saightly

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

No annotations provided, so description carries full burden. Discloses cost=0 and booking constraints, but does not detail error handling, idempotency, or side effects beyond a 400 error. Moderate transparency.

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 sentences, front-loaded with purpose, second sentence adds critical condition. No 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?

Covers main use cases and constraints despite complex schema (10 params, nested objects). Mentions response cost field, but lacks description of return object structure. Good completeness for a creation 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 100%, baseline 3. Description adds value by explaining response field 'avgift_kr' is 0, the 'pass' array replaces 'bekraftad_tid', and 'slug' selects correct service. Enhances parameter understanding.

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 clearly states it creates an avrop (order/booking) against a supplier by organization number. Distinguishes from sibling tools like 'skapa_offertforfragan' which create inquiries, not direct orders.

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?

Provides condition for booking requiring contact info, but does not explicitly compare with alternatives or specify when to use this tool vs. 'skapa_offertforfragan' or 'valj_offert'. Limited guidance on choosing 'typ' enums.

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 discloses that the tool reads data from Bolagsverket, implies no side effects, and specifies what is returned. It lacks details on auth or limitations but is adequate for a simple lookup.

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 is front-loaded and contains no unnecessary words. Every part adds value.

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 covers the essentials: what it does, what data it returns, and the source. It could mention the return format or potential errors, but it is sufficiently 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 coverage is 100% with a description for the only parameter (orgnr). The description adds context about the data source but does not add significant meaning beyond what the schema provides. Baseline 3 is 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?

Description clearly states the tool retrieves basic information for an organization number from Bolagsverket, listing specific fields (name, status, address, SNI). It distinguishes itself from siblings that deal with services and offers.

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?

While the purpose is clear, the description does not explicitly state when to use this tool versus siblings, nor does it mention when not to use it or provide alternatives. Usage is implied but not 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?

Discloses each offer's fields (company, verification, rating, sum, price type) and explains price type meanings (fixed binding, budget target). No annotations, but description implies read-only behavior without 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?

Two sentences, no fluff, front-loaded with purpose and key details.

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 no output schema, description adequately explains what each offer contains and the tool's role in the workflow (create → read → select). Complete for a simple read 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 has 100% coverage with description for 'token'. Description adds value by linking token to the creation step, clarifying its origin.

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?

Clearly states it reads status and offers for a previous offer request (using token). Distinguishes from 'valj_offert' (select winner) and 'skapa_offertforfragan' (create).

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?

Explicitly mentions token comes from 'skapa_offertforfragan' and directs to use 'valj_offert' to select winner, providing clear context and alternatives.

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 full burden. It indicates a read operation via 'Hämtar detaljer', but does not disclose potential errors, rate limits, or other behavioral traits beyond retrieval.

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 concise sentence containing essential information with no fluff 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?

Given the low complexity (1 parameter, no output schema), the description is adequate but lacks specification of return value structure, which could help an agent process the output without additional inference.

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% with a clear description for the slug parameter. The tool description adds no additional semantic value beyond what is already in 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 explicitly states the tool retrieves details for a specific service by slug, and mentions the slug comes from sok_tjanster, clearly distinguishing it from sibling tools like sok_tjanster (search) and las_foretag (company).

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 when to use the tool (after obtaining a slug from sok_tjanster) through clear context, but does not explicitly state when not to use it or name alternatives.

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 must carry the full burden. It explains that the tool shows actual calendar data minus bookings and absences, and that waiting times are already booked and cannot be booked. However, it does not disclose edge cases (e.g., no times available) or potential authorization requirements. The description is adequate but not comprehensive.

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 moderately concise with each sentence adding useful context. It is front-loaded with the main purpose. Some redundancy exists (e.g., explaining slot_minuter and resurser separately), but overall it is efficient and well-structured.

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 lack of output schema and annotations, the description covers the core functionality and key concepts (available times, waiting times, slot length, performers). However, it omits details on return value structure, error handling, or required permissions, leaving some gaps for an agent to rely on implicit knowledge.

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%, so baseline is 3. The description adds value by explaining the meaning of slot_minuter (derived from slug) and resurser (derived from resurs), and introduces the concept of platstyp (not a parameter) to clarify the service location context. This enrichment justifies a score above baseline.

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 that the tool retrieves the next available times from a provider's actual calendar (schedule minus bookings and absences). It specifies the key concepts like slot length, performers, and waiting times, distinguishing it from sibling tools like avropa_tjanst which is for ordering.

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 explains that the returned time should be used as 'bekraftad_tid' in avropa_tjanst, and warns that waiting times ('vantande') are not bookable. This provides clear usage context, though it does not explicitly contrast with other sibling tools for 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?

No annotations provided, so description carries full burden; it discloses that AI structures the brief and matched companies return quotes, but lacks details on side effects or response format.

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 concise Swedish sentences plus a parenthetical, front-loaded with purpose, zero 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?

Covers overall workflow and parameter usage well, but lacks explicit return value details; hints at outcome (quotes from companies) but no output schema given.

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%, baseline 3; description adds value by giving an example of 'beskrivning' (natural language) and stating that 'ort' controls geographic matching, plus high-level AI structuring context.

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?

Clearly states the tool sends a general request for quotes to multiple verified companies in an industry, with explicit distinction from sibling tool 'avropa_tjanst' for booking a single supplier.

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?

Explicitly says when to use (for quote jobs of all sizes) and when not to use (for booking a single supplier, use 'avropa_tjanst'), and lists valid profiles.

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 must disclose behavior. It explains that it parses free text for category, location, and urgency, returns ranked providers, and lists tips with reasons. However, it does not mention whether the operation is read-only, rate limits, or error handling.

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 two sentences, efficiently front-loading the core purpose and then adding key behavioral details about tips. Every clause adds value 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 single-parameter tool with no output schema, the description adequately covers input interpretation and output behavior (ranked providers and tips). It could optionally mention result count limits or pagination, but 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 input schema covers 100% of parameters, describing 'query' as a natural language search string. The description adds context that the query is interpreted for category, location, and urgency, enriching the schema's minimal 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?

The description clearly states it searches local services in free text, interprets category, location, and urgency, and returns ranked providers. It distinguishes from sibling tools like 'avropa_tjanst' (order service) and 'las_foretag' (read company) as a search function.

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 finding local service providers via natural language queries. It mentions tips for alternatives, but does not explicitly state when not to use or compare to other search-like tools among 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 fully bears the transparency burden. It discloses idempotency and the side effects (acceptance, decline, contact info sharing, request closure), which are critical behavioral traits not otherwise conveyed.

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 sentence with clear front-loading of the action. Every clause adds value: the action, the source, the result, and idempotency. No 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?

Given the tool's simplicity (2 parameters, no output schema, no nested objects), the description provides all necessary context: what it does, its effect, and idempotency. It is fully sufficient for an agent to understand and invoke the tool 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 100%: both parameters are described in the schema. The description reiterates 'id från las_offertforfragan' for offert_id, which adds no new information beyond the schema. Baseline 3 is 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 uses a specific verb ('Väljer vinnande offert') and clearly identifies the resource (a quote request from 'las_offertforfragan'). It distinguishes itself from siblings like 'skapa_offertforfragan' (create) and 'las_offertforfragan' (read) by describing the selection action.

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 explains the outcome of using the tool (accepts one, declines others, closes request) but does not explicitly state when to use it versus alternatives. However, given the sibling context and the tool's purpose, the usage context is clear.

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