The Emotion Dictionary
Server Details
The Emotion Dictionary's 402 emotions: define a word, resolve a feeling, body maps. CC BY 4.0.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.9/5 across 3 of 3 tools scored.
Each tool serves a distinct purpose: looking up a specific emotion by name, resolving a feeling description to emotions, and mapping an emotion's bodily signature. No functional overlap.
Two tools follow verb_noun pattern (define_emotion, resolve_feeling), while body_signature uses noun_noun, but all are clear and share consistent snake_case format.
Three tools is a reasonable size for a focused emotion dictionary server, covering essential lookup and resolution functions without being overly sparse.
Core functionality is covered: direct lookup, semantic resolution, and spatial representation. Minor gaps (e.g., listing all emotions) are non-critical for this domain.
Available Tools
3 toolsbody_signatureAInspect
Where an emotion lives in the body, from The Emotion Dictionary's body maps: regions on a 378 by 924 grid, each marked stirred or stilled.
| Name | Required | Description | Default |
|---|---|---|---|
| name_or_slug | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses output structure (regions on a 378x924 grid, each marked stirred or stilled). No annotations provided, but description adds valuable context beyond 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?
Single, front-loaded sentence with no waste. Efficiently conveys purpose and output format.
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?
Adequate for a simple tool with one parameter and no output schema. Describes source, grid dimensions, and output markers. Missing input format details and error cases.
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?
Single parameter 'name_or_slug' lacks description. Schema coverage is 0%. Description does not specify expected input format (e.g., emotion name pattern or slug requirements).
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 clearly states the tool maps emotions to body regions using The Emotion Dictionary's body maps, distinguishing it from sibling tools like define_emotion and resolve_feeling.
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?
Implied usage for retrieving body maps of emotions, but no explicit guidance on when to use versus siblings or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
define_emotionAInspect
Look up one emotion from The Emotion Dictionary by name or slug. Returns its identifier, family, short definition, valence, arousal, canonical colour, and the entry URL.
| Name | Required | Description | Default |
|---|---|---|---|
| name_or_slug | Yes | The emotion's name or URL slug, for example 'saudade' or 'Quiet joy'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description does not disclose behavioral traits such as idempotency, side effects, rate limits, or authentication requirements. For a read-only lookup, behavior is generally safe, but the description fails to explicitly confirm this, leaving gaps for the agent.
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 efficiently communicates purpose, input type, and output fields without any extraneous words or repetition. It is well-structured and front-loaded.
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 simplicity (single parameter, no output schema), the description provides sufficient detail about what it does and returns. However, it omits potential nuances like case sensitivity or error handling, which would be helpful for completeness.
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 a clear description of the single parameter. The tool description reinforces that it takes a name or slug and lists return fields, but adds minimal new information beyond the schema, warranting a baseline score of 3.
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 looks up one emotion by name or slug, specifying the resource (Emotion Dictionary) and listing the exact return fields. This distinguishes it from siblings like 'body_signature' and 'resolve_feeling' which presumably have different purposes.
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 implies usage for retrieving emotion details but provides no explicit guidance on when to use it versus alternative tools. It lacks when-not-to-use or specific conditions, making it adequate but not helpful for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
resolve_feelingAInspect
Describe a feeling in plain words and get the five closest named emotions from the 402 in The Emotion Dictionary, ranked by meaning.
| Name | Required | Description | Default |
|---|---|---|---|
| description | Yes | A plain description of the feeling, up to 500 characters. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool returns five emotions ranked by meaning but does not disclose whether it is a read-only operation, any side effects, auth requirements, or rate limits. For a lookup tool, the missing safety disclosure is acceptable but not thorough.
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?
Single sentence of 20 words, clearly front-loaded with action and outcome. Every word is meaningful, no redundancy. Ideal conciseness.
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 (1 parameter, no output schema), the description fully explains input and output. Siblings are listed but the tool's role is self-contained. Completeness is sufficient for an AI 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?
Schema description coverage is 100% with the 'description' parameter well-documented (plain text, max 500 chars). The tool description adds little beyond 'in plain words' and reiterates 'five closest named emotions'. With full schema coverage, a score of 3 is appropriate as the description does not add significant new 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?
Description clearly states the verb 'describe' and 'get', the resource 'The Emotion Dictionary with 402 emotions', and the outcome 'five closest named emotions ranked by meaning'. This distinguishes it from siblings like 'define_emotion' which likely defines a single emotion, and 'body_signature' which may map physical signals.
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?
Description implies usage when one has a plain feeling description and wants the closest emotions. However, it does not explicitly state when not to use or mention alternatives among siblings. The context is simple enough that the use case is clear, but lacks exclusion guidance.
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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