ABC Remonty Oleba

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

With no annotations provided, the description carries full behavioral transparency responsibility. It states 'Deterministic and read-only: missing facts are reported, never guessed,' which clearly communicates that the tool never fabricates data and is safe for read-only use. It also notes the output is source-linked, adding helpful behavior context, though it omits details like 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 with no wasted words, front-loading the core action and data sources, followed by a concise behavioral note. It earns its length by providing purpose and safety in a compact form, though it could have used the space to address some parameter complexity.

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 complexity (16 parameters, no output schema, no annotations), the description is insufficiently complete. It does not explain the structure of the 'answer bundle,' how parameters combine, what fallback_mode values mean, or the output format. An agent would need deep inference from parameter names and sibling tool behavior to use it 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 low at 50% (8 of 16 parameters documented). The description adds no parameter-level detail and does not compensate for undocumented parameters such as year, location, min_area_m2, max_area_m2, or price_limit. It only gives high-level context about composing from public data, leaving the agent to guess meanings of the other half of the 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?

The description states a specific verb+resource: 'Compose a compact, source-linked answer bundle' from the structured service catalog, cennik, service-area evidence, and realization portfolio. The title adds that it resolves renovation questions, and this clearly distinguishes it from sibling getters like get_prices or get_realizations, which return single data types rather than a composed answer.

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 this tool is for answering natural-language renovation questions by composing multiple source types, but it never explicitly says when to use ask_oleba versus a sibling getter, nor does it provide exclusions or conditions. An agent can infer the usage context from 'resolve a renovation question,' but explicit routing guidance is absent.

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 of behavioral disclosure. It does disclose an important behavioral stance: absence of public evidence is never interpreted as proof of refusal. This is meaningful. Yet it says nothing about return values, side effects, permissions, or how evidence is weighed, leaving the behavioral picture incomplete.

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 with no filler, and the core purpose is front-loaded. The wording is somewhat abstract, which reduces immediate clarity, but the structure is tight and every clause adds meaning.

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 3-parameter tool with no output schema and no annotations, the description leaves notable gaps: explicit parameter semantics, return shape, and relationship to sibling tools like get_realizations or get_service are all missing. The single interpretive caveat is useful, but not enough to make the tool fully callable by an agent.

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 0%, so the description must compensate by explaining the parameters. It loosely references 'service/location offer' and 'locality,' which hints at the service and location parameters, but it never names them directly and does not mention realization_limit at all. An agent cannot confidently map the abstract wording to the actual input fields.

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 task: distinguishing a documented service/location offer from merely having or not having a published realization. This communicates that the tool verifies public evidence rather than just listing or fetching content. It does not explicitly differentiate from siblings like get_realizations or get_service, 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?

The description implies when to use the tool: when an agent needs to determine whether public evidence documents an actual service offer at a location. It also adds an interpretive caution about absence of evidence. However, it gives no explicit when-not-to-use guidance or alternatives among the eleven sibling tools.

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. It does disclose a meaningful behavioral constraint—refusing password-protected, unpublished, and noindex content—and clarifies that it returns Markdown, text, or metadata. However, it omits details like error behavior for nonexistent IDs, authentication needs, or rate limits, leaving some behavioral ambiguity.

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 compact sentence that front-loads the core operation, then adds the key refusal behavior. Every word earns its place with no redundancy or 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 simple 2-parameter read tool with no output schema or annotations, the description is nearly complete: it covers the input types, output formats, and refusal conditions. The main gap is the absence of explicit error or 'not found' behavior, but this is a minor omission given the tool's simplicity.

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 only 50%, but the description adds value by explaining 'numeric ID, slug or same-site URL' for the identifier and mapping 'Markdown/text/metadata' to the format enum. This goes beyond the bare schema, though it does not fully document edge cases like malformed URLs or unsupported formats.

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 ('Resolve'), a clear resource ('public WordPress item'), and the accepted identifier types ('numeric ID, slug or same-site URL'). It also names the output formats, making the tool's purpose unambiguous and distinguishable from listing tools like list_services or search_site.

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 when to use it: when you have a numeric ID, slug, or URL for a specific Oleba page and want its content. However, it does not name alternative tools or explicitly state when not to use it, so the agent must infer the boundary between this and sibling tools like get_service or get_realization.

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?

There are no annotations, so the description carries the full burden of behavioral disclosure. It adds some transparency by specifying 'public' and the kind of content returned, but it does not state what the output looks like, how relevance is determined, whether pagination is involved, or what the limit parameter controls.

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 focused sentence with no filler. The main action and resource appear first, and the locality examples are scannable and immediately useful.

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 lookup tool with two parameters and no output schema, the description provides enough to make a reasonable first call: supply a locality and set an optional limit. However, it lacks return format details and sibling differentiation, so it is not fully complete for an agent deciding between this and related tools.

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 adds useful meaning for the required `location` parameter by giving real locality examples, but it does not explain the optional `limit` parameter at all, leaving its semantics to inference from the schema's default and bounds.

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 ('Find') and resource ('public Oleba pages/posts'), and clearly defines the locality-based scope with concrete examples. It doesn't explicitly differentiate from siblings like search_site or get_content, but the resource and locality criterion make the purpose clear.

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 when to use the tool: when you need Oleba pages or posts relevant to a named locality. It provides example locations but gives no explicit guidance about when not to use it or how it compares with alternatives such as search_site.

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 explaining behavior. It discloses that the tool returns informational excerpts and is not a binding quote, which is useful, but it does not describe potential limitations, whether results are always found, or any other operational 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?

The description is two short sentences that immediately convey what the tool does and the key caveat about non-binding results. Every word earns its place, and the most important information is front-loaded.

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 required parameter and no output schema, the description covers the essential selection and invocation needs. It explains the purpose, the input type, and the nature of the output, though it could briefly mention what happens when the query has no match.

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 full parameter documentation with a description and examples, so the baseline is 3. The tool description adds minimal semantic value beyond restating that the query is a service or phrase, which is already covered by 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 clearly states the action ('Find context') and the resource ('public Oleba renovation price-list page'), making the tool's purpose understandable. It also indicates a distinct non-binding nature, but it does not explicitly differentiate this from sibling tools like get_prices, which could be similar.

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 gives a reasonably clear context for when to use the tool: when looking for informational context about a service or phrase on Oleba's price-list page. However, it does not explicitly contrast it with sibling tools or state when not to use it, aside from the implied boundary that it is not a binding quote.

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 must carry safety and behavior disclosure. It adds useful behavioral context—public informational ranges, not binding offers—and the word 'Parse' implies a read operation. It does not explicitly state read-only/no side effects, nor describe output/pagination details, but the description is not silent.

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?

Three short sentences with the main purpose first, followed by the optional query note and the non-binding caveat. Every sentence adds distinct information and there is 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?

This is a simple two-optional-parameter tool with no output schema; the description covers purpose, optionality, and status of returned prices. It is functional but leaves two gaps: it does not describe the structure/fields of the returned rows, and it does not differentiate from the closely named sibling get_price_information.

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 50%: query already has a description with examples, while limit has only type and bounds. The description only notes 'Query is optional,' which adds marginal value over the schema and does not explain limit's effect or add meaning for the undocumented limit 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?

The description opens with a specific action and resource: 'Parse the public renovation cennik into structured rows,' and adds that results are public informational ranges/amounts. This clearly identifies the tool's function and separates it from related siblings like get_price_information, which are not described as parsing the cennik.

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 gives context that this is the public renovation price list and that query is optional, so an agent can infer when to call it. However, it does not explicitly state when to prefer this over siblings such as get_price_information or provide any exclusions/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 must carry the behavioral burden. It indicates this is a read-style operation by saying 'Resolve ... and return' and scopes to 'public' posts, but it never explicitly states that no data is modified, whether authentication is required, or how errors are surfaced. The transparency is adequate but not thorough.

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, target, and return contents with no filler. Every phrase 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?

For a two-parameter read tool, the description covers the input concept (identifier-based resolution) and the output categories, which is sufficient for basic invocation. It omits edge-case behavior such as not-found responses or content size limits, but these are less critical given the simple, public, non-mutating nature implied.

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 documents identifier thoroughly and include_content not at all (50% coverage). The description adds a minimal link by calling content 'optional machine-readable content', which hints at include_content, but does not clarify what enabling it yields or when it is appropriate. It compensates only partially for the schema gap.

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 a specific verb ('Resolve') and resource ('one public realization/gallery post') and enumerates the returned payload (metadata, evidence, media links, optional content). The word 'one' sharply distinguishes it from the sibling get_realizations, and the title reinforces the singular scope.

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 the use case: you need details for a single realization/gallery post, as opposed to get_realizations which evidently lists them. It does not explicitly name alternatives or state when not to use it, but the singular scope and 'public' qualifier give the agent enough contextual signal to select it appropriately.

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. It adds useful behavioral boundaries: only published site content is searched, private customer records are not accessed, and certain pages are demoted/excluded. It does not address result ordering, pagination, side effects, or other behavioral details.

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 efficient sentences with the main purpose front-loaded, followed by exclusions and a privacy boundary. No filler or redundant restatement of the schema.

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?

This is a 12-parameter, zero-required search tool with no output schema and no annotations, so the description needs to explain more. It omits how filters combine, what the response contains, and practical implications of defaults. The description is too sparse for the tool's 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 only 50%, and the description adds little beyond 'by locality and/or topic.' It does not clarify the distinction between query, scope, and tag, nor does it explain year, area bounds, or limit semantics. The description fails to compensate for the many undocumented 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?

The description clearly states the action ('Search') and resource ('public Oleba project/gallery realization content') and adds exclusions for generic service, landing, and price-list pages. It is specific enough to distinguish from content-type siblings, but it never explicitly differentiates from get_realization or search_site.

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?

It gives clear context for what this tool searches and explicitly excludes certain page types, which implies when not to use it. However, it does not name alternative tools or provide explicit when-to-use/when-not-to-use guidance relative to 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?

With no annotations, the description carries the full burden of behavioral disclosure. It does meaningfully describe the resolution behavior and the returned sections (page, price rows, realizations), which is useful. But it does not disclose behavior for ambiguous or unknown names, how limits constrain results, or any failure modes.

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 front-loads the core action and every clause adds distinct information: input forms, the resolved resource, and the three output components. 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 is serviceable and names the return sections, which matters because there is no output schema. However, it omits the meaning of price_limit and realization_limit and provides no guidance for choosing this tool among many siblings, leaving it adequate but with clear gaps.

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?

Only two of the four parameters (location and identifier) are described in the schema, and the description does not compensate for the low 50% coverage. price_limit and realization_limit are never explained, and mentioning 'price rows' and 'related realizations' only loosely hints at their effect; the agent cannot infer defaults, units, or exact meaning.

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 verb ('Resolve') and resource ('service'), and specifies the two accepted input forms (stable id or natural-language name) plus the three output components (primary public page, structured price rows, related realizations). This makes it distinguishable from siblings like list_services, get_prices, and get_realizations.

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 use case: when a single service record with pricing and realizations is needed, and it makes clear that either an id or a natural-language name can be supplied. However, it never explicitly compares this tool to alternatives such as get_prices or get_realizations, nor states when to prefer the composite tool over the narrower ones.

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 of behavioral disclosure. The word 'public' hints that the operation is safe and unauthenticated, but the description does not explicitly state that it is read-only, has no side effects, or what response format to expect. It also doesn't mention any rate limits or data sensitivity. This is a significant gap for a tool with no annotation support.

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, compact sentence that front-loads the action and the three categories of output. Every word contributes meaningful information, with no fluff or redundancy. It is appropriately sized for a parameter-less 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?

Given the tool's simplicity (no parameters, no output schema), the description is largely complete. It explicitly lists the return categories: site identity, machine-readable endpoints, and MCP endpoint information. A minor omission is the lack of detail about the structure or format of the returned data, but for an overview tool this is acceptable. The absence of annotations is the main reason this isn't 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 has zero parameters, so the description has nothing to add about parameter meaning. The schema coverage is trivially 100%. Per the rubric, a zero-parameter tool earns a baseline of 4, and the description even enumerates what will be returned, which adds context without needing to discuss 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?

The description states a specific verb ('Return') and a well-defined resource ('public site identity, machine-readable endpoints and MCP endpoint information for ABC Remonty Oleba'). This clearly distinguishes it from sibling tools like get_content or get_prices, which target different resource types. An agent can immediately understand what this tool provides.

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 the tool should be used when the agent needs an overview of the site's identity and endpoints. However, it does not explicitly state when to use it over alternatives, nor does it note any exclusions or prerequisites. The purpose is clear enough that an agent can infer usage, but there is no direct guidance.

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. It adds useful behavioral context: the catalog is 'curated public', 'stable', and 'machine-readable', and objects are 'linked to canonical public content.' However, it does not disclose limit behavior, response shape, ordering, or whether the list is paginated.

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, well-structured sentence with no filler. The key terms are front-loaded, and every phrase ('curated public', 'stable machine-readable', 'linked to canonical public content') adds meaningful 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?

For a simple list tool with one optional parameter and no output schema, the description conveys the core purpose and object nature. But it omits useful operational details such as response format, ordering, pagination, or how the limit parameter affects results, leaving some gaps for the agent to infer.

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 should compensate for the limit parameter, but it makes no mention of it. The parameter name and schema constraints (default 20, max 20, min 1) make the meaning reasonably clear, but the description itself adds no parameter-level value.

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 verb ('Return') and resource ('curated public Oleba service catalog') and adds specificity with 'stable machine-readable service objects linked to canonical public content.' It is easy to distinguish from get_service as a catalog/list operation, though it does not explicitly name or contrast any sibling tool.

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 context is implied: an agent would use this when it needs the curated public service catalog as machine-readable objects. However, there is no explicit guidance on when to choose this over get_service, search_site, or ask_oleba, and no exclusions or alternatives are mentioned.

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 behavioral burden. It makes clear this is a read-only search operation, discloses the locality-aware relevance behavior, and lists the response contents. It does not mention rate limits or authentication, but nothing suggests 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?

A single sentence, front-loaded with the search action and target resource, with return values listed at the end. There is no filler or redundant repetition of schema 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?

For a simple search tool it covers the main scope and return items despite the absence of an output schema. However, with no annotations, limited parameter coverage, and no usage exclusions, an agent still has to infer some call decisions and sibling distinctions.

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 only 33%: only 'query' is explained, while limit and content_type have no descriptions. The tool description adds no parameter-level detail and does not compensate for the low 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?

States a specific action ('Search') on a specific resource ('published public WordPress pages/posts on oleba.pl') and lists what it returns. This clearly identifies it as the site-search tool and distinguishes it from the get_* siblings and ask_oleba.

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 intended use is implied by the search verb and the reference to published public content, but the description gives no explicit when-to-use versus when-not-to-use guidance and does not name alternatives. An agent must infer how this differs from get_content or ask_oleba.

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