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

With no annotations, the description carries the full burden and does disclose the internal pipeline (technical planning, requirement alignment verification, document rendering), which is genuine context beyond structured fields. It is silent, however, on side effects an agent would care about: whether files are written to output_dir, overwriting behavior, or failure modes.

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 sentences, front-loaded with the key claim ('sole entry point'), with no filler. Slightly terse given the gaps, but nothing is wasted.

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, and the entry-point role is conveyed. Still incomplete: output_dir semantics and the file-writing side effect are unaddressed, and there is no annotation coverage to fall back on.

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 session_id as coming from a completed requirements document, adding real meaning, but says nothing about output_dir (the default-empty optional parameter), leaving half the parameters undocumented.

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 the resource and role precisely: '架構書唯一入口' (the sole entry point for architecture documents) and that it renders an architecture document. This distinguishes it from generate_requirements and the other siblings, though it never uses an explicit verb like 'generate' for the resource itself.

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?

Gives a clear prerequisite: use the session_id of a completed requirements document (已完成需求書的 session_id), which implicitly routes the agent through generate_requirements first. No explicit when-not or named alternatives, but the usage condition is unambiguous.

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 burden and does disclose real behavior: the server (not the agent) generates and persists Q1..Qn, sessions survive interruption and day boundaries, and generation, validation, state transitions and document rendering are a closed process the caller cannot intervene in. It omits permissions, error behavior, and limits, which keeps it below 5.

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 short sentences with no filler, front-loaded with the tool's identity before the input modes. The semicolon-heavy packing is dense but every clause carries information, so nothing is wasted.

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 fully covers the session lifecycle that is this tool's core complexity. What is missing is any account of the profile and output_dir parameters, which an agent must still set 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 for all five parameters, and it only covers three: q0, answer, and session_id, including how they combine across turns. The enum parameter profile and output_dir are never explained anywhere, leaving a real gap.

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 resource and role: the single entry point (唯一入口) for requirement documents, with the server generating and persisting Q1..Qn. This is far more than a restatement of the name and implies a pipeline-entry role, though it never explicitly contrasts itself with generate_architecture or generate_skill.

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 lays out three concrete invocation modes: new work supplies q0, continuation supplies session_id plus answer, and session_id alone resumes or queries an interrupted session. That is clear when-to-use guidance, but it names no alternatives or conditions under which a sibling tool should be chosen 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 burden and does disclose meaningful behavior: template mode emits a server canonical template, optimized mode augments via Client LLM Sampling while always preserving PDCA differences, the first three tools' purposes, and session_id continuation rules. Still omits file-writing semantics such as overwrite behavior, permissions, and the default output location.

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 compact, front-loaded paragraph that opens with the deliverable and keeps each clause informative. Dense but no filler sentences.

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 purpose/mode behavior are well covered. However, with no annotations, two undocumented parameters, and unaddressed file-write semantics, it is only minimally complete for a generation 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 coverage is 0%, so the description must compensate. It thoroughly explains the meaning of the mode enum values, but says nothing about output_dir or customization, leaving two of three parameters undocumented in both schema and description.

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 and deliverable (產生/generate a PxDCA SKILL.md) and clarifies scope by noting it does not create a requirements session, which differentiates it from generate_requirements. It is clear what is produced, though it never names the sibling tools it competes with.

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?

Explains the two modes (template vs optimized) and what each produces, and gives an explicit exclusion ('此 Tool 不建立需求 session') that routes session-creation needs to generate_requirements. Lacks a positive 'use this when' statement against the other generate_* siblings.

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 usefully discloses the internal process (consistency, coverage, traceability, risk checks that culminate in a report), but says nothing about side effects, whether output_dir gets written to, permissions, or runtime characteristics — relevant since the presence of an output_dir parameter implies file creation.

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 sentences with no filler, front-loaded with the most important fact ('稽核唯一入口'). The prerequisite condition and the internal behavior follow in logical order. Nothing is 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?

An output schema exists, so the return-format gap is largely covered, and the description explains the composite audit behavior. But for a tool with no annotations it leaves side-effect and permission questions unanswered, and output_dir's purpose is unaddressed, so it is adequate rather than 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 0%, so the description must compensate. It meaningfully explains session_id (a session whose requirements and architecture docs are complete), adding real semantics beyond the bare 'string' type. However, output_dir is left entirely undocumented in both schema and description, leaving half the parameters unexplained.

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 resource+role ('稽核唯一入口' – the sole audit entry point) and enumerates what the audit covers (consistency, coverage, traceability, risk) plus report generation. This differentiates it from the generate_* siblings, which produce artifacts rather than audit them. The purpose is clear without opening the 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?

Gives a concrete precondition: use the session_id of a session where the requirements and architecture documents are already complete. Calling itself the 'sole entry point' implicitly answers the alternative question (there is no other audit tool), though no explicit when-not-to-use guidance is given.

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