max4.live
Server Details
Natural-language search over 8,900+ Max for Live devices for Ableton Live. Fuzzy full-text plus type, license, popularity and date filters.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.1/5 across 3 of 3 tools scored.
Each tool has a distinct purpose: searching, retrieving details, and listing filter options. No overlap between them.
All tool names follow the consistent verb_noun snake_case pattern (get_device, list_filters, search_devices).
With 3 tools covering search, detail retrieval, and filter enumeration, the count is appropriate for the scope of browsing a device database.
The tool surface is complete for its intended purpose: search with filters, get details by ID, and discover available filter values. No obvious gaps.
Available Tools
3 toolsget_deviceAInspect
Get full details for one device by its numeric id (from search_devices results).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Device id. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description mentions it retrieves details but doesn't disclose behavioral traits like permissions or side effects. Adequate for a simple read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no wasted words; efficiently conveys purpose and source.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single parameter and no output schema, description covers what the tool does and where the input comes from; could mention output structure but not required.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers the parameter with full description; description adds context that the id comes from search_devices results, enhancing meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Get', resource 'full details for one device', and specifies the id source from search_devices results, distinguishing it from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly indicates to use after search_devices to retrieve full details, but no explicit when-not-to-use or alternatives beyond siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_filtersAInspect
List the valid values for the type, license and sort filters of search_devices.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states that it 'list the valid values,' but with no annotations provided, it fails to disclose any behavioral traits such as return format, pagination, authorization requirements, or side effects. For a listing tool, additional context (e.g., whether it requires network access or is fast) would be helpful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that directly states the tool's function without any extraneous words. It is front-loaded and efficient, every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (no parameters, no output schema), the description is somewhat complete but lacks details on the output format or examples. It could be more helpful by mentioning the structure of the returned values (e.g., lists of strings).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters and 100% schema description coverage, the baseline is 4. The description adds no parameter information because none exist, but this is acceptable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'List the valid values for the type, license and sort filters of search_devices.' It specifies the verb (List) and the resource (valid filter values), and it distinguishes itself from sibling tools (get_device, search_devices) by focusing on filter metadata rather than device data or search execution.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that this tool should be used to obtain filter values before calling search_devices, but it does not explicitly state when to use it or provide alternatives. It lacks guidance on prerequisites or when not to use it, leaving room for ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_devicesAInspect
Search ~8,900 Max for Live devices for Ableton Live. Fuzzy full-text match (title/author/description, identical to max4.live) plus filters. Compose for natural language, e.g. "popular free MIDI devices from the last 2 weeks" -> type=[MIDI Effect,MIDI Generator,MIDI Transformation], license=[free], sort=downloads, added_after=.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Default relevance (Fuse ranking with a query, else newest). | |
| type | No | Device types to include. | |
| limit | No | Max results (default 20). | |
| query | No | Free-text fuzzy search (name, author, keyword). Omit to browse by filters only. | |
| license | No | License buckets. free=freeware, commercial=paid, cc=any Creative Commons. For 'free to use' pass [free, cc]. | |
| added_after | No | ISO date (YYYY-MM-DD). Only devices added on/after this date. | |
| min_downloads | No | Minimum download count. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses fuzzy full-text matching (identical to max4.live) and filter behavior. Read-only nature is implied but not explicitly stated. Lacks details on response format or error handling, but is informative for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences: first states purpose and scope, second explains matching, third gives a rich example. No redundant words, front-loaded with the most critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 optional parameters and no output schema, the description covers search scope, matching mechanism, filters, and usage. However, it omits any description of the response format or fields, which would help an agent understand what is returned. Adequate but with a notable gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all 7 parameters described), so baseline is 3. The description adds value by providing a concrete example translating natural language into parameters (e.g., 'free to use' -> license=[free, cc]), and hints at implicit filter composition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Search' and resource 'Max for Live devices for Ableton Live', with scope (~8,900 devices). It distinguishes from siblings 'get_device' (single device) and 'list_filters' (filter options) by focusing on search and browse.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a clear usage example ('Compose for natural language') and translates it into parameter values. Implicitly guides when to use this vs. sibling tools (search vs. single device or filter listing), but lacks explicit when-not or alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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