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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description usefully adds that the catalog is a *local synced snapshot* (implying possible staleness) and that status covers count plus last sync time, but says nothing about behavior when no sync has occurred.

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 that front-loads the resource and then lists the returned fields. No filler, no repetition of the tool name.

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 parameterless read-only status tool with an output schema that already documents the return shape, the description supplies the essential framing (local, synced, count + last sync time). Only edge cases such as a never-synced catalog are unaddressed.

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 takes zero parameters, so the schema_description_coverage baseline of 4 applies; there is no parameter semantics for the description to clarify or omit.

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 (the locally synced 보조금24 catalog) and what the status consists of (count, last sync time). It does not explicitly contrast itself with siblings like refresh_catalog or find_benefits, but the purpose is unambiguous.

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?

No when-to-use guidance is given. The description never indicates whether this should be called before refresh_catalog, after a sync failure, or on its own; the agent must infer the trigger condition from the tool name alone.

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 openWorldHint=true, so the agent knows this is a non-mutating lookup. The description adds that the call reports denial reasons and insufficient-information cases, which is modest extra context, but says nothing about latency, caching, or what happens when optional inputs are omitted.

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?

Purpose is front-loaded in one sentence, followed by a compact per-argument list with no filler. Slightly terse, but every line earns its place.

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 an output schema present, return values need no explanation, and the description sensibly covers purpose plus all six inputs for a read-only tool. Remaining gaps are the enumerations for traits and gender, which would materially help an agent populate the request 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 carries the full parameter burden and does so for all six arguments: units for median_income_percent, the meaning of traits as life/occupation/household situations, and the non-obvious convention that unknown traits should be omitted while inapplicable ones use []. It falls short of enumerating valid trait values or accepted gender strings.

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 resource: judging eligibility (자격 판정) for one named benefit, scoped to a single service_id. It also discloses the output character (ineligibility reasons, missing information). It does not name sibling tools like find_benefits or search_benefits, so the single-vs-many distinction is only implied.

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?

Usage is implied by the phrase '특정 혜택 하나에 대해' (for one specific benefit), which suggests this is a per-benefit follow-up rather than a discovery tool. However, no explicit when-to-use/when-not guidance or named alternative is given, leaving the agent to infer the relationship with search_benefits and get_benefit_detail.

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 openWorldHint=true, so the safety profile is covered. The description adds genuine behavioral context beyond that: eligibility is determined by coded conditions, and insufficient information is returned as follow-up questions rather than silently dropped, plus include_needs_info controls whether pending determinations appear.

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?

Front-loads the purpose sentence before the parameter list, and each arg line is tight. The length is justified by 10 undocumented parameters, though a few lines could be trimmed without loss.

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 an output schema present, return values need not be described, and the description fully covers parameters and the follow-up-question behavior. The only material gap is the absence of sibling routing guidance for a tool sitting alongside search_benefits and check_eligibility.

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 carry the full burden, and it does: every one of the 10 params gets meaning, format, and examples (e.g., sido '서울, 경기도, 부산광역시', traits ['직장인','1인가구'], limit default 20/max 50). It also encodes edge-case rules (leave blank if unknown, empty list [] if not applicable) and cross-references list_profile_options for valid trait values.

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+resource+scope: finding government/municipal benefits a user can receive, judged by coded eligibility conditions, and returning follow-up questions when data is insufficient. This is clear, but it does not explicitly differentiate itself from siblings like search_benefits or check_eligibility, which appear to operate in the same space.

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?

Usage is implied rather than explicit: it tells the agent to leave params blank if unknown and to consult list_profile_options for trait options, but never states when to choose this tool over search_benefits or check_eligibility. Partial guidance for parameter handling, none for tool selection.

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 openWorldHint=true, so the safe-read profile is covered. The description adds no operational traits such as permissions, rate limits, or error behavior beyond the annotated safety profile; it mainly enumerates returned content, which the output schema likely covers.

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 and front-loaded: the purpose and returned field list come first, followed by a clear Args section. The field enumeration is somewhat long but informative and not padded with 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?

For a one-parameter, read-only detail tool with an output schema and safety annotations, the definition is nearly complete: it identifies the resource, lists the detail content, and tells where to obtain service_id. It could be improved by explicitly routing eligibility questions to check_eligibility, but nothing essential for calling it 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 description coverage is 0%, so the description must compensate. It does add meaningful semantics for the single required parameter by specifying that service_id should be taken from find_benefits/search_benefits results. It does not define the ID's format or constraints, keeping it below a 5.

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 ('혜택 상세') and enumerates the specific detail fields returned (지원대상, 선정기준 원문, 지원내용, 신청방법, 구비서류, 문의처, 온라인 신청 링크, 코드화된 자격조건). This clearly separates it from search/list siblings, though it does not explicitly name an alternative.

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 Args line says service_id comes from find_benefits or search_benefits results, which implies use after a search step. However, it does not explicitly state when to use this tool versus check_eligibility or other siblings, nor does it include exclusions.

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 openWorldHint=false, so the safe-read profile is covered. The description adds that the content is trait options plus income input guidance, but says nothing about pagination, formatting, or whether options are exhaustive.

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 identifies the returned content and its consumer with no filler. Nothing is redundant or buried.

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 an output schema present, the return values do not need re-explaining, and there are no parameters to cover. The only gap is the absence of explicit routing guidance relative to the sibling tools, which keeps it short of a 5.

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 takes zero parameters, so the baseline is 4. The description usefully points out that the returned options are meant to feed find_benefits's traits argument, giving cross-tool semantics even though there are no local parameters to document.

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 concrete resource – the valid life/vocational/household situation options and income input method for find_benefits's traits argument – which lets an agent recognize it as a lookup/reference tool. It is differentiated from siblings by explicitly tying its output to find_benefits, though it never uses a clear action verb of its own.

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?

By naming find_benefits's traits parameter the description implies this tool is consulted before or alongside find_benefits, but it never states when to call it, when to skip it, or how it relates to siblings like check_eligibility. Usage is only inferrable.

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 tell the agent this is a non-read-only, open-world, idempotent operation, and the description adds relevant context about it being a full re-fetch normally automated once per day. It does not disclose side effects such as whether the cached catalog is overwritten or how long the refresh takes, so it adds moderate value 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?

A single sentence with zero waste, front-loading the action and the scope, with the frequency nuance tucked into a compact parenthetical.

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 refresh tool with an output schema available, the description covers what is refreshed and how often it normally happens, which is enough to invoke it correctly. A note on cost or when a refresh is warranted would make it fully self-sufficient.

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 takes zero parameters and schema coverage is 100%, so there is nothing for the description to disambiguate. Baseline 4 applies for a parameterless tool.

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 (다시 받아온다 / re-fetch) plus a precise resource scope (보조금24 전체 목록과 자격조건), so an agent can tell this re-pulls the full catalog and eligibility data. It is distinguishable from data-reading siblings like catalog_status or get_benefit_detail, though it never names 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 parenthetical '(보통은 하루 한 번 자동)' implies the data is refreshed automatically daily, which hints the tool is for forcing an out-of-band refresh, but it never states when an agent should call it versus relying on the cached data or the other catalog tools. Usage is implied rather than prescribed.

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 and openWorldHint, but the description adds real behavioral semantics beyond them: results exclude eligibility judgments, multiple space-separated words are AND-matched, and sido/sigungu scope the search to local-government projects. It still doesn't mention pagination, result freshness, or empty-result 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?

One front-loaded sentence states purpose, scope and examples, followed by a compact Args block. Every line earns its place; only the terse sigungu line could be clearer without adding length.

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 covers scope, the eligibility carve-out, and all four parameters. The main residual gap is the unaddressed overlap with the find_benefits sibling.

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 carries the full burden and largely meets it: query semantics (all words must be present), sido as a residence filter for local projects, sigungu, and limit with default 20 and maximum 50. Only sigungu's relationship to sido is left implicit.

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 (키워드로 정부·지자체 혜택을 검색한다) and adds a scope qualifier (자격 판정 없이) plus concrete example queries, so an agent can distinguish it from check_eligibility. It does not, however, differentiate itself from the sibling find_benefits, which appears to be the closest overlap.

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 parenthetical '(자격 판정 없이)' implies when this tool is appropriate versus an eligibility tool, and the example queries hint at suitable inputs. But no alternative sibling is named explicitly and there is no statement of when NOT to use it (e.g. versus find_benefits or get_benefit_detail), leaving routing partly to inference.

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 openWorldHint=true, so the safety and openness profile is covered. The description adds useful scope behavior (deadline-only filtering, exclusion of always-open benefits). Return format and pagination aren't addressed, but an output schema exists.

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?

Front-loaded with the scope sentence, then a compact Args list where each line earns its place. Slightly list-heavy but no wasted prose.

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 needn't be explained, and the description covers scope plus all parameters. For a read-only listing tool this is complete enough 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 carries the burden — and it does document all five parameters inline with meaning and defaults (days=window, sido/sigungu=residence, keyword=filter, limit=max results). This meaningfully compensates for the empty schema descriptions, though residency fields could say more about matching semantics.

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+resource — listing benefits with approaching application deadlines — and adds a scoping constraint (only items with explicit deadline dates; always-open applications excluded). This clearly separates it from a generic catalog, though it doesn't name which sibling (find_benefits/search_benefits) to prefer.

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 exclusion of 상시신청 (always-open applications) implies the intended use case, but there is no explicit when-to-use vs alternatives guidance naming sibling tools like find_benefits or search_benefits. Usage 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.