path, leaving every parameter's meaning and format to inference from its name alone.

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 names a specific verb (benchmark) and resource (Hyperframes render), plus the measured dimensions (speed, file size), so an agent can tell it is a measurement tool rather than a renderer. However, it does not differentiate itself from the sibling video_benchmark_run, which sounds like it does the same thing for a different pipeline.

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?

There is no guidance on when to run this benchmark, what state the project must be in, or how it relates to video_benchmark_run. The agent must infer that this applies only to Hyperframes projects.

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

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing beyond the fact that the result is 'editable.' It does not say whether the tool fetches the live site, whether it writes files to disk (the 'output' param implies this), whether network access or credentials are needed, or how long a capture typically takes.

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?

It is a single front-loaded sentence with zero filler, which is structurally clean. But for a five-parameter tool with no annotations, this level of brevity crosses from concise into under-specified.

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?

An output schema exists, so return values need not be described, but the rest of the context is thin: five undocumented parameters, no annotations, and no usage framing. An agent could not reliably call this tool beyond supplying a URL.

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?

Schema description coverage is 0% across five parameters, so the description must compensate and it does not. Only 'url' is implied by 'a website'; output, timeout_ms, skip_assets, and max_screenshots are entirely unexplained in both schema and description, leaving their meaning and expected values to inference.

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 states a specific verb ('Capture') and resource ('a website') and names the output artifact ('editable Hyperframes components'), which distinguishes it from pure-render siblings like hyperframes_render. However, it gives no differentiation from near-neighbors such as hyperframes_snapshot, hyperframes_still, or hyperframes_inspect, leaving the agent to guess which capture-like tool applies.

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?

There is no when-to-use guidance, no prerequisites, and no mention of any alternative among the many hyperframes_* siblings. The agent is told what the tool does but not the conditions under which it should be preferred over snapshot, still, or preview.

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

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

No annotations are provided, so the description carries the full behavioral burden. It says only that the tool browses the catalog; it does not disclose pagination, filtering behavior, permissions, rate limits, or whether the operation is read-only.

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 a single front-loaded sentence with no wasted words. However, it is under-specified for a tool with two optional filters, so its concision comes at the cost of useful detail.

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?

An output schema exists, so return values need not be described. Still, with no annotations and no parameter documentation, the description omits how to use the tag and item_type filters and gives no behavioral context for browsing the catalog.

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 has two parameters ('tag' and 'item_type') with 0% description coverage, and the description does not explain either one. 'Blocks/components' loosely gestures at item type but does not define values or clarify how 'tag' filters the catalog.

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?

States a specific verb ('Browse') and resource ('Hyperframes catalog blocks/components'), so the basic purpose is clear. It does not differentiate from sibling tools such as hyperframes_compositions or hyperframes_info, which prevents a 5.

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?

Provides no explicit when-to-use, when-not-to-use, or alternative guidance. The imperative 'Browse' implies a read operation but does not help an agent choose between this catalog tool and related hyperframes tools.

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

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

No annotations are provided, so the description carries the full behavioral burden. It doesn't indicate whether the list is recursive, whether it requires the project to be initialized, error behavior for invalid paths, sorting, or pagination. The single line about args adds nothing behavioral.

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?

Very short and front-loaded with the action and resource. The Args block is somewhat redundant with the schema, but it adds the absolute-path clarification, so it earns its place.

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?

Output schema exists, so return values needn't be described. However, for a listing tool with no annotations, the description lacks essential context such as prerequisites (initialized project) and the nature of the returned list, leaving gaps an agent would want filled.

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?

Schema description coverage is 0%, but the description explains project_path as an absolute path to the Hyperframes project directory, partially compensating for the empty schema title. With only one parameter and no format details or examples, this meets the baseline but goes no further.

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?

States a specific verb (list) and resource (compositions) scoped to a Hyperframes project, which an agent can distinguish from siblings like hyperframes_info or hyperframes_catalog. It does not, however, say how compositions differ from those other Hyperframes artifacts, leaving mild ambiguity about what exactly is returned.

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?

No when-to-use or when-not-to-use guidance, and no mention of alternatives such as hyperframes_catalog or hyperframes_info. The agent must infer from the name alone whether this is the right listing tool.

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

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

With no annotations provided, the description carries the full behavioral burden. It does not disclose whether the tool is read-only or has side effects, what environment aspects it inspects (binaries, config, credentials, versions), whether it requires auth, or how failures are reported. The presence of an output schema covers return shape but not behavioral characteristics.

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?

A single front-loaded sentence with no padding or redundancy. It is efficient, though the sparseness reflects under-specification rather than tight editing.

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?

The output schema means return values need not be described, and zero params keeps the surface small. However, with no annotations and no indication of when to run it or what it verifies, the definition is only minimally complete for a diagnostics entry point in a large tool family.

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 tool takes zero parameters, so there are no parameter semantics for the description to explain. Baseline of 4 applies.

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?

States a specific verb ('Run') and resource ('Hyperframes environment diagnostics'), which is clear enough that an agent knows it checks the Hyperframes environment. It does not explicitly differentiate itself from nearby siblings such as hyperframes_validate, hyperframes_info, or hyperframes_preflight, but the 'environment diagnostics' framing is distinct.

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?

There is no when-to-use guidance, no prerequisites, and no naming of alternatives. An agent cannot tell from the description whether this should be run before rendering, after a failure, or as a general health check versus hyperframes_validate or hyperframes_preflight.

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

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

No annotations are provided, so the description carries the full burden. 'Print' implies a read-only operation, but it does not state permissions, side effects, rate limits, or whether the output is purely informational. The presence of an output schema reduces the need to explain return values, but behavioral context remains thin.

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 a single, front-loaded sentence with no wasted words. It is appropriately sized for a simple metadata tool.

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 tool with one required parameter, no annotations, and 0% schema description coverage, the description is incomplete. It omits when to use the tool, what kind of metadata is printed, and any parameter expectations, leaving the agent with insufficient context beyond the bare purpose.

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?

Schema description coverage is 0%, and the description does not mention the required 'project_path' parameter at all. It does not explain the expected path format, whether it must point to a Hyperframes project directory, or any constraints. The parameter name is somewhat self-explanatory, but the description adds no meaningful semantics.

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 verb ('Print') and resource ('Hyperframes project metadata'), making the basic action clear. It distinguishes itself from generic video metadata tools by specifying Hyperframes, though it does not differentiate from sibling tools like hyperframes_inspect or hyperframes_catalog.

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?

There is no guidance on when to use this tool versus alternatives such as hyperframes_inspect, hyperframes_catalog, or video_read_metadata. Usage is only implied by the tool name and description.

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

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

No annotations are provided, so the description carries the burden. It does disclose useful behavior: defaults for output_dir/template, that transcription happens during media bootstrap and can be skipped, and that media can seed the project. It does not say whether an existing directory is overwritten, what files are produced, or what permissions are needed.

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 one-line purpose is correctly front-loaded, but the body is a flat docstring arg dump that mirrors the schema field-by-field without grouping or prioritization. It is not padded, but it is not tight either.

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 10-parameter mutating scaffold tool with no annotations, the description covers parameter meaning adequately and an output schema exists so return values need no explanation. It is still missing preconditions (existing directory handling, required media formats) and any routing context against the sibling initializers.

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?

Schema description coverage is 0%, so the description must compensate, and it largely does: every one of the 10 parameters gets a plain-language meaning, template enumerates its three valid values (blank, warm-grain, swiss-grid), and defaults are restated for output_dir, template, and the media fields. Only 'resolution preset' and the Whisper model choices remain underspecified.

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?

States a specific verb and resource: 'Scaffold a new Hyperframes project.' An agent can immediately tell this creates project scaffolding. It does not, however, differentiate itself from close siblings like video_init_project or video_project_create, so it stops 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.

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

There is no when-to-use guidance and no mention of the alternatives in a sibling list that contains at least two other project-initialization tools (video_init_project, video_project_create). The description never says when this should be preferred over those.

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

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

No annotations are provided, so the description carries the full burden. 'Inspect' implies read-only, but the description does not disclose whether it triggers a render, requires an existing rendered composition, its side effects, or how results are produced. With 7 params and no annotation safety profile, this is a significant gap.

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?

A single front-loaded sentence with no filler. It is efficient, though arguably too terse given the parameter complexity; still, it wastes no words.

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?

Output schema exists, so return values need not be explained. However, with no annotations and 0% parameter coverage, the definition omits usage context, behavioral traits, and parameter meaning, leaving the agent under-equipped to invoke the tool correctly.

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?

Schema description coverage is 0% for 7 parameters. The description names no parameters and gives no meaning for 'at', 'strict', 'samples', 'tolerance', 'max_issues', 'timeout_ms', or 'project_path'. It does not compensate for the complete lack of schema documentation.

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?

States a specific verb ('Inspect') and resource ('rendered composition layout') and names the issue types ('overflow and visual issues'). It does not differentiate from siblings like hyperframes_validate or hyperframes_snapshot, so it stops 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.

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

No when-to-use guidance, no prerequisites, and no mention of alternative tools. The agent must infer from the name that this is for post-render layout inspection.

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

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

No annotations are provided, so the description carries the full behavioral burden. 'Launch ... for live preview' implies a long-running server process, but nothing is said about whether the call blocks, what it returns (URL?), how the server is stopped, or any port-conflict behavior.

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?

One-sentence purpose followed by a two-item arg list; front-loaded and free of filler. The Args block duplicates the schema somewhat but stays short.

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?

An output schema exists, so return values need not be described. But for a server-launching tool with no annotations, the description omits lifecycle essentials: blocking behavior, server URL, and how to terminate the preview.

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?

Schema description coverage is 0%, so the description must compensate. It does add real meaning: project_path must be an absolute path to a Hyperframes project directory, and port defaults to 3002. However, it omits valid port ranges or what happens on conflicts.

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?

States a specific verb and resource: launching the Hyperframes preview studio for live preview. It's clear this is the Hyperframes-local preview server launcher, but it does not explicitly distinguish itself from near siblings such as video_preview, video_template_preview, or hyperframes_snapshot.

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?

No when-to-use guidance, prerequisites, or alternatives are given. An agent cannot tell from the description when to prefer this over video_preview or hyperframes_still.

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

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

With no annotations, the description carries the burden and does well: it discloses the hidden install dependency (kinocut[object-matte]), the no-silent-fallback behavior ("Never falls through to the people model"), and that info=True lists models without downloading (a side-effect-free probe). It does not describe how device/quality/mask_interval change runtime behavior or resource cost, so it is not complete.

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?

Purpose is front-loaded in the first sentence, followed by the model-selection caveat and the info probe, with no filler. The model/install sentence is densely packed (install requirement embedded in parentheses), which is slightly compressed but still readable.

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?

An output schema exists, so return values need no explanation, and the safety/selection story is covered. However, with 10 parameters at 0% schema coverage and no annotations, an agent still cannot reason about mask_interval, device, quality, or the equipment-overlay/failure flags that materially affect output. Minimum viable rather than complete.

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?

Schema description coverage is 0% across 10 parameters, so the description must compensate, and it only clarifies two of them (model, info). device, quality, input_path, output_path, mask_interval, equipment_overlay, background_output_path, and fail_if_equipment_on_subject remain entirely unexplained in both schema and prose. Partial compensation, substantial gap.

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?

States a specific operation and scope: "Cut a person or a product out of a still or video." That is unambiguous about verb and resource, and it implicitly separates itself from keying/masking siblings by naming person/product cutouts. It stops short of naming an alternative tool (e.g. video_chroma_key) explicitly, so it falls just short of 5.

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?

Explicitly routes the caller: default u2net_human_seg is people-only, and products/packaging/jewelry/bottles/ceramics require model="birefnet-general". It also tells the agent how to enumerate options (info=True with no input) and where the extended guide lives. The when-to-use-which-model condition is fully spelled out.

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

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

With no annotations, the description carries the full burden. It does disclose useful behavior: output_path is auto-generated if omitted, and it supplies defaults not present in the schema (quality=standard, format=mp4, workers=auto). However it says nothing about side effects (overwriting existing files), resource/GPU needs, blocking behavior, or failure modes, which are significant for a 25-param render tool.

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 purpose sentence is front-loaded and the Args list is a compact, scannable format appropriate to a 25-parameter tool. Most lines earn their place with default values or value ranges, though the trailing whitespace and lack of grouping for the boolean flags are minor inefficiencies.

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?

An output schema exists, so return values need not be described, and the core render parameters are covered. But for a tool with 1 required and 24 optional parameters and zero schema descriptions, the unexplained GPU/strict/docker/quiet flags leave the definition insufficiently complete to call it confidently.

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?

Schema coverage is 0%, so the description must compensate. It documents roughly half the parameters with meaningful value ranges (fps 24/30/60; quality draft/standard/high; format mp4/webm/mov/png-sequence; resolution presets; 'crf: lower = better quality'), which is genuinely useful. But about a dozen parameters (gpu, hdr, sdr, quiet, docker, strict, strict_all, browser_gpu, no_browser_gpu, video_bitrate, strict_variables, max_concurrent_renders) are left entirely unexplained.

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 lead sentence states a specific verb and resource: 'Render a Hyperframes composition to video.' That clearly identifies the operation and its output artifact, distinguishing it from still/preview siblings. It stops short of explicitly contrasting with revideo_render or video_workflow_render, so it is clear but not sibling-differentiating.

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?

There is no when-to-use guidance and no mention of alternatives such as hyperframes_preview or revideo_render. The description only lists arguments; an agent cannot infer when this render path is preferred over the other render tools in the sibling set.

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

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

With no annotations, the description carries the full burden. It states that frames are captured as PNG screenshots, but does not disclose side effects (e.g., whether files are written, where they are saved), permissions required, or how frame selection behaves. Only the most basic operation is described.

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 a single front-loaded sentence with no wasted words. However, for a 6-parameter tool with no other documentation, the extreme brevity leaves essential information absent, keeping it from a perfect score.

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?

The presence of an output schema means return values need not be explained, but the description still lacks parameter meanings, side effects, and prerequisites for a tool with 6 parameters and no annotations. It is insufficiently complete for correct invocation.

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?

Schema description coverage is 0% across 6 parameters, so the description must compensate. It mentions no parameters and gives no meaning for 'at', 'frames', 'variables', 'timeout_ms', 'project_path', or 'variables_file'. 'Key frames' vaguely relates to the 'frames' parameter but provides no actionable semantics.

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?

States a specific verb ('Capture') and resource ('key frames as PNG screenshots') with a stated purpose ('for visual verification'). Clear, but does not differentiate from siblings like hyperframes_capture, hyperframes_still, or hyperframes_preview, 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.

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

The phrase 'for visual verification' hints at a context, but there is no explicit guidance on when to use this tool versus alternatives, no exclusions, and no prerequisites. The agent must infer usage entirely.

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

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

No annotations are provided, so the description carries the full behavioral-disclosure burden. It states that a single frame is rendered and that output_path is auto-generated if omitted, but it does not disclose output format, overwrite behavior, permissions, error conditions, or any side effects of writing the image.

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 front-loaded with the core purpose in one sentence, followed by a compact Args list. Every line contributes directly to invocation understanding, with no filler.

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?

The tool has five parameters, no annotations, no schema descriptions, and an output schema. The description adequately documents parameters, but without annotations it should also provide usage and behavioral context, such as when to choose this over hyperframes_snapshot or what happens on invalid frames/output paths.

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?

Schema description coverage is 0%, so the description must supply parameter meaning, and it does so for all five parameters. It explains project_path as an absolute directory, output_path behavior, frame defaulting to 0, and the inline/file variants for runtime variables; it only misses precedence between variables and variables_file.

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 gives a specific verb and resource: rendering a single frame as an image from a Hyperframes composition. It clearly differentiates from a full render by saying 'single frame as image,' but it does not explicitly position itself against sibling tools such as hyperframes_snapshot, hyperframes_render, or hyperframes_capture.

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?

There is no explicit guidance on when to use this tool versus alternatives. The description only documents arguments and does not mention when a single-frame render is appropriate, nor when to prefer hyperframes_render, hyperframes_snapshot, or other frame-extraction siblings.

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

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

No annotations, so the description carries the full burden. It discloses only that output_path is auto-generated if omitted; it omits permissions, side effects, whether existing output is overwritten, and runtime/rate-limit behavior for a render pipeline.

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?

Front-loaded one-sentence purpose followed by a compact Args block; the single example is useful and no sentence is wasted.

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?

Output schema covers return values, and parameters are well documented, but for a pipeline tool with an open-ended post_process array, the description never enumerates valid operations or their required params, leaving a meaningful gap for correct invocation.

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?

Schema description coverage is 0%, but the description compensates by defining all three parameters: project_path as absolute project directory, post_process as a list of op/params objects with a concrete example, and output_path as the save location with a default. This adds substantial meaning beyond bare schema titles.

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?

States a specific verb ('Render') and resource ('Hyperframes composition') plus 'post-process with mcp-video', and the 'in one step' phrasing distinguishes it from separate render and post-process siblings.

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 'in one step' phrasing implies using this when combined render+post-process is desired, but it names no alternatives (e.g., hyperframes_render plus separate post-processing) and gives no explicit when-not guidance.

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

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

No annotations are provided, so the description carries the full behavioral burden. It discloses output granularity ('word-level timestamps') and a dual import mode, but omits permissions, supported formats, whether files are written, and other operational constraints.

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?

A single sentence, front-loaded with the core action and covering the secondary import mode without filler. It is appropriately sized for a tool definition.

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?

An output schema exists, so return values need not be explained, but with no annotations and zero schema parameter descriptions, the definition leaves too much unspecified for reliable invocation. Usage context and parameter meaning are missing.

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?

Schema description coverage is 0% across four parameters. The description only loosely implies an input path via 'audio/video' and does not explain model, language, or project_path at all, leaving most parameters undocumented.

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 names a specific verb ('Transcribe') and resource ('audio/video') and states the output granularity ('word-level timestamps'). It also covers an import mode, but does not differentiate the tool from similar siblings such as video_ai_transcribe or video_generate_subtitles.

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?

There is no when-to-use guidance, no prerequisites, and no alternatives named. The two modes are mentioned, but the description does not help an agent choose this tool over sibling transcription or subtitle tools.

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

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

No annotations are provided, so the description carries the full behavioral burden. It mentions 'local TTS' but does not disclose output file behavior, permissions, voice availability, speed limits, or whether text_or_file reads from disk, leaving significant behavioral gaps for a generation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.