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

With no annotations, the description carries the behavioral burden. It reveals use of a real chart engine, the inclusion of citable evidence entries, and a non-obvious calendar trap. It does not discuss side effects or permissions, but for a chart-casting tool the disclosed output scope and constraints are substantial.

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 compact and well-structured: output first, usage condition second, calendar warning third. Every sentence adds distinct value with no 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?

This is an 11-parameter tool with zero parameter-level schema descriptions. Although an output schema exists, so return values need not be documented, the description still leaves the caller to guess multiple input details such as allowed detail values, calendar encoding, time-zone handling, and leap-month semantics. The tool is easy to select but not fully specified 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 0%, and the description only explicitly addresses the calendar distinction. It does not clarify the meaning of year, month, day, hour, gender, detail, time_zone, current_year, or is_leap_month, nor the valid values for detail and calendar. Some meaning can be inferred from the tool's domain, but the description does not compensate for the missing 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 a specific action and resource: it 'simultaneously produces both BaZi and Ziwei charts' and enumerates the returned data. It also clearly distinguishes itself from liuyao_qimen_fusion by scope, so an agent can tell them apart.

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 an explicit condition: use only for long-term fate or stage fortune, and for specific matters use liuyao_qimen_fusion instead. It also supplies an important invocation rule: the caller must explicitly specify solar or lunar calendar and cannot default to solar.

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 of behavioral disclosure, and it delivers meaningful context: the image must be generated from the structure (“图片由结构生成”), with an explicit prohibition on AI redraw or manual assembly (“不得用 AI 生图重绘或手工拼爻线”), and the tool re-casts the hexagram itself. It does not cover delivery format of the PNG or failure modes, but the disclosed constraints are genuinely informative.

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 dense sentences front-load the core function and enumeration of diagram contents, then cover generation constraint, sibling relationship, re-casting behavior, and the text fallback. Every clause earns its place; there is no filler or repetition of the schema.

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 tool with 10 parameters, no output schema, and no annotations, the description covers the core behavior and the text fallback well, but leaves gaps that matter for invocation: how the PNG is returned (path/URL/data URI), what valid values method/number accept, and the meaning of category. The cross-reference to liuyao_qimen_fusion partially fills this, but the definition is not self-sufficient for a fresh agent.

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 should compensate, but it only cross-references the sibling (“参数与 liuyao_qimen_fusion 一致”) rather than explaining the 10 parameters. The date/time fields are self-evident, but the required domain-specific parameters — method, numbers, category — get no value guidance and the schema offers no enums. The cross-reference is useful partial mitigation but the description cannot stand alone.

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 a specific verb and resource: “直接画出固定坐标的 PNG 卦图” (directly draw a fixed-coordinate PNG hexagram diagram), and enumerates the exact contents (本卦、变卦、六亲、六神、世应、伏神、动爻). It also differentiates from the sibling liuyao_qimen_fusion by noting the parameters match but the output is the diagram plus text, leaving no ambiguity about what this tool produces.

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 frames this as the image companion to liuyao_qimen_fusion (“参数与 liuyao_qimen_fusion 一致，会重新起同一卦”), which tells the agent this tool re-casts the same hexagram rather than consuming a prior result, and it gives a concrete fallback condition (“宿主不能显示图片时就只用逐爻文字”). It lacks an explicit 'use X when you need interpretation, use this when you need an image' contrast, so the choice rule is implied 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?

With no annotations provided, the description carries the full burden. It meaningfully discloses that the tool returns an entry point (入口), not the actual consultation output, and explicitly states the server does not produce the Teacher Master's tone or consultation flow. This prevents the agent from assuming the tool performs the full consultation. It could specify what the entrance looks like, but the output schema likely covers the return value.

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 purpose is front-loaded in the opening clause, but the single sentence is dense and poetic ('用户想要的不是一张盘，而是有人把盘讲明白'), and the enumeration of five usage conditions (断成败、看时间、点条件、用核对式问句定盘、按需要细讲) makes it longer than strictly necessary. The phrasing is evocative but somewhat verbose.

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 zero-parameter entry-point tool with an output schema, the burden is low. The description covers the use case, what it returns (the official consultation entrance), and what it does not do (generate the consultation itself). Nothing essential is missing for an agent to decide to invoke it.

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 has zero parameters, which sets the baseline at 4 per the rubric. With an empty schema and no parameters to document, there is nothing for the description to add 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 clearly states the tool's purpose: when the user wants a chart explained (成败, timing, conditions, verification questions, detailed explanation) rather than just a chart, return the official entry to the Teacher Master's consultation. It distinguishes itself from the server's chart-only function ('本服务器本身只排盘'), implicitly separating it from the chart-producing siblings, though it doesn't name them 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?

The description gives explicit triggering conditions: '用户想要的不是一张盘，而是有人把盘讲明白' and enumerates the specific scenarios (断成败、看时间、点条件、用核对式问句定盘、按需要细讲). It implies the alternative (chart tools) by stating the server only produces charts, but doesn't name siblings or say 'use X instead'.

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 discloses the real-engine nature (actual computation, not templates), the strict number-entry rule, the precondition of a clarified matter, and the no-repeat-casting guidance. It does not cover auth needs or rate limits, but for a divination tool the disclosed casting rules are substantial.

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 dense paragraph where each sentence carries distinct information: core purpose, return components, method selection rules, and a usage warning. Front-loaded with the purpose. Efficient with no filler, though the compactness slightly reduces scannability.

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 required, though the description does list return components anyway. For an 11-parameter tool with 0% schema coverage, the description is incomplete — the date/time and detail/category parameters are entirely unaddressed, leaving an agent guessing at their format and semantics.

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% — no parameter descriptions exist in the schema. The description only partially explains 3 of 11 parameters (method, numbers, question), leaving year/month/day/hour/minute/time_zone/detail/category undocumented in both the schema and the description. For a tool with zero schema coverage, the description must compensate far more than it does.

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 a specific action: using a real engine to simultaneously cast Liu Yao and Qi Men charts and perform dual-method joint consultation. It clearly differentiates from siblings — resolve_pillars (pillar resolution), bazi_ziwei_chart (Bazi/Zi Wei), hexagram_diagram (single diagram), laoshifu_consultation (human consultation) — by naming the dual-method fusion resource and its 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?

Clear context for choosing method=time (use confirmed current moment) versus method=numbers (three positive integers from first thought), plus a precondition (matter must be clarified first) and a warning against re-casting. However, it does not explicitly contrast with sibling tools or state when not to use this tool.

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 behavioral disclosure burden. It does this well by explaining that pillars repeat, that no unique candidate blocks further reasoning, that zero candidates implies invalid input, and that multiple candidates must be confirmed by the user. This is substantive behavioral context beyond a simple operation statement.

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 compact, front-loaded with the core use case, and every sentence adds value—use case, repeat behavior, failure interpretation, and user-confirmation requirement. There is no wasted text.

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 description covers the core workflow and ambiguous-result handling well, and an output schema exists to describe return values. However, the tool has three required parameters with no schema descriptions and no mention of pillar syntax or year-range semantics, leaving an agent to guess important input details.

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 for missing parameter meaning. It clarifies that pillars refer to four ganzhi and that the tool returns candidates, but it does not explain the format of the pillars string or the semantics/range of start_year and end_year. This is a meaningful gap for correct invocation.

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: reverse-look up candidate Gregorian years matching the user's provided four pillars, and it specifies the exact scenario in which this tool is used. It does not explicitly differentiate from sibling tools, but the described operation is distinctive enough that confusion is unlikely.

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 explicitly says when to use the tool: when the user gives only four pillars and not a birth date. It provides clear context and behavioral expectations, though it does not mention alternatives or an explicit 'do not use when...' condition.

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