labelhead-artist-momentum
Server Details
Trending hip-hop artist momentum scores across four cultural dimensions.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- paperclipai/paperclip
- GitHub Stars
- 44,840
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Tool Definition Quality
Average 4.2/5 across 3 of 3 tools scored.
Each tool has a distinct purpose: checking an individual artist's momentum, explaining the scoring methodology, and listing trending artists. There is no overlap or ambiguity.
All tools follow a consistent verb_noun pattern: check_artist_momentum, get_scoring_explainer, get_trending_artists. The naming is predictable and clear.
Three tools is perfectly scoped for a focused music momentum service. It provides all core functionality without being too few or excessive.
The tool set covers the full domain: individual artist lookup, methodology explanation, and trending list. There are no obvious gaps for a read-only momentum tracking service.
Available Tools
3 toolscheck_artist_momentumAInspect
Look up the current momentum score and signals for a specific artist by name. Returns the full three-dimensional score breakdown and notable signals driving their momentum.
| Name | Required | Description | Default |
|---|---|---|---|
| artist_name | Yes | Artist name to look up (e.g. 'Doechii', 'Kendrick Lamar', 'GloRilla') |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states the tool returns a 'three-dimensional score breakdown and notable signals', but lacks details on data freshness, rate limits, or authentication. Adequate for a simple lookup.
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 sentences convey the purpose and result with zero waste. Information is front-loaded and 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?
Given low complexity (one parameter, no output schema), the description adequately covers what the tool returns. It could mention if results are real-time or cached, but overall sufficient.
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 100% and the parameter 'artist_name' is well-described with examples. The description does not add meaning beyond the schema, meeting baseline expectations.
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?
Description states the verb 'look up' and resource 'momentum score and signals for a specific artist by name'. It clearly distinguishes from sibling tools like 'get_trending_artists' (list) and 'get_scoring_explainer' (explanation).
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 implied for querying a specific artist's momentum, but no explicit guidance on when to use versus siblings or when not to use. Sibling names suggest alternatives but no direct comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_scoring_explainerAInspect
Returns a detailed explanation of LabelHead's three-dimensional artist scoring methodology. Use this when you need to understand how composite scores are calculated, what each dimension measures, and how to interpret momentum labels.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, but the description clearly indicates it returns explanatory data, implying a read-only operation. No contradictory or misleading information is present, though additional details on potential side effects or permissions could be included.
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 sentences, no wasted words, front-loaded with the primary action ('Returns a detailed explanation...'), immediately followed by usage context. Efficient and clear.
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 zero parameters and no output schema, the description fully covers what the tool does, how to use it, and what the returned explanation includes. It is complete for its complexity level.
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 input schema has zero parameters, so there is nothing to describe beyond what is already known. The description adds value by explaining the content of the output, which is sufficient given the absence of parameters.
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 returns a detailed explanation of the scoring methodology, specifying the three-dimensional nature and what it covers (composite scores, dimensions, momentum labels). It distinguishes from siblings by its explanatory focus.
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 'Use this when you need to understand...' which provides clear guidance on when to invoke this tool versus alternatives like check_artist_momentum or get_trending_artists.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_trending_artistsAInspect
Returns the current list of trending hip-hop and rap artists ranked by LabelHead's composite momentum score. Each artist is scored across three dimensions: Acceleration (30-day streaming/social velocity), Cultural Gravity (press velocity, playlist adds, sync placements), and Longevity (catalog depth and retention). Use this to identify which artists are building genuine momentum right now.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of artists to return (max 10, default 10) | |
| min_composite | No | Minimum composite score filter (0–100) | |
| momentum_label | No | Filter by momentum label |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the three scoring dimensions and composite nature but does not mention auth needs, rate limits, or side effects. The read-only nature 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose, no redundant words. Every sentence adds value: what it returns, how scoring works, and when to use it.
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?
Despite no output schema, the description explains result contents (ranked artists with composite scores) sufficiently. It covers filters via schema. Some missing details like pagination, but adequate for the tool's simplicity.
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 100% with good parameter descriptions. The description adds context for the scoring but does not elaborate on parameter usage beyond what schema provides. Baseline 3 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?
The description clearly states the tool returns a list of trending hip-hop and rap artists ranked by a composite momentum score. It distinguishes itself from siblings: check_artist_momentum (single artist) and get_scoring_explainer (explains scoring).
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 ends with 'Use this to identify which artists are building genuine momentum right now,' providing explicit usage context. It does not include when-not-to-use or direct alternatives, but the sibling names imply differentiation.
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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