audiomade
Server Quality Checklist
Latest release: v0.1.1
- Disambiguation4/5
Most tools have clear boundaries, but get_candidate_audio and get_sound_candidates both relate to retrieving playable audio, requiring careful reading to distinguish existing previews from generated candidates. The remaining tools are unambiguous in their roles.
Naming Consistency3/5The verb_noun pattern is mostly consistent, but the nouns mix 'audio' and 'sound' (get_candidate_audio vs. get_sound_candidates), and 'candidate' appears as both singular and plural. This creates minor naming friction.
Tool Count5/5Six tools are well-scoped for the generate-audition-select-install workflow. Each tool maps to a clear step without redundancy or bloat.
Completeness4/5The full generation-to-install lifecycle is covered, including loading existing previews. Minor gaps like a cancellation or status-check tool are absent, but the core workflow is complete enough for agent success.
Average 3.7/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already communicate idempotency and non-destructiveness. The description adds a useful behavioral clarification—recording a selection does not install a file—which helps disambiguate from install_sound_candidate. However, it does not describe side effects, whether the selection is persisted, or what happens on repeated calls, though idempotentHint covers some of this. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with no fluff. The main action is front-loaded, and the clarifying 'does not install a file' earns its place by preventing a common confusion. Every word contributes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 2-parameter tool with no output schema, the description is minimal but leaves critical workflow context missing: where generation_id comes from, how it relates to the user's 1-4 choice, and what the agent should expect after calling this. The sibling tool list hints at the workflow, but the description itself does not provide enough for confident invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does 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 explains that the variant parameter maps to a 1, 2, 3, or 4 user reply, which is helpful. However, it never explains generation_id—its origin, how to obtain it, or its relationship to the candidates being selected. This is a notable gap given the schema provides no semantic help.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Record') and identifies the exact resource: the user's explicit 1, 2, 3, or 4 reply. It also distinguishes itself from installing by adding 'This does not install a file,' which differentiates it from the install_sound_candidate sibling. It does not explicitly name all siblings, but the core purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is used when the user provides a 1-4 selection and explicitly clarifies that it is not an install action. However, it does not state when to use this versus generate_sound_candidates or get_sound_candidates, nor does it describe the expected workflow order. Usage context is implied rather than explicit.
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?
It discloses asynchronous execution, realistic side effects, and the four-candidate count, beyond the sparse false-valued annotations. However, it doesn't state what happens on repeated calls, whether the previous generation is replaced, or any rate-limit/cost externalities, so transparency is incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler; the action is front-loaded and the follow-up instruction is placed at the end. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With seven parameters, no output schema, and annotations that add little guidance, this terse description is not enough for reliable invocation. It captures the workflow but omits parameter meaning, output/result behavior, and side-effect details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description never mentions any parameter, not even required prompt and sound_type. The agent must rely on raw property names, enums, and defaults with no explanatory guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific action ('Start one real asynchronous AudioMade generation') and pins the expected outcome ('exactly four candidates'), making the tool's role clear. It also references the downstream get_sound_candidates call, which distinguishes it from sibling retrieval/selection tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives an explicit workflow: start generation, continue implementation while it renders, then call get_sound_candidates. This tells the agent when to invoke the tool against the main alternative, though it doesn't spell out when not to use it or list other alternatives.
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?
Annotations already indicate the operation is non-read-only, idempotent, and non-destructive, so the description does not need to restate those. It adds that the tool targets specific engines, but it does not disclose installation behavior such as file copying, project structure modifications, or what overwrite means in practice.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single focused sentence with no redundant wording. It is front-loaded with the action and resource, and every phrase adds relevant context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having seven parameters, no output schema, and no parameter documentation, the description provides only the core purpose. It omits what 'install' actually does, how the candidate is identified, what required inputs mean, and what a successful installation entails, making it incomplete for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description explains none of the seven parameters beyond echoing the engine options already present in the schema. generation_id, variant, project_root, asset_name, overwrite, and destination_directory are left entirely to the agent to infer.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the primary action — installing an explicitly selected AudioMade candidate — and specifies the target project types (Unity, Godot, Defold, or generic). This distinguishes it from sibling tools focused on generation, retrieval, or selection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'explicitly selected' implies this tool should be used after select_sound_candidate, but it does not explicitly say when to use this tool versus alternatives or mention prerequisites. The usage context is implied rather than spelled out.
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?
Annotations already mark the tool as readOnly and idempotent. The description adds valuable behavioral context: it loads previews into the picker and explicitly denies generation, selection, or installation behavior. This goes beyond the annotations and helps set expectations about side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with no filler. The primary action is front-loaded, and the exclusion clause is a distinct second sentence. Every word contributes meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one optional parameter and no output schema, the description leaves important gaps: what generation_id means, what happens if it is omitted, and what the return/result of the load looks like. Annotations cover safety but not invocation semantics, so the description is not complete enough for confident correct use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter, generation_id, with no description coverage. The tool description does not mention this parameter at all, leaving the agent to guess what generation_id refers to, why it is optional, or how it affects the operation. With 0% schema coverage, the description needed to compensate and did not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Load') and a clear resource ('existing audio previews') with a destination ('into the picker'). It also explicitly states what the tool does not do ('Does not generate, select or install audio'), which clearly differentiates it from sibling tools like generate_sound_candidates, select_sound_candidate, and install_sound_candidate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool: when loading existing audio previews into the picker. It also states exclusions ('Does not generate, select or install audio') which signals what not to use it for, but it does not explicitly name alternative tools or provide conditional guidance, so it falls just short of a 5.
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 annotations already convey read-only and idempotent behavior. The description adds useful context beyond that: the result contains exactly four real playable candidates, and the agent should present them as a numbered list and wait for the user's reply. This is meaningful behavioral guidance without contradicting the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the action and then gives the key interaction instruction. No words are wasted, and the structure makes the tool's purpose immediately clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main purpose and the return content (four candidates), and annotations handle safety semantics. However, it omits the meaning of wait_seconds, possible error conditions, and what to do if no candidates exist or the generation is invalid. These gaps are noticeable but not critical for a simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden of explaining the parameters. It indirectly implies generation_job_id through 'a started generation,' but it never explains wait_seconds, which has a default, minimum, and maximum but no stated purpose in the description. This leaves a meaningful parameter unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Retrieve four real playable candidates') on a specific resource ('a started generation'). It clearly differentiates from the sibling tools: it does not generate, select, install, or fetch audio capabilities, making the tool's role unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for a started generation' clearly places this tool after generation has begun and before a candidate is chosen. It does not explicitly name alternatives or exclusion conditions, but the context is strong enough that an agent can infer when 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?
Annotations already declare readOnly and idempotent, and the description adds a meaningful behavioral detail: the tool consumes no generation credits. It also clarifies that the tool only describes the workflow and does not execute generate, audition, select, or install operations. This aligns with, and enriches, the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that front-loads the action and names the workflow phases in order. There is no filler or redundant restatement of the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only informational tool, the description covers what the tool does, the workflow it describes, and an important operational constraint (no generation credits). No output schema exists, and no additional context appears necessary for correct selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema documents 100% of them trivially. There is no parameter meaning for the description to add, so the baseline of 4 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Describe') and names a concrete resource: AudioMade's generate, audition, select, and install workflow. It clearly marks itself as an informational/overview tool rather than an actual generation or installation action, distinguishing it from the 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 Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'without using generation credits' implies the tool is useful when an agent wants to understand the workflow without incurring cost. However, it does not explicitly state when to prefer this tool over the workflow-executing siblings or when not to use it, leaving some routing to inference.
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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