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

With no annotations, the description carries the full burden and it does disclose a non-obvious behavior: sections that cannot be published are dropped and written to a warning. This is useful, but it does not state whether the operation is read-only, whether authentication or permissions are required, or any other side effects.

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 efficient sentence that leads with the purpose and adds a behavioral detail. There is no filler or repetition, though the extreme brevity leaves several important aspects underspecified.

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, but the tool has 3 parameters with zero schema descriptions, no annotations, and no usage or parameter guidance. For a tool with a required channel parameter and optional package and opportunity parameters, the description is too thin for an agent to confidently select and invoke it 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% and the description does not mention channel, package, or opportunity at all. The agent receives no help understanding what these parameters mean or how they should be populated, so the description fails to compensate for the empty schema descriptions.

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 verb and resource: extracting material for writing media-facing copy. It also adds a specific behavior, dropping non-publishable sections and recording them as warnings, which helps distinguish it from siblings such as get_positioning or check_consistency. However, it does not explicitly name alternatives or contrast itself with sibling 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?

The phrase '媒体向けの文面を書くための' implies the tool is for assembling material when preparing media-facing content. There is no explicit guidance about when not to use it, prerequisites, or which sibling tool to choose in other scenarios.

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 well: it states the master document is not modified ('正本は変えない') and that nonexistent names return a list of existing scopes rather than an error. This discloses important edge-case behavior and the read-only character of the operation. It could add more about error conditions or the meaning of '直し先', but the core behaviors are covered.

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 front-loaded: the primary action and non-mutation guarantee come first, followed by a concise scope specification. Every sentence earns its place, and the edge-case behavior is included without bloat.

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 low complexity, one optional parameter, and the presence of an output schema, this description is complete enough for an agent to call the tool correctly. It covers the parameter semantics, the non-destructive nature, and the unusual invalid-name behavior. No critical information appears to be 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?

The schema tells the agent almost nothing about the scope parameter: it is simply a nullable string with a default. The description compensates fully by defining the exact accepted values, what each value selects, and the behavior for invalid names. This is exactly the kind of semantic enrichment the dimension asks for.

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 operation: apply the master document to constraints and return a list of violations with fix targets, while explicitly noting the master is not changed. This is specific and informative, but it does not explicitly distinguish this tool from its siblings such as get_positioning or revise_package.

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 guidance on the scope parameter values: omitted or '全体' means the whole master, a medium name selects that medium, and a presentation file name selects that item. It also explains the behavior for nonexistent names. It does not explicitly mention when to prefer this tool over alternatives, but the input guidance is strong.

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 of disclosing behavior. It does convey that the operation reads current positioning and that channel omission changes the result to the full-scope decision. It does not explicitly state side-effect freedom, error behavior, or what the returned object contains, though the output schema may cover some of this.

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 one short Japanese sentence that immediately states the core action and then clarifies the optional-parameter behavior. It contains no filler, repeated information, or unnecessary detail.

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: one optional parameter and an output schema is present, so return-value explanation is not necessary. The description covers the primary behavior and the effect of omitting the parameter, which is the main uncertain point for an agent. It could be slightly stronger by explicitly noting the absence of side effects, but given the tool's simplicity it is largely 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?

The schema provides no parameter descriptions, and schema description coverage is 0%, so the description must compensate. It does add meaning by mapping the 'channel' parameter to a medium ('媒体') and explaining that omitting it returns the decision applied to the whole. However, it does not clarify what valid channel values look like or what '全体' concretely means, leaving some 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 uses a specific verb ('読む' / read) and a clear resource ('いまの決め（看板）' / current decision), so an agent can tell this is a retrieval operation. It also explains the behavior when the optional channel is omitted, which adds precision. It does not explicitly differentiate itself from sibling tools like record_positioning, but the read-vs-write intent is reasonably clear.

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 indicates that the tool reads current positioning and that omitting the channel scopes the request to the overall setting. However, it does not state when to choose this tool over siblings such as record_positioning or check_consistency, nor does it mention any exclusion conditions. Usage context is 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?

No annotations are provided, so the description bears full behavioral burden. It discloses rejection behavior on missing required fields, atomic 'one block' registration, required date format, and a concrete return payload (package definition freshness and count of presentations with filenames). It omits permissions/reversibility, but the core behavior is well covered.

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 short, front-loaded with the primary action, and each sentence adds a distinct piece: action, rejection condition, date format, and return value. No filler is present.

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?

Despite having 5 parameters (4 required) and no annotations, the description does not explain how to populate the main fields, nor does it clarify what qualifies as an exception. It covers the return behavior, which helps, but the calling contract is incomplete.

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 only addresses the date parameter ('2026-09-16' format); it gives no semantics for scope, headline_package, rationale, or exceptions. An agent would have to guess the meaning of headline_package and scope from names 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?

Description opens with a specific verb+resource: 'register the sales-positioning decision as one block' (売り方の決めを1ブロック登記する). This clearly distinguishes from siblings like get_positioning (retrieval) and register_capability (capability, not positioning). It also states a behavioral guard: refuse without writing if required fields are missing.

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 context—register a positioning decision—and gives a date format rule, but it never states when to prefer this over siblings or mentions alternatives. There are no exclusions or routing cues beyond the resource type, so an agent could still be uncertain between record_positioning and register_capability.

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 burden of behavioral disclosure. It usefully reveals that failed validation leads to a refusal without writing and a 'next move' response. It does not, however, disclose success-path behavior, permission requirements, or whether entries are modifiable later, leaving important gaps.

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 core action, then the failure behavior and resulting response. Every phrase earns its place and there is 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?

Despite having an output schema, the definition leaves substantial gaps: no parameter semantics, no sibling differentiation, no guidance on what valid categories or evidence sections look like, and no success-path description. An agent would likely struggle to invoke this correctly without additional context.

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 alludes to 'required fields, classification, and evidence sections' without defining the four parameters (name, description, category, evidence_sections) or their validation criteria. This partial mapping does not compensate for the absent schema-level 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 verb ('adds a row') and resource ('capability ledger'), and adds refusal behavior. It is clear, but it does not explicitly distinguish this tool from siblings such as record_positioning, so it does not reach a 5.

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 use case (registering a capability entry) and gives a conditional rule: if required fields, classification, or evidence sections fail, refuse without writing and return the next move. However, it provides no explicit guidance on when to use this tool versus the sibling tools or when not to use it.

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 of explaining side effects. It does this well: it warns that the tool refuses without writing if capabilities are not in the ledger, and it details what happens when the revision passes—rewriting the section, updating the last-updated date, and adding a section if absent.

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 three tight sentences with no filler. The main purpose is front-loaded, followed by the refusal condition and then the write behavior. Every sentence adds information.

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 6 parameters, 0% schema description coverage, and no annotations, the description is too thin. The behavioral details are useful, but the missing parameter meanings and lack of usage context leave an agent guessing about how to construct a valid call.

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, but it only implicitly refers to capabilities ('台帳に無い機能名') and the package name. Parameters like basis, buyer, source, and hypothesis_state remain completely 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?

The description clearly states the action ('改訂する' / revise) and the resource ('パッケージ定義' / package definition). It stops short of explicitly distinguishing this from sibling tools, but the revision framing is specific enough to be understood.

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 revise_package versus get_positioning, record_positioning, or register_capability. The description explains the tool's behavior but not the conditions under which an agent should select it.

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