Home Renovation Free Tools

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

Annotations already declare readOnlyHint/idempotentHint/non-destructive, so the safety profile is covered. The description adds the meaningful extra: with no output schema, it discloses what the response contains (bilingual links, descriptions, ratings with source and date), so the agent knows what a full-detail fetch returns.

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 with the lookup key stated first, followed by the payload enumeration. Nothing is padded, and the field list earns its place given there is no output 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?

For a one-parameter read tool with full schema coverage and no output schema, the description supplies exactly the missing piece: what the returned record includes. Nothing an agent needs to invoke and interpret it is 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?

Only one parameter and schema description coverage is 100%, so the schema already explains the id and even gives an example. The description's phrase 'by id' adds no syntax or format meaning beyond that; baseline 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?

States a specific verb and resource with a precise lookup key: 'All details of one tool by id'. It even enumerates the payload (EN/PL links, app store links, bilingual descriptions, ratings with source and date), which clearly separates it from siblings search_tools and list_categories, which only enumerate or find 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?

Usage is only implied: the schema note 'Tool id from search_tools' hints at the search-then-fetch workflow, but the description itself never says when to call this versus the siblings or what happens for an unknown id. Context is inferable, not 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?

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is fully covered. The description usefully adds the shape of the result (category, description, tool count), but says nothing about pagination, ordering, or how many categories come back.

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 with no filler; every clause (what is listed, what is returned) carries 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 zero-parameter, read-only listing tool with complete annotations and no output schema, the description adequately covers both purpose and return contents. Minor missing detail on result volume/ordering keeps it from being fully 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 takes zero parameters, so the baseline is 4; there is nothing for the description to disambiguate. It does not need to compensate for any 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?

States a specific verb ('List') and resource ('categories') plus the payload the agent gets back (description and tool count per category). It is clearly distinguishable from get_tool and search_tools in intent, though it does not name those siblings 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: an agent can infer this is the entry-point browsing tool versus get_tool/search_tools, but the description never states when to prefer it or what it should not be used for. No exclusions or alternatives are given.

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 cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description still adds real context: accepted query languages, the provenance of `rating` (App Store/SourceForge with review count), the meaning of maintainer_tool, and the semantics of an empty result set.

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 core purpose is front-loaded in the opening clause, and the parenthetical enumerations are dense but each item earns its place by telling the agent what content is indexed. The long material-tool list is the only mildly expensive section.

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?

There is no output schema, so the description must carry return-value context, and it partially does by explaining the rating and maintainer_tool fields and the empty-result case. It stops short of describing the full result shape (title/link/category fields), which an agent would otherwise have to discover by calling.

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 all five parameters are already documented, which sets the baseline at 3. The description adds only marginal parameter-level meaning — bilingual query acceptance and the source of the rating used by min_rating — but nothing about limit, category, or interaction between filters.

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 ('Find') and resource ('free home renovation tools for a task') and then enumerates the concrete content classes returned (calculators, templates, planners, directories, apps, forums). This makes it trivially distinguishable from get_tool (fetch one) and list_categories (enumerate taxonomy).

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 query-oriented framing ('Find ... for a task'), and the note that an empty result means nothing in the list fits usefully sets expectations. However, it never states when to prefer this over get_tool or list_categories, nor any prerequisite steps, so routing guidance is left to inference.

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