ASAPDevs

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered without description help. The description contributes the payload contents (a contact form plus static contact fields), which is mild extra value, but says nothing about freshness, formatting, or whether the values are static constants.

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 naming the resource first and the returned fields second. No filler, no redundancy, nothing that could be cut without losing 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?

With no output schema, the description does the work of telling the agent what comes back, which is the main thing needed for a zero-parameter read tool. Only minor gaps remain, such as whether any of the fields can be absent.

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 4 baseline applies; there is no input for the description to clarify. Its only parameter-adjacent claim, that a contact form is included, is content rather than input 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 resource (ASAPDevs contact data) and enumerates exactly what it returns: e-mail, phone, address and contact form. It is clearly distinguishable from siblings like get_pricing or search_blog by topic, 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?

Usage is only implied: the name and field list make it obvious an agent calls this when it needs contact details. There is no explicit when-to-use statement, no prerequisites, and no routing to or away from 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?

The annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered structurally. The description adds content-scope context (which fields the price list contains) but discloses no behavior beyond that — no freshness, currency/format caveats, or whether prices are current. With annotations carrying the read-only burden, 3 is appropriate.

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 dense sentence that front-loads the resource and then the parenthetical enumeration of contents. Nothing is padded or redundant, and it is appropriately sized for a zero-parameter lookup tool.

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, zero-parameter read tool with no output schema and no nested structures, the description covers both the primary data (subscription packages and prices) and the secondary rule (pricing for other services). It could say a little more about the shape of what comes back, but nothing essential for correct invocation 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?

The tool takes zero parameters, so the schema has nothing to document and the baseline is 4. The description correctly implies a no-argument retrieval of a single fixed price list, and introduces no parameter-like concepts that would need explanation.

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 (the 'Pogotowie IT' subscription price list) and enumerates its contents — packages, net monthly prices, hours, response time — plus a pricing rule for other services. That is concrete and non-tautological. It stops short of distinguishing itself from the potentially overlapping sibling 'list_offers', so it lands at 4 rather than 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 explicit when-to-use or when-not statement, nor any named alternative. The content scope (subscription pricing plus pricing rules for other services) strongly implies its usage, which is the definition of implied guidance. An agent can reasonably infer the trigger, but it must do so itself.

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 safety profile is covered. The description adds that results are case studies and implementation posts and that filtering is optional, but says nothing about ordering, volume, or pagination beyond what is structured.

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 brief sentences, front-loaded with the resource and followed by the filter note; nothing is padded. It is slightly lean given the sibling overlap it never addresses.

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 zero-required-parameter read-only list tool with a fully documented enum parameter and annotations covering the safety profile, the description says enough to invoke it correctly. Only sibling differentiation 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 100% and the single area parameter is fully enumerated, so the schema carries the semantics. The description only restates that area is an optional filter, adding no meaning beyond the schema 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 names the resource concretely ('Opisane realizacje ASAPDevs: case study i wpisy o konkretnych wdrożeniach'), so an agent understands this returns published case-study write-ups. It does not, however, distinguish itself from the sibling search_blog, which also surfaces posts, leaving overlap unresolved.

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?

'Opcjonalny filtr obszaru' signals that the area filter is optional, which is useful invocation context. There is no statement of when to choose this tool over search_blog or list_offers, so usage is only implied.

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 safety is covered. The description adds real value by disclosing the return payload (service name, offer-page URL, short description) and that results are grouped by category, which matters because no 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?

One sentence, front-loaded with the verb and resource, then the groupings, then the return shape. 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?

For a parameterless list tool with no output schema, the description covers both content scope and returned fields adequately. It omits ordering and volume/pagination expectations, which is a minor gap for a fixed catalog.

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 per the rubric the baseline is 4. The description adds nothing about inputs because none exist, and none are needed.

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 ("Lista") and resource (ASAPDevs services), and enumerates the groupings it returns (e-commerce, apps/AI, websites, care/security). This clearly separates it in content from siblings like get_pricing or search_blog, 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?

Usage is implied — an agent can infer this is the entry point for browsing the service catalog — but there is no explicit statement of when to prefer this over get_pricing or list_case_studies, nor any prerequisites. Minimum viable.

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 safety is covered. The description adds genuinely useful behavioral context beyond that: matching is case-insensitive and diacritic-insensitive, which affects how an agent should phrase the query. It stops short of describing result ordering or pagination 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?

A single compact sentence that front-loads the action and resource, then adds the matching caveat in a parenthetical. 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?

For a two-parameter search tool with no output schema and full schema coverage, the description is nearly sufficient: it states scope and matching rules. It omits result ordering/limit interaction, but that is minor given the limit parameter is self-documented.

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 the baseline is 3. The description goes beyond the schema by explaining the matching semantics (case- and diacritic-insensitive) that govern how the `query` value is interpreted, which is directly actionable for the required parameter.

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?

Specific verb ("Wyszukuje") plus a concrete resource ("wpisy na blogu ASAPDevs") and the fields searched (title, lead, tag). This is unmistakably distinct from the sibling tools (get_contact, get_pricing, list_case_studies, list_offers), which cover entirely different resources.

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 — search blog posts when you need to find one by phrase — but there is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named for the case where the exact post is already known.

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