rnv-color-mcp
Server Details
A complete color workflow over MCP: mix, convert, harmonize, measure, and remember palettes.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- RNVizion/rnv-color-mcp
- GitHub Stars
- 1
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Usage analytics
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Tool Definition Quality
Average 4.9/5 across 9 of 9 tools scored.
The color tools are well-differentiated, but the inclusion of transform_text (a text case tool) in a color MCP creates confusion. Agents may wonder if it's for color names or general text, and it has no clear relationship to the rest of the tools.
Most tools follow a verb_noun pattern (convert_color, generate_harmony, mix_colors, etc.), but color_difference and contrast_check deviate as noun_noun. Overall, names are intuitive and consistent enough.
Nine tools is a reasonable count for a color server, covering conversion, difference, harmony, mixing, and palettes. However, the unrelated transform_text tool feels like scope creep, slightly reducing appropriateness.
The server covers core color operations and palette CRUD (create, read, list) but lacks a delete_palette tool and basic color adjustment (lighten/darken). The transform_text tool is irrelevant, leaving some gaps in the color domain.
Available Tools
9 toolscolor_differenceAInspect
Perceptual difference (Delta-E) between two colors. color1 and color2 accept a hex, CSS name, RNV brand name, or saved-palette reference. method is 'ciede2000' (default, modern standard) or 'cie76'. A value near 1.0 is the threshold the eye can just notice; larger means more different. Returns the value and a plain-language interpretation. Read-only and deterministic, with no side effects. Use ciede2000 for accuracy and pick cie76 only to match a legacy system; to test whether text is legible on a background (not raw difference) use contrast_check instead.
| Name | Required | Description | Default |
|---|---|---|---|
| color1 | Yes | ||
| color2 | Yes | ||
| method | No | ciede2000 |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Explicitly states 'Read-only and deterministic, with no side effects.' Explains return value: 'Returns the value and a plain-language interpretation.' Interprets numeric result: 'A value near 1.0 is the threshold the eye can just notice.' No contradictions with annotations (none provided).
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?
Three dense sentences with zero waste. Front-loaded with purpose, then parameter details, then usage guidance. Every sentence adds unique value.
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?
Covers input format, method choices, meaning of output (numeric threshold and interpretation), side-effect safety, and sibling differentiation. Perfectly adequate for a 3-param tool with 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?
Despite 0% schema description coverage, the description fully compensates: specifies accepted formats for color1/color2 (hex, CSS name, RNV brand name, saved-palette reference), explains method options with default and context for choosing.
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?
Clearly states the tool computes perceptual difference (Delta-E) between two colors. Distinguishes from sibling contrast_check, which tests legibility, not raw difference. Verb 'difference' is implicit but clear from 'perceptual difference'.
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 advises when to use each method: 'Use ciede2000 for accuracy and pick cie76 only to match a legacy system.' Also provides alternative tool: 'to test whether text is legible on a background (not raw difference) use contrast_check instead.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
contrast_checkAInspect
WCAG contrast ratio between a foreground and background color, for accessibility. Both accept a hex, CSS name, RNV brand name, or saved-palette reference. Returns the ratio (1.0-21.0) plus pass/fail for AA and AAA at normal and large text sizes and for UI components. Read-only and deterministic, with no side effects. Use this for legibility and accessibility checks; to measure raw perceptual difference between two colors rather than readability use color_difference instead.
| Name | Required | Description | Default |
|---|---|---|---|
| background | Yes | ||
| foreground | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses it is read-only and deterministic with no side effects. Lists accepted input types (hex, CSS name, RNV brand name, saved-palette reference). Describes output: ratio and pass/fail for AA/AAA at normal/large text and UI components.
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?
Two-sentence description is highly efficient. First sentence states purpose and input types. Second sentence details output and usage guidelines. No wasted 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?
Given the output schema exists, description appropriately does not repeat return format. Covers inputs, purpose, behavior, and differentiation from sibling. Completely sufficient for an agent to select and invoke 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 has 0% description coverage, but description adds significant meaning: both parameters accept hex, CSS name, RNV brand name, or saved-palette reference. This fully compensates for the missing schema descriptions.
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?
Clearly states it calculates WCAG contrast ratio for accessibility. Explicitly distinguishes from sibling tool color_difference by noting it measures readability, not raw perceptual difference.
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 tells when to use (legibility/accessibility checks) and when not to (use color_difference for perceptual difference). Also notes read-only nature.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_colorAInspect
Convert a color between formats. Input accepts a hex, CSS name, RNV brand name, or saved-palette reference. With to set to one of hex/rgb/hsv/hsl/lab, returns just that format; otherwise returns all of them. Read-only and deterministic, with no side effects. Use for format conversion of a single color; to blend several colors into one use mix_colors, and to compare two colors use color_difference.
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | ||
| color | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses read-only, deterministic, no side effects. Describes output behavior based on the 'to' parameter. Lacks explicit error handling for invalid input, but given the listed accepted formats, this is minor. No annotations provided, so description carries full burden.
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?
Three sentences, each serving a distinct purpose: input, output, usage guidelines. No unnecessary words. Front-loaded with the action and resource.
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?
Covers all essential aspects: input formats, output behavior, and usage context. Output schema exists, so return value details are not needed. Complete for a conversion tool with good parameter descriptions.
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 coverage, the description compensates well by explaining the 'color' parameter accepts hex, CSS name, RNV brand name, or palette reference. The 'to' parameter is described as one of hex/rgb/hsv/hsl/lab, plus default behavior. Enumerates allowed formats but does not list them in a structured way.
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?
Clearly states the tool converts a color between formats, listing accepted input types. It distinguishes itself from siblings by explicitly naming alternatives: mix_colors and color_difference.
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 explicit when-to-use and when-not-to-use: 'Use for format conversion of a single color; to blend several colors into one use mix_colors, and to compare two colors use color_difference.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_harmonyAInspect
Generate a color harmony from a base color. base accepts a hex, CSS name, RNV brand name, or saved-palette reference (e.g. 'Spring line:2'). scheme is one of: complementary, analogous, triadic, split-complementary, tetradic (a.k.a. square), monochromatic, compound. Returns a list of hex colors. Read-only and deterministic: it derives the colors from the base and stores nothing, so it has no side effects and is safe to call repeatedly. Use to expand one base color into a related set; to blend existing colors into a single color use mix_colors, and to persist a set you like use save_palette.
| Name | Required | Description | Default |
|---|---|---|---|
| base | Yes | ||
| scheme | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden and covers read-only, deterministic, no side effects, and safety. It could mention potential errors or limits, but is sufficient.
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?
Concise and well-structured; purpose is front-loaded, followed by details. Every sentence adds value.
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?
Complete coverage given two parameters, output schema exists, and sibling context. Describes input, output, behavior, and alternatives.
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%, but description fully compensates by explaining base accepts hex, CSS name, RNV brand name, or saved-palette reference with example, and lists all schemes with alternative 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?
The description clearly states the tool generates a color harmony from a base color, specifying input formats and scheme options. It distinguishes itself from siblings like mix_colors and save_palette.
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 explicitly states when to use (expand one base color into a related set) and when not to (use mix_colors for blending, save_palette for persisting). Also notes it is safe to call repeatedly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_paletteAInspect
Retrieve one saved palette by name, returning its colors and metadata. Returns null if no palette by that name exists. Read-only; no side effects. Use when you already know the palette name; to list available names first use list_palettes, and to create or update a palette use save_palette.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description discloses that the tool is read-only with no side effects, and returns null if the palette does not exist. This fully informs the agent about expected 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?
Two concise sentences cover purpose, return value, null handling, and usage guidance. No extraneous words; every sentence adds value.
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 retrieval tool with a simple input, the description covers all essential aspects: operation, output, null case, side effects, and context (when to use). An output schema exists, so return details are covered.
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 coverage is 0%, and the description only repeats the parameter name without adding details like case sensitivity or format. However, the single parameter 'name' is self-explanatory, so minimal additional semantics are needed.
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 clearly states the verb 'retrieve' and the resource 'saved palette by name', distinguishing it from sibling tools like list_palettes and save_palette. It specifies what the tool returns: colors and metadata.
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 provides explicit guidance: use when the palette name is already known, and for listing names use list_palettes, for creating/updating use save_palette. This helps the agent decide when to invoke this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_palettesAInspect
List every saved palette as name + colors. Read-only; no side effects. Use to discover what palettes exist or to find a name before calling get_palette; to fetch one palette's full detail use get_palette, and to create or overwrite one use save_palette.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description fully carries the burden. It explicitly states 'Read-only; no side effects,' which is key behavioral info. Output schema covers return structure.
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?
Three sentences, front-loaded with main action, no fluff.
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 no parameters and an output schema, the description is complete: it states purpose, read-only behavior, and sibling differentiation.
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?
No parameters; schema coverage is trivially 100%. Description doesn't need to add parameter info. Baseline 4 for zero params.
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 clearly states 'List every saved palette as name + colors' and distinguishes from siblings by naming get_palette and save_palette for related but different actions.
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 says when to use ('to discover what palettes exist or to find a name') and when to use alternatives ('to fetch one palette's full detail use get_palette, and to create or overwrite one use save_palette').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mix_colorsAInspect
Blend up to 12 colors into one. Each color may be a hex (#d2bc93), a CSS name (red), an RNV brand name (brand gold, near-black), or a saved-palette reference (Spring line, or 'Spring line:2' for its 2nd swatch). Optional integer weights bias the blend (defaults to equal). mode selects the model: rgb/hsv/lab are digital blends (lab is perceptual and the default, best for on-screen color); paint mixes pigments via Kubelka-Munk physics (colors darken like real paint, use it for physical-media matching); ryb is the artist's color wheel; cmy is subtractive like printer inks. Returns hex and rgb. Read-only and deterministic: it computes a result and stores nothing, so it is safe to call repeatedly with no side effects. Use to combine multiple colors into a single blend; to convert one color between formats use convert_color, and to measure how far apart two colors are use color_difference.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | lab | |
| colors | Yes | ||
| weights | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Explicitly states that the tool is 'Read-only and deterministic: it computes a result and stores nothing, so it is safe to call repeatedly with no side effects.' This fully discloses behavioral traits beyond the minimal schema. No annotations contradict.
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?
Every sentence adds value. The description is front-loaded with the core purpose, then details parameters, modes, output, side effects, and alternatives. No redundant or filler content.
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 the tool's complexity (3 parameters, multiple modes) and the presence of an output schema, the description covers all necessary aspects: input formats, all mode behaviors, output format, and safety guarantees. It is complete enough for an agent to use 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?
With 0% schema coverage, the description compensates fully: explains that colors can be hex, CSS name, brand name, or palette references; weights are optional integers; mode lists all options (lab default, paint, rgb, hsv, cmy, ryb) with explanation of differences.
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 starts with 'Blend up to 12 colors into one,' which is a clear verb+resource. It also distinguishes from siblings by explicitly naming convert_color and color_difference for related but different tasks.
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?
States when to use: 'Use to combine multiple colors into a single blend' and when not to: 'to convert one color between formats use convert_color, and to measure how far apart two colors are use color_difference.' Provides clear guidance on alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
save_paletteAInspect
Persist a named color palette for later retrieval with get_palette or list_palettes. colors is a list of hex values; optional notes are stored as the palette's description. Author is recorded as RNVizion. This WRITES to the palette store and is the only tool here that does. Reusing an existing name overwrites that palette: save and update are the same call (an upsert), there is no separate update operation. Returns a durable flag: true if the palette reached durable storage (the HF Dataset) and will survive a restart, false if it saved to the local working copy only (which is lost on rebuild, e.g. when the Space HF_TOKEN is missing or lacks write scope). Use when the user wants to keep a set of colors under a name for reuse across sessions, such as a brand or launch palette; to read a palette back use get_palette, and to see what already exists use list_palettes. The saved name can then be passed to mix_colors, convert_color, and generate_harmony as a palette reference.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Unique key the palette is stored under. Reusing an existing name overwrites that palette (upsert). Can be referenced later by other tools as 'name:index', e.g. 'Spring line:2'. | |
| notes | No | Optional human-readable description stored as the palette's notes. | |
| colors | Yes | Ordered list of hex colors, each '#RRGGBB' (e.g. '#d2bc93'). Order is preserved; at least one required. |
Output Schema
| Name | Required | Description |
|---|---|---|
| name | Yes | Name the palette was stored under. |
| notes | Yes | Description stored on the palette; empty if none given. |
| colors | Yes | The hex colors saved, in order. |
| durable | Yes | True if the palette was written through to the durable HF Dataset and will survive a Space rebuild; False if it saved to the local working copy only (e.g. the Space HF_TOKEN is missing or lacks write scope), meaning it will be lost on the next restart. |
| color_count | Yes | Number of colors in the saved palette. |
| overwritten | Yes | True if a palette with this name already existed and was replaced; False if newly created. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully carries the burden. It discloses that the tool WRITES to the palette store, that it is an upsert (overwrites existing), that author is recorded as RNVizion, and explains the `durable` flag meaning including conditions for durability. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Every sentence serves a purpose: stating purpose, detailing parameters, explaining behavior, giving usage guidance. It is length but well-structured with no redundancy.
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 the 3 parameters, no nested objects, and presence of an output schema, the description covers all necessary context: input constraints, side effects, return value (durable flag), and cross-tool references. No gaps.
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 100%, but the description adds meaningful context: colors are hex values, notes are stored as description, name is a unique key that can be referenced as 'name:index'. This goes beyond the 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?
The description clearly states the verb 'Persist' and the resource 'named color palette'. It explicitly distinguishes the tool from siblings by noting it is the only tool that writes to the palette store and specifies that get_palette and list_palettes are for retrieval.
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 provides explicit when-to-use guidance ('when the user wants to keep a set of colors under a name for reuse across sessions') and explicitly names alternative tools for reading (get_palette) and listing (list_palettes). It also mentions that the saved name can be passed to other color tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
transform_textAInspect
Apply an exact, deterministic text transformation. operation is one of: UPPERCASE, lowercase, 'Title Case', 'Sentence case', camelCase, PascalCase, snake_case, CONSTANT_CASE, kebab-case, dot.case, 'iNVERTED cASE'. Read-only and deterministic: it returns the transformed string and changes nothing, safe to call repeatedly. Use whenever exact, reproducible case formatting matters rather than rewriting the text by hand or guessing the casing.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| operation | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly states 'Read-only and deterministic: it returns the transformed string and changes nothing, safe to call repeatedly.' This fully discloses behavioral traits beyond what annotations (none provided) would cover.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loads the action and key information, and contains no fluff. Every sentence adds value.
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 is comprehensive for a simple transformation tool, covering purpose, operations, and behavior. It does not explicitly describe the return format, but an output schema exists (not shown) to provide that detail.
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% with no parameter descriptions. The description adds critical meaning by enumerating all valid values for the 'operation' parameter and implying that 'text' is the input string. This compensates fully for the 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?
The description clearly states it applies an exact, deterministic text transformation and lists all supported case formats. It distinguishes itself from sibling tools which are color-related, making it unambiguous.
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 provides explicit when-to-use guidance: 'Use whenever exact, reproducible case formatting matters rather than rewriting the text by hand or guessing the casing.' It does not mention alternatives beyond manual rewriting, but sibling tools are unrelated, so no conflict.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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