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

With no annotations, the description carries full behavioral burden. It usefully discloses the non-destructive upsert behavior ('does not overwrite, smart-updates the existing page'), which is genuinely important for a write tool. However, it doesn't clarify what 'smart update' actually merges, what happens to omitted fields, permission requirements, or return 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?

Two tightly written sentences that front-load the core purpose before the upsert caveat. No filler, though it is terse enough that it leaves behavioral questions open rather than earning a 5.

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 10-parameter write tool with no annotations and no output schema, the description is adequate but thin. It explains the core upsert semantics but omits what a successful call returns and how partial updates are resolved, which matters for an agent deciding what to pass.

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 all 10 parameters documented in the schema, including Korean-language field hints and format examples. The description adds no parameter-level detail beyond this, so baseline 3 applies.

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 (maintenance site / client company) and states both operations: registration and update. It implicitly distinguishes itself from list_maintenance_sites by being the write-side counterpart, though it never names a sibling 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?

There is no explicit when-to-use guidance, no prerequisites, and no routing to alternatives (e.g., when to use list_maintenance_sites to check first). The upsert behavior is described but the agent is not told under what circumstances to reach for this tool versus the work-log or troubleshooting 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?

No annotations are provided, so the description carries the full burden. It reveals the write target (Notion) but says nothing about required Notion permissions, whether an entry is created as a new page, whether duplicates are possible, whether the write is reversible, or what happens on partial failure — all significant for a mutation tool with zero annotation coverage.

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 that names the action, the content type, and the destination with zero filler. It is efficiently sized, though the extreme brevity is partly what leaves the behavioral gaps noted elsewhere.

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 7-parameter mutation tool with no annotations and no output schema, the description is too thin: it does not confirm which fields are mandatory, does not describe the created record or any returned identifier, and gives no failure or retry behavior. Only the destination is disclosed.

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% and every one of the 7 fields carries its own Korean description, so the schema does the heavy lifting. The description adds no field-level meaning, no format hints for error_log, and no indication that title/symptom/resolution are the three required fields. Baseline 3 applies when the schema fully documents parameters.

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 (적재합니다, 'loads/inserts') plus a clearly bounded resource (에러 및 트러블슈팅 조치 내역) and the destination system (노션). This separates it from read-side siblings like search_troubleshooting and from the adjacent add_work_log, though it never names those siblings 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?

There is no guidance on when to use this tool versus search_troubleshooting, add_work_log, or list_work_logs, and no prerequisites or timing conditions are stated. The agent must infer from the name alone that this is the write path for troubleshooting records.

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 write target (Notion work-log DB), but says nothing about whether the write is idempotent, what happens to duplicate dates/titles, whether it fails on missing fields, or what the caller gets back.

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 sentence that front-loads the action and destination with zero filler. Nothing in it 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?

For a 7-parameter mutation tool with no annotations and no output schema, the description covers destination and record type but omits any note on required vs optional fields, error behavior, or result. The rich schema compensates for parameters, leaving the description minimally adequate.

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%, so every one of the 7 parameters is already documented in the schema, making 3 the baseline. The description adds no parameter-level meaning beyond naming the record types that can be logged.

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 (등록/register) and resource (업무 일지 및 정기점검 수행 기록), plus the destination system (노션 업무일지 DB). It is clear enough to separate from add_maintenance_site and add_troubleshooting, though it does not explicitly name those siblings.

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 add_troubleshooting, add_maintenance_site, or list_work_logs. Inclusion criteria are only implied by the tool name and the resource nouns in the sentence.

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. The verb 조회 implies a read, but the description says nothing about pagination, result size, ordering, or empty-result behavior for a list operation that could return many sites.

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 filler. Every word contributes to the stated purpose without padding.

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 one-parameter read tool with full schema coverage and no output schema, the description is minimally sufficient. It omits any mention of the filtering parameter or result characteristics, leaving a noticeable gap even at this low complexity.

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% and the single optional site_name parameter is already documented in the schema. The description adds no filtering, matching, or format semantics beyond the structured field, so the baseline 3 applies.

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 (조회) and resource (유지보수 사이트 목록), making it immediately distinguishable from the sibling add_maintenance_site. It is clear but does not explicitly name the alternative tool or scope of what is returned.

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 versus the sibling add_work_log/list_work_logs tools, nor any note that the optional site_name filter narrows results. The only usage signal is the implicit 'list' semantics of the name.

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 the full behavioral burden, yet it only implies a read via '조회' and says nothing about pagination, result limits, sort order, or default scope. For a list tool with zero structured safety metadata, this is a significant disclosure 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?

One short front-loaded sentence with no filler, but it is minimal to the point of conveying almost nothing actionable. It is concise without being informative.

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-required-parameter list tool with no output schema, the essentials are technically covered by the name and schema. Missing pagination, ordering, and default-scope information keeps it at merely adequate.

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% and the single optional 'query' parameter is already documented as a search term, so the baseline is 3. The description adds no format, matching-rule, or empty-string semantics beyond the schema.

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 (조회합니다 / retrieve) and resource (업무 일지 목록 / work log list), so an agent can tell it apart from mutation siblings like add_work_log. It does not, however, contrast itself with the other list-style sibling (list_maintenance_sites) or clarify scope beyond the resource noun.

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 alternatives such as add_work_log or search_troubleshooting, nor any mention of the optional keyword filter or default ordering/paging. The agent must infer usage entirely from the name.

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, yet it only says a search happens. It does not disclose that the operation is read-only, how results are ordered or limited, whether matching is exact or fuzzy, or what the result set looks like.

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 short sentence with no filler and the key action front-loaded. It is efficient, though its brevity borders on under-specification rather than tight conciseness.

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 one-parameter read tool with no output schema, the description is minimally adequate. It omits any note about result format, matching behavior, or empty-result handling, which leaves real gaps even for a tool this simple.

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% (the single query parameter is documented as 검색 키워드), so the schema already carries the parameter meaning. The description adds no keyword syntax, matching behavior, or format guidance, making the baseline 3 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 gives a specific verb (검색합니다) and a scoped resource (트러블슈팅 해결 사례), which is slightly more specific than the tool name alone because it clarifies that resolution cases are what is searched. It does not, however, distinguish this from siblings like list_work_logs or add_troubleshooting, so it stops short of 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?

There is no guidance on when to use this tool versus the sibling list/add tools, nor any stated preconditions or exclusions. The agent must infer usage entirely from the name.

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