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

With no annotations, the description carries the full behavioral burden. It usefully discloses that cloud mode requires SILICONFLOW_API_KEY and that local mode is an optional offline mode. However, it omits other important behavior such as extraction output format, failure conditions, 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.

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

The description is two short clauses and is front-loaded with the core action before mode details. It is concise, though its extreme brevity reflects under-specification rather than optimal restraint.

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 five-parameter tool with no annotations and 0% schema description coverage, the description is incomplete. Output schema exists, so return values need not be explained, but parameter meaning and usage context are still missing.

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 0% for five parameters, so the description must explain them. It loosely maps to asr_mode's cloud/local values but never names or explains share_link, context, asr_mode, or local_model. The compensation is far from sufficient.

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 says '提取文案' (extract text/copy), which gives a verb+object but does not specify that it extracts text from a Douyin share link. It does not distinguish this tool from siblings like recognize_audio_file or parse_douyin_video_info. The mode note helps but remains vague about the exact resource.

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 mentions cloud vs. local mode and the API-key requirement for cloud, but gives no guidance on when to choose this tool over alternatives. No when-to-use or when-not-to-use guidance is provided relative to sibling tools.

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?

With no annotations, the description carries the full behavioral burden. It does disclose one genuinely useful trait — an automatic browser-based fallback when HTTP fails, implying possible latency/side effects — but says nothing about auth requirements, rate limits, or reliability beyond that single clause.

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 compact clauses with no filler, and the fallback behavior is stated crisply. It is efficient, though it errs toward under-specification rather than being over-long.

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?

The output schema covers return values, so that need not be described, and the tool is a single-parameter call. However, with no annotations, no parameter documentation, and three adjacent Douyin sibling tools, the description is too thin to reliably route the agent to the correct tool.

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 0% for the single required share_link parameter, and the description adds no format, example, or accepted-link-shape detail. Only the parameter's self-evident name carries meaning.

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 name promises a download link, but the description only says it parses a Douyin link (解析抖音链接), which is vaguer than the tool's actual name and fails to differentiate from the nearby siblings parse_douyin_video_info and extract_douyin_text. An agent cannot tell which Douyin-parsing tool actually returns a downloadable link.

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 guidance on when to use this tool versus the three sibling Douyin tools, nor any preconditions stated. The only conditional mentioned (HTTP failure fallback) is internal behavior, not a selection criterion for the agent.

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 burden, yet it says nothing about network fetch behavior, failure modes for invalid or expired share links, rate limits, or whether parsing is local vs remote. It only lists outputs, which the output schema already covers.

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 no filler, front-loading the action verb and the field list. It is efficient, though the brevity is partly under-specification rather than discipline.

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 re-explained, but the description leaves the only input parameter undocumented and offers no guidance on the tool's place among three overlapping siblings. For a network-fetch parsing tool this is thin.

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 single required parameter share_link has 0% schema description coverage and is never mentioned in the description. The description enumerates outputs, not the input, so nothing compensates for the undocumented parameter — the agent must guess whether it accepts a full URL, a share code, or plain text.

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 verb '解析' (parse) plus the explicit enumeration of extracted fields (视频 ID、标题、下载地址、解析方式) makes the purpose concrete. However, it never distinguishes itself from the similar siblings extract_douyin_text or get_douyin_download_link, which clearly overlap in scope.

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 tool versus its siblings, nor any precondition about the share link format. An agent seeing four Douyin-related tools gets no routing guidance from this description.

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. It hints at two backends (cloud SiliconFlow vs local Whisper) but never states that cloud mode requires network/API credentials, what audio formats or size limits apply, or how failures are surfaced – all material for an ASR 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?

A single front-loaded sentence with no wasted words. It is efficiently structured, though the brevity is partly under-specification rather than disciplined concision.

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 explained. However, with zero annotations and 0% parameter coverage, the description should compensate by explaining the mode/model choices and any input constraints, and it does not.

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 0% and none of the three parameters are documented in the schema. The description loosely maps to 'asr_mode' (cloud vs local) but never names the parameter or enumerates valid values, and the 'model' parameter (default 'small') is entirely unaddressed.

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 ('识别本地音频' – recognize local audio), which is unambiguous and clearly distinct from the Douyin video siblings. It stops short of explicitly differentiating itself from those siblings, but the resource makes the boundary obvious.

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 mention of 'default SiliconFlow, also can choose local Whisper' describes backend selection, not when to use this tool versus alternatives or prerequisites. There is no guidance on when to prefer local vs cloud mode, or what inputs are acceptable.

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