netcafe-china

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

Annotations already declare the operation as read-only, idempotent, and non-destructive. The description adds a useful behavioral detail by noting that it uses true solar-term boundaries, which affects chart accuracy, and enumerates output elements. This is beyond the annotation-provided safety profile, making it transparent for expected behavior.

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 sentences, front-loads the main function, and packs relevant details (output components and the solar-term boundary method) without redundancy. Every phrase adds value, making it well-structured and concise.

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 tool has one parameter, complete schema documentation, explicit annotations, and an output schema, the description covers the essential context: input, purpose, and distinctive calculation logic. It does not need to explain return values, as the output schema handles that. The only minor gap is timezone handling, but that is not essential for a straightforward birth datetime input.

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 schema fully documents the only required parameter (datetime) with format YYYY-MM-DDTHH:mm, providing 100% coverage. The description simply refers to 'birth date and hour' without adding new parameter semantics, so the baseline of 3 is appropriate.

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 computes a BaZi (Four Pillars) chart from birth date and hour, listing key output components (four pillars, five-element counts, 纳音, zodiac). This differentiates it from sibling tools like lunar_calendar or huangli, which serve different purposes. The verb '排盘' (chart calculation) is specific and resource-oriented.

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 tool is for generating BaZi charts from birth datetime, giving clear context for when to invoke it. However, it does not explicitly name alternatives or exclusion criteria, so it stops short of providing full when/not guidance. It still qualifies as clear context with no exclusions, meriting a 4.

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 and idempotentHint=true, and the description adds meaningful context: it performs a live fetch from a real China egress, reports specific metrics, and frames the result as a measurement rather than a guess. No contradictions with annotations. It does not mention rate limits or failure behavior, but annotations cover safety.

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 concise sentences, front-loaded with the action verb, and every word earns its place. No redundancy or filler.

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 tool is simple (1 parameter, output schema provided). The description fully explains the tool's purpose, the measurement approach, and the key limitation of alternatives. Return values are already covered by the output schema, so no further detail is needed.

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 the 'url' parameter described as 'Full URL to test, e.g. https://example.com'. The description restates the URL-fetching concept but doesn't add new parameter-level detail or format constraints beyond the schema. Baseline 3 is appropriate.

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 a specific action ('Fetch a URL from a real mainland-China network egress') and the resource/scope ('URL reachability from China'), with measurable outputs (HTTP status, latency, DNS resolution). This distinguishes it from all sibling tools, which are unrelated to network testing.

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 clarifies when to use the tool: to answer 'is my site/API usable from China?' and explicitly notes that a VPS abroad cannot provide this measurement. While it doesn't name a specific alternative tool, it gives strong contextual guidance and an implicit exclusion.

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 indicate a safe read-only, idempotent operation. The description adds specific behavioral detail: it evaluates three categories (public holiday, weekend, workday) and returns the next holiday. This provides useful context beyond the annotations, though it doesn't cover edge cases like historical date range.

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 front-loaded sentence that conveys the complete functionality without any wasted words. It is concise and immediately understandable.

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 tool with a rich output schema and informative annotations, the description fully conveys what the tool does. There are no notable gaps in context for an agent to select and invoke this tool correctly.

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 the only parameter `date` fully documented as YYYY-MM-DD with a default of today. The description adds no extra parameter semantics, so the baseline score of 3 applies because the schema already carries the burden.

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 function: determining whether a date is a Chinese public holiday, weekend, or 调休 make-up workday, plus providing the next holiday. This specific scope distinguishes it from sibling tools like lunar_calendar (lunar dates) and huangli (almanac).

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 usage for holiday queries, but it does not explicitly state when to use this tool versus alternatives or mention any exclusions. Given related sibling tools exist, explicit guidance on when to choose this tool would be beneficial, but the purpose is clear enough to infer usage.

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, and destructiveHint=false, covering the safety profile. The description adds that the date defaults to today, which is useful behavioral context beyond the annotations. It does not detail edge cases such as invalid dates or timezone handling, but the additional context is sufficient.

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 concise sentence that front-loads the core purpose (Chinese almanac for a date) and succinctly lists the key output categories. Every word earns its place; there is no redundant or verbose phrasing.

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 tool is simple with one optional parameter, and an output schema exists, so return fields need not be explained in the description. The description covers default behavior and primary outputs. Some context regarding relationship to sibling tools (e.g., lunar_calendar for lunar dates) could be useful, but the tool is self-contained enough for an agent to use correctly.

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 schema provides 100% coverage of the single 'date' parameter, describing it as YYYY-MM-DD with a default of today. The description repeats this default behavior, adding no further parameter-specific meaning. As schema coverage is high, the baseline of 3 is appropriate.

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 identifies the tool as a Chinese almanac for a given date, listing the specific output categories (宜, 忌, 冲煞, 彭祖百忌). This differentiates it from sibling tools like lunar_calendar (lunar date conversion) and pick_lucky_days (date selection), as it focuses on daily almanac information.

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 usage for checking auspicious and inauspicious activities for a date, and mentions the default behavior when date is omitted. However, it does not explicitly state when to choose this tool over alternatives like pick_lucky_days or lunar_calendar, so guidance is only 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.

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

With no annotations, the description carries the behavioral burden. It discloses that the tool validates multiple ID-card dimensions, which is useful, but it does not describe what the tool returns (e.g., validity boolean, extracted fields, error behavior) or how invalid inputs are handled. This is adequate but not rich.

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, compact sentence with the core purpose front-loaded, followed by a short parameter hint. Every element earns its place and there is no wasted wording.

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 tool has no annotations, no output schema, and no parameter descriptions in the schema, so the description must supply most usage context. It defines the purpose and the primary input, but it does not explain the second parameter, expected output, return format, or error behavior, leaving meaningful gaps for an agent that needs to interpret results.

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%, so the description must compensate. It adds meaning to the 'id' parameter by stating it is the 18-digit ID number, but it leaves the second parameter 'number' completely unexplained and does not clarify whether it is an alias, alternative, or ignored field. The parameter semantics are only partially addressed.

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 uses a specific verb ('校验' / validate) and resource ('中国大陆身份证号', Chinese mainland ID number), then enumerates exact validation dimensions: check digit, birth date, age, gender, and region code. This clearly distinguishes it from the sibling tools, none of which target ID card validation.

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 establishes a clear use case: validating an 18-digit Chinese mainland ID number. There are no direct sibling alternatives for ID validation, so explicit when-not-to-use guidance is not critical, and the context is clear enough for an agent to select this tool for ID-card checks.

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, and destructiveHint=false, so the safety profile is known. The description adds valuable behavioral context by specifying the default date behavior and enumerating the types of information returned (lunar, sexagenary cycle, zodiac, solar terms, holidays, constellations), going beyond 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.

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

The description is a single, compact sentence that front-loads the core purpose ('Chinese lunar calendar for any date') and then enumerates the specific outputs in a list. Every part is informative and there is no unnecessary wording.

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 tool's simplicity (one optional parameter), the presence of an output schema, and comprehensive annotations, the description is complete. It covers the main function, default behavior, and output content, leaving no critical gaps for an agent to select and invoke the tool correctly.

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 schema description covers 100% of the parameter, stating 'YYYY-MM-DD, default today'. The tool description does not add any additional parameter semantics beyond what is already in the schema, so the baseline of 3 is appropriate.

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 provides a Chinese lunar calendar for any date, listing specific output types (农历, 干支纪年, 生肖, 节气, 节日, 星座). It distinguishes itself from siblings by focusing on lunar conversion and calendar-related data, unlike bazi_chart or huangli which likely serve different purposes.

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 gives clear context that this tool is for lunar calendar information for any date, including a default behavior of 'date omitted = today'. It does not explicitly mention alternatives or exclusions, but the purpose is evident enough that an agent would know to select it for lunar calendar queries.

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 burden. The description says it identifies validity, carrier, and formatted forms but doesn't explain what happens with invalid numbers, edge cases, or any formatting behavior. It doesn't contradict annotations because there are none, but it lacks depth on behavior.

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 concise, two sentences, and front-loads the key information. However, it could be slightly more structured, but it's efficient overall.

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 description does not explain return values or formats. The tool is relatively simple, but the description leaves out important details like how carrier is returned, what 'formatted forms' means, and how to handle invalid inputs. This is incomplete for an agent to use it effectively.

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 there are two parameters: 'phone' and 'number'. The description mentions 'phone = 11-digit number' but doesn't clarify the purpose of 'number' versus 'phone', nor whether both are required or how they differ. This is a significant gap, as the description does not compensate for the poor schema documentation.

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 states the tool identifies Chinese mainland phone numbers, carrier, and formatted forms. This clearly distinguishes it from siblings like pinyin_convert or id_card_check.

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 mentions the input is an 11-digit number, giving minimal context on when to use it. It doesn't explicitly state when not to use it or mention alternatives like china_reachability, but given the sibling list, the purpose is fairly specific.

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 safety. The description adds context about accepted event terms but does not disclose output format or dependency on the Chinese almanac beyond the '黄历宜' reference.

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, focused sentence with no redundancy. Front-loaded with the primary function and scoped by month.

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?

A simple tool with 2 params, good annotations, and an output schema. The description covers the purpose and parameter flexibility, though it does not mention behavior for invalid events or the default month (already in schema).

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 schema already describes both parameters (100% coverage). The description enriches semantics by listing concrete examples and stating 'any 黄历宜 term' accepts broader input than the schema's generic 'Event keyword in Chinese'.

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?

Clearly states the action ('Find'), target ('auspicious days'), and context ('in a month for an event'). The list of example events and 'any 黄历宜 term' broaden understanding while distinguishing it from generic calendar 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?

Provides implied usage via specific event types but does not explicitly contrast with sibling tools like 'huangli' or state when not to use. No alternatives are mentioned.

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 of behavioral disclosure. It describes the conversion and styles but does not state whether the operation is read-only, has side effects, or any error behavior. For a transformation tool, safety profile is implicitly safe, but the description does not explicitly disclose it, resulting in a transparency gap.

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 extremely concise—two short sentences that are front-loaded with the core purpose and then clarify the 'text' parameter. Every word earns its place with no fluff or repetition.

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 bidirectional conversion tool with 2 parameters and no output schema, the description adequately conveys the inputs, output styles, and the fact that it returns pinyin. It does not mention edge cases or error conditions, but given the tool's simplicity and the absence of an output schema, it is reasonably 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 coverage is 0%, so the description must compensate. It provides meaning for 'text' ('Chinese text') and hints at style values via the output options ('with or without tones, first letters only, or slug'), but it does not specify exact accepted values or format for the 'style' parameter. Partial compensation, but leaves ambiguity.

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 purpose: 'Convert Chinese text to pinyin' with specific output options (tones, no tones, first letters, slug). This is a specific verb+resource and distinguishes it from sibling tools like bazi_chart or lunar_calendar which serve different functions.

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 when to use the tool (whenever pinyin conversion is needed) and lists output styles, but it does not explicitly state when not to use it or mention alternatives. Since no sibling tool overlaps with pinyin conversion, the lack of exclusion is acceptable, but explicit usage guidance is missing.

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 provided, the description carries the full burden. It discloses the probe originates from a real China Mobile backbone node (not overseas inference), provides billing transparency ('self-validation failure not charged'), and indicates the output is a PDF report. This adds meaningful behavioral context beyond the minimal schema. However, it does not mention potential side effects, authorization needs, or concurrency limits, but for a read-only reporting tool this is adequate.

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 concise sentence that packs all essential information: what it does, how it works (source), parameter format, limit, and billing caveat. No wasted words, front-loaded with the main purpose, and perfectly structured for quick comprehension.

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 tool's moderate complexity (2 params, no output schema), the description covers the key aspects: purpose, input format, limits, test origin, output type, and billing condition. It lacks details on error handling or return format specifics, but since output schema is absent, mentioning 'PDF report' suffices. The description is sufficiently complete for an agent to invoke correctly.

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%, so the description must compensate. It explains the 'urls' parameter can be an array or comma-separated list and is limited to 20, but it does not mention the 'url' parameter at all. The description clarifies one parameter meaningfully but leaves the other undocumented, providing partial compensation.

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 checks reachability of a batch of URLs from mainland China and generates a PDF report with per-URL conclusions, latency, HTTP status, and DNS-resolved IPs. It uses a specific verb ('reachability check') and resource ('batch of URLs') and distinguishes itself from the sibling 'china_reachability' by detailing the report format and testing source (China Mobile backbone).

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 usage for checking mainland China accessibility, but does not explicitly say when to use this tool versus alternatives. It mentions input limits (max 20 URLs) and pricing conditions, but lacks explicit exclusion statements or references to sibling tools. The context is clear but not directive enough for an agent to choose it over similar 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?

Annotations already cover non-destructive, read-only, idempotent behavior. Description adds valuable context: it is deterministic, calls no model, costs nothing, and never runs out of quota, plus clarifies it returns example calls and recipes. This exceeds the structured hints without contradicting them.

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?

Four sentences pack purpose, features, behavioral guarantees, and usage guidance with no redundancy. Front-loaded with main action, then supporting details.

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 single-parameter meta-tool with output schema present, the description explains what it returns, when to use it, and behavioral guarantees. Nothing major is 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 covers 100% of parameter info, with a clear description and examples for 'task'. Description adds no additional parameter semantics; baseline of 3 is appropriate.

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 identifies the tool as a meta-tool that maps plain-language tasks to server tools, with ready-to-run examples and multi-step recipes. This sharply distinguishes it from sibling domain-specific tools like bazi_chart or phone_info.

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 instructs to call this FIRST when unsure of server offerings, and frames itself as an alternative to reading the whole catalogue and guessing. Provides clear context for when this tool is appropriate.

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