max4.live

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds only that the lookup is by numeric id and returns 'full details' — no pagination, error, or auth context. Adequate but thin against an already-complete annotation set.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler; the verb, resource, scope, and id provenance all land immediately.

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?

For a simple single-parameter read tool with rich annotations and no output schema, this covers what an agent needs to invoke it. 'Full details' is left vague, but that is minor for a lookup tool whose return shape is not schema-documented anyway.

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?

One parameter with 100% schema description coverage, so the schema already documents 'id' and its type. The description adds the useful detail that the id is numeric and originates from search_devices results, but nothing about format, validity, or failure behavior. Baseline 3 for full schema coverage.

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?

States a specific verb (Get), resource (device), scope (one, by numeric id), and the source of the id. It implicitly distinguishes itself from search_devices by retrieving a single known device, though it never explicitly contrasts the two.

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 parenthetical '(from search_devices results)' tells the agent this is a follow-up call after search_devices, which is useful routing context. It stops short of an explicit when-to-use/when-not statement or any exclusion, but the intended workflow is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered structurally. The description adds which filters are enumerated but says nothing about the return format or whether the value set is static, which is minor for a zero-parameter lookup.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single tight sentence with no filler, naming the filters and the target tool up front. Nothing could be removed without losing 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?

No output schema exists, so the description could ideally sketch the shape of the returned values (e.g., a map of filter name to allowed values). Otherwise it is complete for a trivial no-arg enumerator whose annotations fully cover its behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so the schema imposes no semantic burden and there is nothing for the description to clarify. Baseline 4 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (List) and the exact resource (valid values for the type, license, and sort filters), and names the sibling tool whose filters it describes. An agent can distinguish it from get_device and search_devices, though it does not explicitly say it exists to serve search_devices calls.

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 reference to search_devices implies the natural workflow (discover valid filter values before filtering), but there is no explicit when-to-use or when-not-to-use statement and no alternative is named. Usage is inferable rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/idempotent/openWorld=false, so safety is covered. The description adds real behavioral context beyond that: dataset size (~8,900), fuzzy matching over title/author/description, and parity with max4.live, plus default-sort fallback behavior. It does not discuss pagination or result-shape limits beyond the schema's limit field.

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?

Front-loaded with purpose, then matching semantics, then a single high-value composition example. The example sentence is long but earns its place by showing cross-parameter reasoning; only minor trimming is possible.

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?

With no output schema, the agent would benefit from knowing the return shape (fields per device, whether pagination exists), which is not stated. Everything else needed to call it correctly — filters, defaults, sorting, empty-query behavior — is present, and annotations carry the safety profile.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3, but the description adds compositional meaning the schema does not: a worked example translating 'popular free MIDI devices from the last 2 weeks' into type=[MIDI Effect,MIDI Generator,MIDI Transformation], license=[free], sort=downloads, added_after=<date>. That teaches multi-parameter interaction, not just individual fields.

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?

Specific verb+resource+scale: 'Search ~8,900 Max for Live devices for Ableton Live', with the matching strategy (fuzzy full-text over title/author/description) stated up front. An agent can distinguish it from get_device (single-device lookup) and list_filters (facet enumeration) without opening a schema.

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 tells the agent when to omit query ('Omit to browse by filters only') and gives a concrete natural-language composition example mapping intent to type/license/sort/added_after. It does not explicitly name when to prefer get_device or list_filters, so it stops short of full when/when-not routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.