DataCrate360 Guides & Fixes

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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description adds real value beyond them by disclosing the returned content sections (symptoms, cause, solution, how to confirm), which is important since 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?

A single front-loaded sentence with zero filler; the parenthetical enumerating returned fields does useful work rather than padding.

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 read-only single-record lookup with annotations covering safety, the description supplies the missing return-content detail in place of an output schema. Only edge behavior (error on unknown slug) is left unstated, a minor gap.

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% — the 'slug' property has no schema description at all. The description compensates by explaining what the slug identifies and where it originates (search_fixes), which is more than the bare `string` type conveys.

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 (read the full text of one Guides & Fixes entry) and scopes it to a single record, explicitly noting the slug comes from search_fixes. That naming of the sibling cleanly separates it from search_fixes without opening either schema.

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?

'by slug from search_fixes' establishes the prerequisite workflow: search first, then read by slug. It gives clear usage context but offers no explicit when-not-to-use or fallback behavior (e.g., invalid/unknown slug).

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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds the useful constraint that only 'published' posts are readable and that the full text (not a summary) is returned, but says nothing about auth, rate limits, or behavior on a missing/unpublished post_id.

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; the resource is named first and the parameter's provenance second.

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 no output schema, the description adequately covers what is returned and where the ID comes from, and annotations cover safety. It would be slightly better with a note on unpublished/invalid post_id behavior.

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% and the schema only declares post_id as a string, so the description carries the burden. It does add meaningful semantics by specifying where post_id comes from (search_posts) and that it must denote one published post, but gives no format or example.

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+resource: returns the full text of one published community post. It implicitly distinguishes from search_posts by naming it as the source of post_id, but never explicitly frames search_posts as the alternative for finding posts.

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?

'by post_id from search_posts' tells the agent this tool is invoked downstream of search_posts, giving clear usage context. It stops short of explicit when-not guidance (e.g., that it cannot retrieve drafts or multiple posts).

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, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered without the description. The only extra information offered is 'with links', which lightly hints at the response payload, but nothing is said about result volume, ordering, pagination, or whether this is an exhaustive catalogue.

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?

It is a single short fragment with no waste, so length is fine, but it is under-specified rather than well-structured — there is no leading verb to anchor the reader and no secondary sentence adding the context the fragment omits.

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 no-parameter, read-only listing tool with no output schema, the description should at least characterize what comes back; 'with links' gestures at that. However, it never states that this returns a catalogue of labs, how many, or in what form, so an agent has only a rough idea of the payload.

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 and the schema is empty with additionalProperties=false, so there is nothing for the description to document. Per the zero-parameter baseline, a 4 is appropriate; no parameter detail is missing or misstated.

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 fragment 'Hands-on DataCrate360 labs to practise a skill, with links' conveys the resource (labs) and a hint about content (hands-on, with links), but it is a noun phrase with no verb, so it never says what the tool actually does to the labs — list, browse, retrieve. Siblings (get_fix, list_tools, search_fixes) are in unrelated domains, so differentiation is easy by default, but the purpose itself stays vague.

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 when-to-use guidance, no statement of prerequisites, and no mention of alternatives or when-not to call it. The phrase 'to practise a skill' hints at an intent but does not tell the agent under what circumstances to select this tool.

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, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description adds the output context that results include counts, but says nothing about pagination, rate limits, or ordering, so the added behavioral value is modest.

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 fragment with no wasted words. It is highly concise, though its fragmentary nature slightly limits clarity compared to a complete sentence.

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 list tool with read-only annotations and no output schema, the description gives enough to understand the returned set and that counts are included. Minor details like sorting or pagination behavior could be added, but the core context is present.

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 there are no parameter semantics to document. Schema coverage is 100% and the baseline for zero-parameter tools is 4.

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 identifies the resource (tools) and scope (those that have published Guides & Fixes, with counts), making the tool's result fairly clear. It lacks an explicit verb like 'list' and does not differentiate itself from siblings such as search_fixes or list_labs, but the domain is still evident.

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 guidance on when to use this tool versus alternatives, nor any conditions or exclusions. The description only states what the tool returns, leaving the agent to infer its use case.

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, non-destructive, closed-world). The description adds real value beyond them: it confirms the corpus is DataCrate360's *published* content (consistent with openWorldHint=false) and imposes an attribution behavior (cite the returned URL). It stops short of describing result shape, ranking, or pagination.

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, zero filler. Scope, input method, and the citation requirement are each front-loaded in the order an agent needs them.

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 read-only search with no output schema, the description covers purpose, inputs, and the one downstream obligation (cite URLs). The only shortfall is that it doesn't characterize the result set or how many entries come back, which matters slightly given the undocumented limit.

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%: q and tool are documented, but kind and limit are not. The description reinforces q ("paste an error message") but says nothing about what distinguishes kind=fix from kind=guide or how limit behaves, so the gap on half the parameters is only partly offset.

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 (Search) and a precisely scoped resource (DataCrate360's published Guides & Fixes), and even names the domain of tools covered (Snowflake, dbt, Airflow, Spark). It is distinguishable from get_fix by the search-vs-retrieve distinction, though it never explicitly says so.

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?

"Paste an error message or describe the problem" gives concrete input guidance, which implies this is the entry point before get_fix. However, it never states when to prefer this over get_fix or the list_* siblings, and offers no exclusions or prerequisites.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds some value beyond that by scoping to 'published' posts and instructing the agent to cite the returned URL, which hints at the response shape. It still says nothing about result ranking, pagination, or how the limit cap behaves.

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 short, front-loaded sentences with no filler; the search scope comes first and the citation instruction second. Slightly terse, but every clause 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 two-parameter search tool with no output schema and full annotation coverage, the description covers the essentials plus the URL-citation convention. It stops short of describing what a result contains (fields, ranking, whether the limit is a hard cap at 10) or what happens on an empty query, leaving minor 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?

Schema description coverage is 50%: 'q' is documented as 'Keywords' and the description reinforces this with 'by data people (keywords)'. The 'limit' parameter carries only min/max constraints in the schema and is never mentioned in the description, so the description does not compensate for the coverage gap but also does not mislead.

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 ('Search') and a specific resource ('published DataCrate360 community posts'), narrowing scope with 'published' and 'by data people'. It doesn't explicitly differentiate from siblings like get_post or search_fixes, but the verb/data-domain combination is clear enough for an agent to distinguish it from single-item retrieval 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 implied rather than stated: an agent can infer this is the keyword-search entry point versus get_post for a known item. There is no explicit when-to-use/when-not guidance and no mention of the sibling search_fixes as an alternative for a different content type.

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