Venice MCP Server

Official

by veniceai

Overview Schema Related Servers Score Discussions

TypeScript

Remote

Server Quality Checklist

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Latest release: v0.2.0
Disambiguation4/5
Tools are mostly distinct by domain and action. The chat-related tools (venice_chat, venice_chat_with_character, venice_responses) could cause some confusion as they all handle conversational AI but differ in context and API semantics. However, the majority of tools target unique functionalities.
Naming Consistency3/5
All tools share the 'venice_' prefix, but the naming pattern varies: some follow noun_verb (e.g., image_edit), others are noun_noun (audio_quote) or use domain+action (web_scrape). While readable, the lack of a uniform verb_noun structure reduces consistency.
Tool Count2/5
With 31 tools, the server exceeds the typical well-scoped range. Although the breadth of features (chat, images, video, audio, web, crypto, payments) justifies many endpoints, the count feels heavy and might benefit from grouping or modularization.
Completeness4/5
The tool set covers a wide range of Venice API capabilities: text, image, audio, video, web, and crypto. Obvious CRUD gaps are absent; most workflows have generate/status/complete patterns. Minor omissions (e.g., no dedicated tool for updating a chat or image) are not critical.
Average 3.6/5 across 31 of 31 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on May 16, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
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.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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?
Without annotations, the description partially discloses behavior (URL fetching, multipart upload, auth support) but omits key details like output format, rate limits, or privacy implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (2 sentences) but at the cost of omitting essential details about parameters and usage. It is front-loaded but incomplete.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters and no output schema, the description lacks completeness. It does not explain parameter options, expected return values, or provide examples, leaving the agent under-informed.
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?
Schema coverage is 0%, and the description fails to explain any parameter except audio_url by implication. No details on model, language, or response_format choices.
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's purpose ('Transcribe audio') and distinguishes it from siblings like venice_video_transcriptions by specifying it handles audio URLs. It also explains the server-side fetching mechanism.
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 over alternatives such as venice_video_transcriptions or venice_tts. The description mentions auth methods but does not provide usage context or exclusions.
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 present, so the description must disclose behavioral traits. It only states the action (marking as downloaded) and auth support, but does not explain side effects (e.g., whether the job is deleted or what other state changes occur). The title suggests 'cleanup', but this is not in the description.
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 sentences, front-loading the core action. However, it could benefit from a more structured breakdown of parameters and usage context without adding bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, annotations, and parameter descriptions, the description is insufficient for a mutation tool. It fails to explain return values, error conditions, or lifecycle positioning (e.g., 'must be called after status is completed').
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?
Schema description coverage is 0%, and the description does not explain the two required parameters (model and queue_id). The description adds no meaning beyond the schema field names, forcing the agent to guess their roles.
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 'Mark a completed music job as downloaded', which is a specific verb+resource combination. It distinguishes from sibling tools like venice_music_generate and venice_music_status, making the purpose unambiguous.
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 mentions authentication methods but provides no guidance on when to use this tool versus alternatives (e.g., after music_status returns 'completed'). No explicit exclusions or prerequisites are given.
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 fails to disclose key behavioral traits such as expected output format, handling of invalid URLs, or limitations on video length. Only auth method is mentioned.
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?
A single sentence that is concise and to the point, covering purpose and auth. Could be slightly restructured to include more detail without losing conciseness.
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 2 parameters and no output schema, the description provides the core function and auth. Missing details on return value and expected behavior make it minimally adequate.
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?
The description adds context for the url parameter (YouTube URL only) but does not explain the response_format parameter despite being an enum. Schema coverage is 50%, and description does not fully compensate.
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 'Transcribe a YouTube video URL' with specific verb and resource. It also mentions authentication methods. However, it doesn't specify what form the transcription output takes, which could be clarified.
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 sibling tools like venice_asr or venice_video_quote. Does not indicate prerequisites or exclusions.
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 provided, so description carries full burden. Mentions POST method and auth, but does not disclose read-only nature, error handling, or polling behavior. Lacks behavioral context for a status check.
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 concise sentences, front-loaded with purpose. Could include a hint about the optional parameter but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite simple scope, description omits output format, error codes, and purpose of optional parameter. Incomplete for a tool with 3 params and no output schema.
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?
Schema coverage is 0%. Description only repeats parameter names from schema (model, queue_id) without adding meaning. Fails to explain the optional delete_media_on_completion parameter or any format constraints.
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 'Check status of a queued music job', identifying the verb and resource. Distinguishes from sibling tools like venice_music_generate and venice_music_complete by focusing on status retrieval.
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?
Implies usage after job creation by mentioning queue_id, but does not explicitly state when to use this tool versus alternatives or provide exclusions. Auth info is helpful but not comparative.
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?
Without annotations, the description adds behavioral context such as 'uncensored' (NSFW allowed) and authentication methods (x402 wallet auth and API key). However, it lacks details on response format, streaming, error handling, or rate limits.
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 sentences, front-loading the key purpose. It efficiently conveys essential info without unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 4 parameters, no output schema, and no annotations, the description is incomplete. It does not explain response behavior, default values, or how tool calling works, leaving significant gaps for an AI agent.
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 low (25%), and the description adds no meaning for parameters like model, temperature, or max_output_tokens beyond what the schema provides. It mentions 'tool support' but does not explain any tool-related parameter.
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 is an 'OpenAI-compatible Responses API' for single-turn or multi-turn interactions with tool support, providing a specific verb and resource. However, it does not differentiate itself from sibling tools like venice_chat or venice_chat_with_character.
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 API-compatible calls and mentions authentication options, but it provides no explicit guidance on when to use this tool over alternatives. No when-not-to-use or exclusion criteria 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 provided, so description carries full burden. It discloses authentication methods ('x402 wallet auth' and API key) and uncensored nature, but omits details about output format, streaming, rate limits, or error handling. The 'OpenAI-compatible' comparison helps but is vague.
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?
Three sentences, no filler. First sentence states purpose, second highlights uncensored feature, third covers auth. Information is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complex tool (chat completion with 6 parameters, no output schema, no annotations) but description only covers auth and censoring. Missing details on response format, model selection guidance, streaming, or cost. Not sufficient for an agent to use reliably.
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 low (33% - only model and messages have descriptions). Description adds default model info and implies messages can contain NSFW content, but does not explain stop, top_p, max_tokens, or temperature. Agent cannot infer meaning for 4 of 6 parameters.
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 the tool runs 'OpenAI-compatible chat completion' via an 'uncensored LLM catalog', listing many models. It distinguishes from siblings like venice_chat_with_character (character-based) and venice_list_models, but could be more explicit about differentiation from venice_responses.
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?
Description notes 'Uncensored: NSFW prompts allowed', providing a key usage condition, but does not explicitly state when to use this tool versus alternatives like venice_chat_with_character. Usage is implied rather than guided.
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 convey behavioral traits. It only discloses the return type (base64 PNG) and auth support. It does not mention side effects, rate limits, image accessibility requirements, or whether the original image is modified. This is insufficient for a mutation tool.
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 highly concise, with only two sentences that convey core purpose and return format. However, it could be slightly more structured to include parameter hints, but within its brevity it is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters (2 required), no output schema, and no annotations, the description is too brief. It fails to explain the role of the prompt, safe_mode, aspect_ratio, or model defaults, leaving significant gaps for effective use.
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 only 40%, and the description adds no explanation for the parameters. The prompt, safe_mode, and aspect_ratio are not explained beyond the schema. The description does not compensate for the low schema coverage.
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 'Edit an image with a prompt. Returns base64 PNG.', specifying the action (edit), resource (image), and output format. The name and title align. Among siblings like 'venice_image_multi_edit' and 'venice_image_remove_bg', this tool is distinct.
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 mentions supported authentication methods ('x402 wallet auth' and 'API key'), providing some usage context. However, it lacks guidance on when to use this tool versus alternatives such as 'venice_image_multi_edit' or 'venice_image_generate', and does not specify prerequisites or conditions.
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 carries full burden. It discloses output format (transparent PNG base64) and auth methods, but lacks details on limitations (e.g., image size, format support, error conditions).
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, no wasted words. Essential information is front-loaded ('Remove image background').
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 one parameter and no output schema, the description covers purpose and auth but misses input constraints and error handling, making it adequate but not complete.
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?
Schema has one parameter 'image_url' with 0% description coverage. The description does not add any information about the parameter, such as accepted URL schemes, file size limits, or required image properties.
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 'Remove image background; returns a transparent PNG (base64).' This is a specific verb-resource pair that distinguishes it from sibling tools like venice_image_generate or venice_image_edit.
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 mentions auth support (x402 wallet and API key) but does not explicitly state when to use this tool versus alternatives or when not to use it. Usage is implied by the tool name.
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 mentions authentication methods but does not disclose behavioral traits such as output format, error handling, rate limits, or whether the operation is destructive. The description lacks crucial context beyond basic functionality.
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 consists of two short sentences, conveying essential information without any redundant or irrelevant content. Every word serves a purpose, making it highly efficient for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters (1 required), no annotations, and no output schema, the description is insufficient. It does not explain return values, behavior of unseen parameters, or how emotion tags integrate with the input. The presence of many sibling tools demands more context to differentiate, but the description is too minimal.
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 only 40% (input and voice have descriptions). The description adds value by mentioning cloned voices and emotion tags, which relate to the input and voice parameters. However, it provides no additional meaning for the model, speed, and response_format parameters, which lack schema descriptions. It partially compensates but is not comprehensive.
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 'Convert text to speech', specifying the action and resource. It distinguishes from sibling tools like venice_asr (speech recognition) and venice_music_generate by mentioning cloned voices and emotion tags, which are unique features.
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 venice_asr for speech recognition or venice_chat for conversation. There are no explicit when-to-use or when-not-to-use instructions, leaving the agent without comparative context.
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?
Without annotations, the description carries the burden. It discloses key behaviors: fetches URL, uploads base64, returns PNG. However, it omits explanation of parameters like 'replication' and 'enhance', and there is no mention of potential side effects or limits.
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, front-loaded with purpose, no redundancy. The second sentence adds technical detail (base64, auth) but is still concise. Could be slightly more structured 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?
Given no output schema and 4 parameters, the description covers the main operation and auth, but lacks documentation on the 'enhance' and 'replication' parameters. Return format is stated, but parameter semantics are incomplete.
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 only 25%. The description adds minimal parameter info beyond the schema: only hints at scale range (1-4). 'Enhance' and 'replication' are not explained, so the description does not compensate for low schema coverage.
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 'Upscale an image (1-4× scale)' with a specific verb and resource. It distinguishes from sibling tools like venice_image_generate or venice_image_edit, all of which 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.
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 (e.g., other image tools). It mentions auth methods (x402 wallet, API key) but does not provide context on prerequisites or when not to use it.
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?
Discloses authentication behavior (API key required) beyond missing annotations, but lacks details on pagination, response structure, or what 'public' entails.
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?
Extremely concise—two sentences, front-loaded with purpose, no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no output schema, and no annotations, the description is insufficient. It omits parameter semantics, expected output, and comparisons to sibling tools.
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?
No parameter descriptions are provided despite 0% schema coverage. The description does not explain the purpose of tag, limit, offset, or search parameters.
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?
Description clearly states the tool lists public Venice characters, which is a specific verb+resource. It distinguishes from sibling tools like venice_chat_with_character and venice_list_models.
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?
Description provides authentication constraint (API key required, not x402 wallet auth) but does not explicitly state when to use this tool versus alternatives like searching or filtering characters.
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?
Explicitly states the destructive action of deleting server-side media, which is critical. No annotations provided, so description carries full burden. Lacks details on irreversibility or scope of deletion.
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, no filler. First sentence states purpose and side effect, second adds auth context. Efficiently front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given destructive nature, no output schema, and 0% schema coverage, the description is incomplete. Lacks parameter details, consequences, and any usage examples or warnings.
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?
Schema has 0% description coverage, and the description does not explain the parameters ('model' and 'queue_id') beyond their names. Adds no value over 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?
Clearly states the action ('Mark a completed video as downloaded') and the side effect ('deletes server-side media'). Distinguishes from sibling tools like venice_video_generate and venice_video_status.
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?
Mentions supported auth methods (x402 wallet and API key), providing context for when the tool can be used. However, no explicit guidance on when to use vs. alternatives or prerequisites.
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, the description carries full burden. It discloses POST method, status enum values, and auth methods. However, it does not state whether the operation is pure read-only (or if it has side effects), or describe response structure, error conditions, or rate limits.
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 with clear front-loading: first sentence states purpose, second adds essential details (status enum, method, auth). No redundant or unnecessary words.
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?
Given the tool's simplicity (status check with 3 params, no output schema), the description covers key aspects: purpose, status values, auth. Missing details include response format, polling recommendations, and behavior when job not found or errors.
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 67%, and the description only references model and queue_id in the body format without adding semantic value beyond the schema descriptions. The optional parameter delete_media_on_completion is not mentioned, leaving it undocumented.
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 checks status of a queued video job, with specific verb 'Check status' and resource 'video job'. It distinguishes from siblings like venice_music_status by specifying 'video', and mentions status enum values, making purpose unambiguous.
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 venice_video_complete or polling strategies. It implies use after venice_video_generate by mentioning queue_id origin, but does not elaborate on context or preconditions.
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 solely carries the burden. It mentions auth methods but omits behavioral details like idempotency, rate limits, whether operations are read-only or writable, and error handling. The agent lacks critical safety info.
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 efficient: two sentences covering purpose, example methods, network listing, and authentication. Every sentence adds value with no wasted words.
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?
Given three parameters, no output schema, and no annotations, the description covers core purpose, networks, and auth but lacks return value details, error handling, and rate limit info. It's adequate for a simple proxy but incomplete for fully autonomous use.
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 only 33% (only 'network' has a description). The description adds clarity about network IDs (full network id, NOT just 'base') and example methods, but doesn't elaborate on 'rpc_params' or 'rpc_method' beyond examples, leaving gaps.
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 proxies JSON-RPC calls to supported blockchains, gives concrete method examples (eth_call, eth_blockNumber), and lists network IDs. This distinguishes it from siblings like venice_chat, as it's the only crypto RPC tool.
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 tells how to list all available networks (GET endpoint) and mentions authentication methods (x402 wallet auth, API key). However, it doesn't explain when to use this tool vs alternatives (e.g., if other RPC tools exist) or provide exclusion criteria.
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, the description must carry the burden. It discloses uncensored nature and auth methods (x402 wallet, API key), but lacks information on rate limits, model availability, costs, or return format.
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 three sentences, front-loading the core action. Every sentence adds information with no redundant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, no output schema, no annotations), the description is insufficient. It omits return format, model selection guidance, and performance expectations.
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 only 22%, yet the description does not elaborate on any parameters beyond listing models. It adds no value over the input schema, missing the opportunity to clarify parameter usage or defaults.
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 'Generate an image' and lists supported models. It distinguishes this tool from siblings like venice_image_edit by focusing on generation from scratch.
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 image generation and mentions uncensored capability, but does not explicitly state when to use this tool versus alternatives (e.g., editing, style transfer) or provide any 'when not to use' guidance.
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, the description must disclose behavior. It states the output is base64 PNG and authentication methods, but lacks details on destructive nature, rate limits, or other side effects. Adds some value beyond the name.
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 concise sentences with no filler. Front-loads key purpose and output format. Every sentence adds value.
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?
Complex tool with 4 parameters and no output schema. Description covers core function and auth but leaves out details on parameter usage and return format beyond base64. Adequate but could be more thorough.
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 that the prompt edits images together, but does not describe model, aspect_ratio, or image_urls beyond their presence. Partially helpful, but gaps remain.
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 edits multiple images together with a single prompt, specifying multi-image composition/outpainting and output format (base64 PNG). It distinguishes from siblings like venice_image_edit and venice_image_generate.
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 venice_image_edit or venice_image_generate. The description mentions authentication methods but does not direct the agent to appropriate use cases.
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 disclose behavioral traits. It mentions authentication methods but fails to disclose critical behavior such as return format, rate limits, data handling, or cost implications. For an embeddings tool, the return vector format and batch limits are essential.
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 with no redundant words. Information is front-loaded: first sentence describes function, second sentence adds authentication context. Every phrase earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description does not explain return values or usage context. For a machine learning embeddings tool, key details like output vector dimensions, batch size limits, and typical use cases are missing. The description is too minimal for practical use.
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 schema coverage at 67%, the description adds value by stating 'OpenAI-compatible', which implies the parameters follow OpenAI's convention (model ID, input text, encoding format). This helps an agent infer parameter semantics beyond the schema's minimal descriptions.
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?
Description clearly states 'Compute embeddings for text input' with explicit verb 'Compute' and resource 'embeddings'. It also notes OpenAI compatibility, which distinguishes it from other Venice tools. With 30+ sibling tools, this clarity is effective.
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?
Description mentions two authentication methods (x402 wallet auth and API key) but provides no guidance on when to use this tool versus alternatives like venice_chat or venice_responses. No explicit when/when-not conditions or use cases.
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, the description discloses server-side fetching, multipart upload, and auth methods (x402, API key). However, it omits potential limitations like file size, supported formats beyond the title, and error behavior.
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 two sentences, front-loaded with the core action, and includes only essential technical details. No wasted words.
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?
Given no output schema, the description fails to mention return format (e.g., plain text) or behavior on large files/errors. Basic functionality is covered, but completeness is only adequate.
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 add meaning for the single 'url' parameter. It clarifies that the URL points to a document, but gives no format constraints or size limits, providing minimal compensation.
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 'Extract text from a document URL,' specifying the verb and resource. The title lists exact formats (PDF/DOCX/EPUB/PPTX/XLSX), and the tool is distinct from siblings like venice_web_scrape or venice_chat.
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 tool versus alternatives (e.g., venice_web_scrape). The description implies usage for document URLs but does not state exclusions or preferred contexts.
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 exist, so the description bears full responsibility. It mentions auth support (x402 wallet, API key) but lacks details on other behavioral aspects like rate limits, size limits, redirect handling, or JavaScript execution.
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 two concise sentences with no extraneous information. It is front-loaded with the primary action and additional auth context.
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?
Given the tool's simplicity, the description provides essential purpose and auth info. However, it lacks details about return format (beyond 'markdown') and is silent on output structure, which is not covered by any output schema.
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%; the description does not explain individual parameters. The schema defines 'url' and 'format' (with enum options), but the description only says 'into markdown text', ignoring the format parameter variability.
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 (scrape), resource (one URL), and output format (markdown). It also mentions additional auth methods, distinguishing it from other tools like venice_web_search.
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 scraping a single URL but does not explicitly state when to use this tool versus alternatives or when not to use it. No exclusions or comparative guidance is 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?
No annotations are provided, so the description carries the full burden. It mentions it is Firecrawl-backed and returns ranked results with snippets. It does not explicitly state it is read-only or non-destructive, but the nature of a web search implies that. More information about rate limits, response structure, or authentication requirements would improve transparency.
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 two sentences, front-loaded with the primary purpose ('Search the web'). It is efficient and contains no fluff. The auth mention is valuable but could be placed at the end. Overall, it earns its length.
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 search tool with two parameters and no output schema, the description covers the main purpose and mentions the backend (Firecrawl) and auth options. However, it lacks details about output format (beyond snippets), pagination, error handling, and any limitations. It is minimally adequate but not comprehensive.
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%, and the description does not elaborate on the parameters. 'query' is implied by 'Search the web', but 'limit' is not explained. The schema provides constraints (min, max) but no descriptions. For a simple tool with two parameters, the description adds marginal 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 'Search the web (Firecrawl-backed). Returns ranked results with snippets.' The verb 'Search' and resource 'the web' are specific. The tool name and title reinforce this. Among sibling tools, only 'venice_web_scrape' is similar, but that scrapes a specific page, while this is a general search, so distinction is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions auth methods ('Supports x402 wallet auth (no Venice account needed) and API key'), indicating when the tool can be used. However, no explicit when-not-to-use or alternatives are provided. The context is clear for a search tool, but it could mention that for scraping a single page, 'venice_web_scrape' is appropriate.
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 that the tool is a read-only fetch (step-1 requirements) and notes that steps 2 and 3 require a wallet and happen externally. However, it does not mention authentication requirements, rate limits, or whether the fetch is safe. This leaves some behavioral ambiguity.
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 two sentences long, no redundant words, and front-loads the purpose. Every sentence provides essential information without wasted verbiage.
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?
With 2 parameters and no output schema, the description is semi-complete. It mentions the type of data returned but not its structure or format. The optional parameter amount_usd is not explained, leaving potential ambiguity about its effect. Given the simplicity of the tool, the gaps are moderate.
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, but it does not explain the parameters individually. It mentions 'min amount' but does not map it to the parameter amount_usd, nor does it describe wallet_address beyond the schema. The description adds minimal value over the schema alone.
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 fetches step-1 top-up requirements and lists specific items (network, USDC token address, receiver wallet, min amount). It distinguishes from steps 2 and 3 which happen outside the MCP server. The verb 'fetch' and resource 'top-up requirements' are specific 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by stating it is step-1 and that subsequent steps occur outside, but it does not explicitly compare with sibling tools like venice_x402_balance or venice_x402_transactions. Nonetheless, it provides clear context for when to use this tool in a multi-step process.
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?
Without annotations, the description carries the full burden. It discloses two key behavioral traits: the authentication split (API key for lookup, x402 for chat) and content policy ('NSFW prompts allowed where the model permits'). This adds value beyond the schema, though it omits details like rate limits or data handling.
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 two sentences plus a note, front-loaded with the core purpose. Every sentence adds value without redundancy, making it highly concise and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters and no output schema or annotations, the description is incomplete. It does not explain the return format or message structure, and lacks guidance on constructing inputs. The auth context is useful, but overall completeness is insufficient.
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 implicitly covers character_slug via 'by slug' but provides no explanation of model, messages, max_tokens, or temperature. The description fails to add meaningful parameter semantics 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's purpose: 'Chat with a Venice character by slug.' It specifies the resource (character) and action (chat), differentiating it from sibling tools like venice_chat (generic chat) and venice_list_characters (list only).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context on when to use: for character-specific chats. It notes the API-key requirement for character lookup and x402 support for chat completion, guiding users with different authentication methods. However, it does not explicitly exclude scenarios or mention alternatives beyond the auth note.
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?
No annotations provided, so description carries full burden. Discloses it is queue-based, returns queue_id, supports NSFW and auth methods, and suggests polling with venice_music_status. Lacks details on rate limits or destructive behavior but is otherwise transparent.
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?
Three sentences with clear front-loading: purpose, models, additional context. No fluff, every sentence adds value.
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 5 parameters, no output schema, and no annotations, the description covers purpose, models, auth, return type, and polling. Lacks explanation of optional parameters and error handling, but is generally complete for a queue-based tool.
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 low (20% - only model has description). Description lists models and mentions return format but does not explain lyrics, instrumental, or duration_seconds parameters. Adds value but insufficient to compensate for missing schema descriptions.
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 'Queue music generation' and lists available models, making the verb and resource explicit. Distinguishes from siblings like venice_music_status and venice_music_complete by specifying it is for queuing generation.
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?
Implies usage for generating music but does not explicitly state when to use it vs alternatives like venice_music_complete. Provides some context (NSFW allowed, auth methods) but no 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.
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 that the tool is read-only (list transactions), requires specific auth (SIWX), and enforces wallet-matching. It does not mention pagination or rate limits, but for a simple list tool this is adequate.
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 three concise sentences, front-loaded with the action. No unnecessary words, each sentence adds value: what it does, auth constraint, wallet matching constraint.
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?
Given the tool's simplicity, the description covers purpose and auth. However, it is missing details about the 'limit' parameter (e.g., defaults, effect) and does not describe the output format. It is adequate but leaves gaps.
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 mentions 'wallet' in the context of authentication but does not explain the 'limit' parameter or its effect. The agent gains no additional meaning beyond the schema's type and regex pattern.
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 'List' and the resource 'recent x402 top-up + debit transactions for a wallet'. It distinguishes from sibling tools like venice_x402_balance and venice_x402_top_up_info by focusing on transaction history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states the authentication requirement: 'SIWX-ONLY: rejects API key, requires X-Sign-In-With-X (VENICE_SIWX_TOKEN)'. It also gives a constraint on wallet matching. However, it does not explicitly mention alternatives if SIWX is not available.
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 provided, the description carries full weight for behavioral transparency. It discloses that the operation is read-only and requires no authentication, which is sufficient for a listing tool. However, it does not mention potential rate limits or response structure.
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: two sentences with no redundant words. It front-loads the purpose and adds a key detail (no auth). 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?
Given the tool's simplicity (single optional parameter, no output schema, no annotations), the description is largely complete. It tells the agent what the tool does and a critical usage condition. However, it could hint at the output format (e.g., list of objects with names, capabilities, prices).
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 add meaning to the sole parameter 'type'. The description does not explain the parameter, leaving the agent to infer from the enum values. It could have stated that filtering by type is possible, but it fails to do so.
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 lists live models, including capabilities and prices. The verb 'list' and resource 'model catalog' are specific, and this purpose distinguishes it from sibling tools like venice_chat or venice_image_generate, which perform different operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions that no authentication is required, which is a direct usage guideline. It implies this tool is for exploring available models before using other tools, though it does not explicitly state when to use it compared to alternatives or when not to use it.
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?
Discloses that no authentication is required, a key behavioral trait since no annotations are provided. The description implies read-only cost estimation, which is sufficient for a quote tool. Could expand on idempotency or rate limits.
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 concise sentences with front-loaded purpose. Every word adds value, no redundancy or filler.
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 (3 scalar params, no output schema), the description provides essential context: purpose, timing, auth. Missing return format details, but overall complete enough for safe invocation.
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 67% (model and character_count have descriptions, duration_seconds lacks one). The description adds no parameter details beyond the schema, so baseline score of 3 applies. Duration_seconds parameter remains undocumented in description.
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 retrieves a price quote before queuing music generation. It uses specific verb ('Get a price quote') and resource ('music generation BEFORE queuing'), distinguishing it from generation tools and other quote tools like venice_video_quote.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'BEFORE queuing' and 'Useful for budgeting,' providing clear context for when to use the tool. However, it does not mention alternatives or when not to use it, which would improve guidance.
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 discloses that no authentication is needed and implies it is a read-only operation. However, it doesn't detail edge cases like invalid parameters or quote accuracy.
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 at one sentence, covering purpose and key usage guidance. It is front-loaded and efficient, though slightly more structure could improve scannability.
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 simple tool with only 2 parameters and no output schema, the description covers core aspects: what it does, when to use it, and auth requirement. It doesn't mention the output format, which is a minor gap.
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 100%, so the schema already describes parameters with examples. The description adds no additional meaning beyond what the schema provides, meeting the baseline of 3.
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 it gets a price quote for video generation before queuing. The verb 'Get' and resource 'price quote for a video generation' are specific and distinguishable from siblings like venice_video_generate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'BEFORE queuing' and 'No authentication required,' providing clear context for when to use this tool versus alternatives like venice_video_generate.
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?
No annotations are provided, so the description carries full burden. It discloses that 'list' returns a static catalog (not a dynamic endpoint), and 'create' uses multipart upload to a specific endpoint. It mentions auth methods but does not discuss side effects, rate limits, or destruction behavior.
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 four sentences, each efficiently conveying essential information. The first sentence sets the purpose, followed by clear explanations of each action. No fluff or 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's simplicity (3 parameters, no output schema, no annotations), the description covers the main actions and protocol well. It lacks response format details or error handling, but the core functionality is adequately described.
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?
Schema coverage is 100% with parameter descriptions. The description adds context: model is required for create, sample_url is for create, and that create uses 'multipart upload to /v1/audio/voices'. This goes beyond the schema's basic descriptions, justifying a score above baseline.
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 explicitly states it 'Manage TTS voices' with two distinct actions: 'list' returns the static catalog of built-in voices grouped by TTS model, and 'create' clones a voice from a sample audio URL. This clearly differentiates it from sibling tools like venice_tts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly indicates when to use each action: 'list' for viewing built-in voices, 'create' for cloning. It also mentions auth methods (x402, API key). However, it does not explicitly state when not to use this tool or compare it to alternatives like venice_tts.
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 provided, the description carries the full burden. It discloses the authentication method and a critical behavioral constraint (wallet must match). It could mention that the operation is read-only, but the purpose implies it. Overall good transparency.
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 two sentences, front-loaded with purpose, followed by critical auth details. No redundant or unnecessary words. Excellent structure.
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 and no output schema, the description covers purpose, auth, and constraint. It could mention the return format (e.g., balance amount) to be fully complete, but it is still sufficient for an AI agent.
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?
Schema coverage is 0%, so the description must compensate. It adds meaning by stating the parameter is a 'wallet address' and that 'the wallet in the path must match the SIWX-authenticated wallet'. This adds constraint beyond the regex pattern in 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 tool's purpose: 'Check the prepaid x402 credit balance for a wallet address.' The verb 'check' and resource 'x402 credit balance' are specific, and it distinguishes from siblings like venice_x402_top_up_info and venice_x402_transactions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly specifies authentication requirements: 'SIWX-ONLY' and requires X-Sign-In-With-X token. It also states the constraint that the wallet must match the authenticated wallet. This provides clear context for when to use the tool, though no explicit comparison to alternatives is given.
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?
No annotations provided, but description adds the key behavioral detail that authentication is not needed, signaling it's a low-risk, non-destructive operation. Sufficient for this 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?
Single sentence conveying purpose and key constraint (no auth). No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter listing tool, the description fully covers what it does and for which sibling tool, making it 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?
Input schema has zero parameters; schema coverage is 100% trivially. Description adds no param info, but none is needed. Baseline 4 applies.
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 verb 'list', resource 'image style presets', and context 'available for venice_image_generate', distinguishing from numerous sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Indicates 'No authentication required', implying it's a safe, public listing to fetch style options before generating images. Lacks explicit when-not-to-use or alternatives, but usage is self-evident.
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?
The description discloses key behaviors: return format (model, queue_id), uncensored nature, auth methods, and duration enum. With no annotations, it carries the full burden and does so well, though it omits latency, quotas, or queuing specifics.
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 front-loaded with purpose, efficiently uses each sentence to add value (model list, auth, return, duration note), and avoids redundancy with the schema.
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 18 parameters, high schema coverage, and no output schema, the description provides substantial context on purpose and parameters. However, it lacks completeness on error handling, queue behavior, and status polling details, which would enhance practical use.
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?
With 83% schema coverage, the description compensates by adding concrete examples (model IDs like 'veo3.1-fast-text-to-video'), usage syntax ('@Element1'), and format details ('URL or data URL', '4s/6s/8s') that the schema lacks.
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 'Queue a video generation' with a specific verb and resource. It lists supported models and explicitly distinguishes itself from sibling 'venice_video_status' by mentioning polling with that tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use this tool (asynchronous generation) and implicitly contrasts with status polling. However, it does not explicitly compare to sibling 'venice_video_complete' or provide guidelines on model selection.
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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