elgato-keylight

by butterflyskies

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clear, distinct purpose: basic on/off/toggle, brightness/temperature control, status query, presets, and specific effects. Descriptions like 'alert_flash' vs 'flash_lights' highlight urgency vs casual use, preventing confusion.
Naming Consistency4/5
Most tools follow a verb_noun pattern (e.g., 'turn_on', 'set_brightness'), but 'celebrate' is a single-word verb, and 'dim_for_attention' uses a preposition, introducing slight inconsistency.
Tool Count5/5
13 tools cover all essential controls (power, brightness, temperature, status) plus presets and effects without being excessive. The count is well-scoped for the domain.
Completeness5/5
The tool set includes CRUD-like operations (turn on/off, set brightness/temp, get status), multiple presets (apply_preset, set_mood_lighting), and fun effects, leaving no obvious gaps for typical usage.
Average 3.6/5 across 13 of 13 tools scored. Lowest: 2.8/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the basic action, omitting any details about side effects, feedback, or whether the operation is irreversible. The simple behavior is implied but not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with front-loaded action. No wasted words, but the docstring format (Args) adds minimal overhead.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple with one optional parameter. An output schema exists but its content is not described; the agent might need to know what the response contains (e.g., status, errors). Somewhat complete given simplicity, but missing output semantic.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. The description only mentions 'light_names' as optional, adding no nuance beyond the schema. It does not explain the meaning of 'names' (e.g., device IDs, user-friendly names) or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Turn off all (or specified) lights', which is a specific verb-resource pair. It distinguishes from siblings like turn_on and toggle_lights, but could be more explicit about the scope of 'specified lights'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like dim_for_attention or flash_lights. The description does not mention prerequisites or context for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavioral traits. It mentions applying a preset but does not specify if it overrides all lights, whether it resets unsaid settings, or any side effects. The mutation nature is clear, but missing details like immediate effect or reversibility.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two short sentences plus a list of presets and Args section. Every part adds value, and the structure is front-loaded with the core action. Could be slightly more compact by merging lists, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with an output schema (context indicates it exists), the description adequately defines the action and parameters. However, it lacks details about what happens upon apply (e.g., all lights change, effect duration) and does not reference the output. Acceptable but not robust.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It explains preset_name as 'Name of the preset to apply' and light_names as 'Optional list of light names', which adds some meaning beyond the schema (which only defines types). However, it could be more descriptive, e.g., list of allowed presets or format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it applies a lighting preset, lists available presets (bright, dim, warm, cool, video), which distinguishes it from sibling tools that set individual attributes like brightness or temperature. The verb 'apply' combined with 'named lighting preset' is specific and contextual.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like set_brightness or set_mood_lighting. It does not mention prerequisites, preferred scenarios, or situations where other tools are better suited. The usage context is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lacks behavioral details beyond the basic operation, such as whether changes are persistent or reversible, permission requirements, or side effects like turning off lights when brightness is 0. Since no annotations are provided, the description bears the full burden but fails to disclose these traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using only two sentences to convey purpose and parameters. While it could include more behavioral details, it avoids unnecessary repetition and is front-loaded with the essential action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the basic purpose and parameters but misses details like error handling (e.g., out-of-range brightness, invalid light names) and return value structure. Given that the tool has an output schema, return values are somewhat covered, but the behavior when light_names is null (i.e., all lights) is only implied.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds the valid range (0-100) for brightness and clarifies that light_names is optional, which supplements the input schema's type and default. However, with 0% schema description coverage, the description does not provide rich semantic detail like why brightness might have a cap or how light_names interact with the function.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (set), resource (lights), and scope (all or specified). This verb+resource+scope combination effectively distinguishes it from sibling tools like set_mood_lighting or set_temperature, which affect different properties.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like dim_for_attention or flash_lights, which might also affect brightness. The description does not mention when not to use it or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It only mentions the action and parameter, omitting behavioral traits such as error handling, permission requirements, or side effects (e.g., does turning on all lights affect all rooms?).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) and front-loaded with the main purpose. However, the 'Args:' formatting adds minor verbosity but is acceptable for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool with an output schema, the description covers the basics. However, it lacks details on return values, error states, or behavior when no lights are specified (e.g., all lights vs. nothing), leaving some ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It repeats the schema's 'light_names' parameter as 'Optional list of light names' without adding format, restrictions, or behavior (e.g., case sensitivity, invalid names). Little value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Turn on') and the resource ('lights'), with an explicit scope ('all or specified'). It effectively distinguishes from siblings like 'turn_off' and 'toggle_lights' by name and verb specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (turn on all or by name) but provides no explicit guidance on when to use this tool versus alternatives like 'toggle_lights' or 'set_brightness'. No when-not-to-use or cross-references are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 key behavior of restoring original state, which is valuable. However, it does not mention other behavioral traits such as whether lights must be on, permissions required, or side effects beyond the flash.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, with the purpose stated in the first sentence and parameter descriptions immediately following. Every word earns its place with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no enums, output schema exists), the description covers the core action and state restoration. It is nearly complete, though adding usage guidance would make it fully robust.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must add meaning. It explains that 'flashes' is the number of alert flashes (default 5) and 'light_names' is an optional list. This adds some context but does not fully describe parameter semantics, e.g., what constitutes a valid light name or the range of flashes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs an urgent attention-getting flash at max brightness and restores original state. It distinguishes from siblings like flash_lights and pulse_lights by emphasizing urgency, but does not explicitly differentiate from all similar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when or when not to use this tool versus alternatives like flash_lights, celebrate, or dim_for_attention. The phrase 'urgent attention-getting' implies a use case but lacks clear context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It mentions 'restores original state' which is good, but omits whether the operation is blocking, concurrency, or required permissions. The core behavior is described adequately for a simple tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise: two sentences plus two one-line parameter descriptions. The main purpose is front-loaded, no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity and existence of an output schema (not shown), the description covers the essential behavior and parameter usage. Could mention default scope (all lights if not specified) or error handling, but overall it's nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description must compensate. It provides brief explanations for both parameters ('Number of flashes', 'Optional list of light names'), which adds minimal value beyond types and defaults. Baseline is 3 due to low coverage, and the compensation is adequate but not exceptional.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool flashes lights on/off to get attention or say hello, and restores original state. It provides a specific verb and resource, but doesn't explicitly differentiate from sibling tools like pulse_lights or alert_flash.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, no prerequisites or exclusions. The description implies usage for momentary attention but lacks explicit when-to-use or when-not-to-use advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the action persists and does not restore previous state, which is valuable behavioral context. With no annotations, more could be said (e.g., effects on other settings), but the persistence note is helpful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with three sentences, listing moods and parameters without verbosity. Slightly more structure could improve readability, but it remains efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter, the description covers purpose, behavior, and parameter options. While it omits error handling or return value details (output schema exists), it is generally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description lists available moods (cozy, focus, relax, energize, movie) for the single parameter, adding meaning beyond the schema's plain string type. This compensates for 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Set a mood lighting preset', specifying the verb and resource. However, among sibling tools like 'apply_preset', it does not differentiate itself, limiting clarity to 4.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description implies use for changing mood presets but provides no when-not-to-use or sibling comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the slow dimming behavior and state restoration, but lacks details like duration, rate, or side effects on other lights. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) and front-loaded with the core purpose. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one optional parameter and an output schema, the description covers the main behavior and restoration. However, it could benefit from clarifying scope (e.g., if no lights specified, does it apply to all?) or duration. Still, fairly complete for a simple interaction.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no meaning beyond the input schema for the single parameter 'light_names'. Schema description coverage is 0%, and the description merely repeats the parameter name without clarifying its semantics (e.g., default behavior when null).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (slowly dim lights), the resource (lights), and the purpose (get attention without being jarring). It also mentions restoring original state, distinguishing it from more flashy sibling tools like flash_lights or pulse_lights.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for subtle attention-getting but lacks explicit guidance on when to use this tool vs alternatives. No when-not conditions or explicit sibling differentiation provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the core behavior of toggling lights, but without annotations, it does not mention side effects, state outcomes, or any constraints. It is adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using only two lines to convey purpose and parameter details. It is front-loaded and contains no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple toggle tool with an output schema, the description is minimally complete. However, it omits edge cases, permission requirements, or return behavior, leaving room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description effectively explains the 'light_names' parameter as an optional list. This adds crucial meaning beyond the schema's raw type definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'toggle' and resource 'lights', with an explicit note about all or specified lights. It distinguishes itself from siblings like turn_on, turn_off, and flash_lights by focusing on toggling state.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use toggle_lights versus turn_on/turn_off or other alternatives like flash_lights. The description lacks context for appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavioral traits. It does not confirm that the operation is read-only, safe, or free of side effects. The output schema exists but is not referenced. The description lacks transparency about what the tool returns or any potential errors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief, with a clear purpose sentence followed by a structured Args block. No extraneous information. It is front-loaded and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with one parameter, the description covers the core functionality. The existence of an output schema reduces the need to describe return values. Minor omission: no mention of error handling or invalid input behavior, but overall it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'light_names' is thoroughly explained: it is optional, listed with example values, and its behavior when omitted is described. This adds meaningful context beyond the schema's type-only definition. Schema coverage is 0% but the description fully compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get the current status of all (or specified) lights', specifying the verb (get), resource (light status), and scope (all or specific). Among sibling tools that are mostly mutative or alert-based, this read-only query is distinct and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to specify light names vs not, but does not provide explicit guidance on when to choose this tool over alternative read tools or when not to use it. The context of sibling names implies it's for reading status, but no direct usage guidelines are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Explains the temperature scale (Elgato units with approximate Kelvin values), but omits behaviors like what happens if lights are off or if values are out of range. No annotations to supplement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus an Args list. Front-loaded with main purpose. Every sentence adds value, no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple tool with two parameters. Describes the key parameter (temperature) well. Could mention that temperature range applies per light, but not critical given sibling context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds significant value for the temperature parameter by providing units and mapping to Kelvin. The light_names parameter is minimally described (optional list), but the schema is sparse (0% coverage) so the description helps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action (set), resource (color temperature), and scope (all or specified lights). Distinct from sibling tools like set_brightness and toggle_lights.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this vs alternatives. The purpose is clear but lacks context like prerequisites or when to avoid usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the main behavior (pulse) and restoration of original state, but lacks detail on duration, interruption, or side effects. Sufficient but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is very concise: one sentence for purpose, then two bullet-like lines for args. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters, no required params, and no annotations, the description covers the tool's purpose, behavior, and arguments. For a simple tool, it is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% coverage; description fully explains both parameters: cycles (number of pulse cycles, default 3) and light_names (optional list). Adds significant meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool smoothly pulses light brightness up and down and restores original state. It distinguishes from siblings like flash_lights (flashing) and dim_for_attention (dimming).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly provide usage guidance or contrast with alternatives. It implies use when a pulsing effect is desired but lacks when-not-to-use or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It explicitly states the effect is temporary ('Restores original state when done'), which is key behavioral information. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two clear sentences: the first states the action and purpose, the second adds critical behavioral detail. No wasted words, well front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and existence of an output schema, the description is complete. It explains what the tool does and its non-destructive nature. Could optionally mention prerequisites like lights being on, but not necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the description does not need to add parameter details. Baseline score of 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs a 'fun alternating color temperature dance' for celebrating a win. It distinguishes itself from sibling tools like set_brightness or pulse_lights by being a celebratory effect.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies when to use it ('celebrating a win') but does not mention when not to use it or suggest alternatives. Usage context is implied but not explicit.
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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