Yeelight Metadata MCP Server

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

With no annotations, the description carries full burden and does disclose meaningful behavior: dryRun defaults to true and produces only a plan, and real execution enforces schema validation, candidate-status checks, and side-effect confirmation. This reveals the safety gates without over-claiming; it stops short of detailing what a real execution mutates.

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?

Two tight clauses with the purpose front-loaded followed by the dry-run/validation behavior. Every phrase carries weight; the only minor cost is the dual 'validate or execute' framing.

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?

An output schema exists, so return values need not be described, and the description covers the key execution semantics (dry-run default, validation gates). For a task/action dispatcher it is reasonably complete, though it could note the prerequisite discovery step.

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 nested request/options/payload fields are already documented. The description reinforces options.dryRun by explaining it returns only a plan, but adds no syntax or format detail beyond the schema, so the 3 baseline 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 (校验/执行) and resource (元数据管理任务), so an agent knows this is the execution dispatcher among the list/get siblings. It does not explicitly name which sibling to consult first, but the execute-vs-list distinction is clear enough.

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 the intended flow – dry-run by default, real execution only after schema/candidate/side-effect checks – which is useful when-to-use context. However, it never states exclusions or points to the discovery siblings (list_tasks/list_actions) that an agent must clearly call first to obtain valid task/action IDs.

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?

No annotations are provided, so the description carries the full disclosure burden. It does enumerate what is returned (schema, global Header, context, payload, options hints), which is genuinely useful, but it never states that this is a read-only lookup with no side effects or whether the lookup can fail for unknown task/action pairs.

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 or repetition. It packs the return contents into one clause efficiently, though the enumeration of five return elements is dense.

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?

An output schema exists, so return-value explanation is not strictly required, and the description still outlines the return shape. Combined with fully documented parameters, an agent has enough to invoke it, with only the when-to-use dimension left implicit.

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% and the schema already gives concrete examples for both task (family_space.manage_room) and action (create, list, delete, get_house_detail). The description adds no format or constraint details beyond what the schema supplies, so the baseline 3 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 (返回) and a well-defined resource (the param schema, global Header, local context, payload and options for a given task/action). It is clearly distinguishable in kind from siblings like execute_task or list_actions, but it never explicitly names or contrasts with them.

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?

There is no statement of when to call this versus execute_task or list_actions, nor any prerequisites. The use case (look up a schema before executing) must be inferred entirely from the purpose, so guidance is effectively absent.

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?

No annotations are provided, so the description carries the full behavioral burden, and it discloses nothing beyond the schema. It does not say the operation is read-only, how results are ordered, how pagination interacts with filters, or what a filtered-out status means.

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 compact sentence front-loading the verb and resource with no filler. It is efficient, though the brevity comes partly from omitting information rather than from tight editing.

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?

An output schema exists, so return values need no explanation, and the filters are named. However, with zero annotations and no behavioral detail about a paginated list tool, the definition is only minimally sufficient for correct invocation.

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

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

Schema description coverage is 100%, with each of the seven parameters documented including examples, so the baseline is 3. The description names five of the filter parameters but adds no syntax or semantics beyond what the schema already provides, and omits limit/cursor entirely.

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 (列出/筛选) and resource (action) and enumerates the filterable dimensions, so the agent knows exactly what the tool returns. It does not, however, differentiate itself from siblings like list_tasks, list_groups, or get_action_schema beyond the noun 'action'.

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?

There is no statement of when to use this versus get_action_schema or execute_task, and no exclusions or prerequisites. The mention of filterable fields implies usage but leaves the agent to infer the routing decision entirely.

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?

No annotations are provided, so the description carries the behavioral burden. It discloses that results are paginated (分页返回), which is useful, but says nothing about permission requirements, error behavior, or the nature of the summary payload beyond what the schema and output schema already provide.

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

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

A single sentence that front-loads the resource and scope, then states the tool's purpose in the workflow. Nothing is redundant or padded.

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 an output schema present, the return values need not be described, and both parameters are fully covered by the schema. The one remaining gap is that it does not explain the relationship to the other sibling tools (list_actions, execute_task), but for a simple two-parameter listing tool it is close to complete.

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% and both parameters (limit, cursor) are documented in the schema, including that cursor comes from nextCursor. The description adds no parameter-level meaning, so the baseline of 3 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?

The description names a specific verb and resource (分页返回 Metadata 任务分组摘要) and relates itself to the sibling tool list_tasks, so an agent can distinguish it from list_tasks/list_actions without opening the schema. It stops short of fully positioning itself against all siblings, so it is clear but not maximally differentiated.

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?

It explicitly states the role: use it to pick the group argument for list_tasks, which is genuine when-to-use guidance tied to a named alternative. There is no explicit when-not-to-use or prerequisite statement, so it falls just below the top tier.

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?

No annotations are present, so the description carries the full behavioral burden. It does disclose mode-dependent behavior (single detail vs. search vs. paginated summary, and that query spans actions too), which is genuinely useful, but says nothing about read-only nature, result volume, or limits beyond what the schema already states.

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 compact sentence with three clearly delimited clauses, front-loading the browse/search/view framing before the branch conditions. No filler, though the three modes run together without separators.

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?

An output schema exists, so return-value detail is not needed here, and the branching logic across the five optional parameters is fully explained. Complete enough to invoke correctly; only cross-tool routing guidance is absent.

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 each of the five parameters is already documented with examples in the schema. The description reinforces the mode semantics of task/query/group but adds no format, constraint, or interaction detail beyond what the schema provides.

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 gives a concrete verb set (浏览/搜索/查看) bound to a specific resource (Metadata 任务) and enumerates three operating modes keyed to which parameter is supplied. It is distinguishable from list_actions and list_groups by resource, but it never names or contrasts those siblings explicitly.

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?

It gives explicit conditional guidance: pass task for a single-task detail view, pass query to search tasks and actions, pass neither to get group-paginated summaries. That covers when to use each mode well, but offers no guidance on when to prefer a different tool (e.g. list_actions or execute_task) instead.

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