saaskr — Korean SaaS Directory (한국 SaaS 디렉토리)

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It does not state whether the tool is read-only, requires any permissions, or has side effects. It only mentions comparison dimensions, leaving the safety profile unclear.

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, well-structured sentence that efficiently conveys the tool's purpose and comparison topics without unnecessary words. It is front-loaded with the core action ('compare two Korean SaaS side by side').

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 tool's simplicity, the description adequately covers the essential aspects (comparison dimensions) and implies a side-by-side format. However, without an output schema, it could benefit from clarifying the return structure, but it is not severely lacking for a comparison 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?

The input schema fully documents both parameters (slug_a, slug_b) with clear descriptions, and the tool description adds no additional meaning beyond what the schema already provides. Baseline 3 applies due to 100% schema description coverage.

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 function: comparing two Korean SaaS products side by side, and it enumerates specific comparison dimensions (category, operational status, popularity, introduction). This distinguishes it from sibling tools like get_korean_saas (single SaaS) and search_korean_saas (search).

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 for side-by-side comparison but provides no explicit guidance on when to choose this tool over alternatives, nor any exclusion criteria or references to sibling tools. 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.

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 explicitly states the operation is retrieval ('가져온다') and lists the specific information returned (introduction, category, official site, operational status, reviews), adding useful behavioral context about the return content. It does not mention error cases or side effects, but for a read tool this is adequate.

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, front-loaded sentence that clearly states the action and the information scope. Every word earns its place with no redundancy.

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 tool with one parameter and no output schema, the description lists the return categories, which is sufficient to set expectations. It does not detail error responses or exact structure, but that is not critical for such a straightforward get operation.

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 100% and the parameter description ('search_korean_saas 가 반환한 slug') already explains the parameter meaning. The tool description adds no additional parameter semantics, so the baseline score of 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 clearly states what the tool does: it retrieves detailed information (introduction, category, official site, operational status, reviews) about a specific Korean SaaS. The verb '가져온다' (retrieves) and the resource '특정 한국 SaaS' are specific, and the tool is distinct from siblings like search, compare, and list.

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 after identifying a specific SaaS, but it does not explicitly state when to use it versus siblings. The parameter schema hints that the slug comes from search_korean_saas, but this is not in the description. There is no mention of alternatives or 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?

With no annotations, the description carries the full burden of transparency. It clearly discloses the return content (16 categories, counts, selection criteria), which is sufficient for a parameterless read-only tool. It doesn't mention data freshness or authentication, but these are not critical for a simple list endpoint.

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 concise Korean sentence that immediately states the output scope and content. No filler or redundant phrasing.

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 utility with no output schema, the description fully specifies what the tool returns. The simple nature of the tool and clear return definition make it contextually 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 tool has zero parameters, so the baseline is 4. There is nothing for the description to add beyond what the empty schema already implies.

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 verb 'list' clearly indicates the action, and 'saas_categories' identifies the resource. The description adds specific detail (16 categories, service counts, selection criteria), which fully distinguishes this from sibling tools that operate on individual SaaS products.

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 a 'browse categories' use case but does not explicitly state when to choose this over search/compare/get alternatives. No exclusions or alternative references are provided, so guidance 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?

With no annotations provided, the description carries the transparency burden. It discloses key behavioral traits: only returns services confirmed to be in operation, and searches specific fields. It does not describe output structure or pagination, but these are less critical for a read-only search tool and the schema covers limit.

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 concise, front-loaded with the core function, and uses one sentence plus example queries. Every phrase adds value: search fields, active-only filter, category narrowing, and concrete usage examples. No redundancy or wasted words.

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 search tool with three optional parameters and no output schema, the description sufficiently covers search scope, the active-service filter, and category narrowing. It does not specify result fields, but the sibling get_korean_saas likely provides details, so this level of completeness is acceptable.

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 descriptions already cover all three parameters with examples and defaults (limit, query, category). The description adds only a marginal reinforcement that category can narrow results, which the schema already states. Baseline of 3 is appropriate given the high schema coverage.

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 function: searching for Korean SaaS, with specific search targets (name, tagline, description, tags) and a filter for active services. It distinguishes from sibling tools via the verb 'search' and explicit scope, e.g., get_korean_saas retrieves a specific service, list_saas_categories lists categories.

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 provides clear usage context with realistic example queries ('한국 AI 도구', '국산 협업툴') and mentions narrowing by category. It does not explicitly mention when to use alternative tools (e.g., get for a single SaaS, compare for comparisons), so it lacks explicit exclusions but is still unambiguous about when search is appropriate.

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 and does well. It discloses key behaviors: confirming name/URL/tagline with the user, auto-verifying the link before publishing, placing new submissions in a review queue, and prohibiting fabricated descriptions. This goes far beyond a basic purpose 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 three sentences, front-loaded with the main action, and each sentence adds a distinct piece of information: purpose, usage triggers, and validation/confirmation rules. There is no filler or redundancy.

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 main flow (registering, handling existing entries, validation, and review) but does not describe the exact return format or error handling. Given the moderate complexity (7 parameters) and lack of output schema, it is sufficient for invocation but could be enhanced with response 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?

The schema already provides 100% coverage with descriptions for all parameters, so baseline is 3. The description adds behavioral semantics by specifying that certain parameters (name, URL, tagline) are confirmed with the user and that the description field must only contain user-provided information, guiding the agent on how to populate these fields correctly.

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 registers a SaaS to the saaskr directory ('saaskr 디렉토리에 등록한다'), using a specific verb and resource. It also distinguishes itself from siblings by describing handling of both existing and new services, which is not covered by compare/get/list/search 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 description provides explicit trigger phrases ('내 서비스 등록해줘', 'saaskr에 올려줘') and outlines the two main scenarios (existing vs. new). However, it does not explicitly name alternatives for other actions, so while usage context is clear, it could be stronger by directly excluding sibling tools.

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