suppscience

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 usefully reveals the returned content (compared options, verdicts, purchase links), but it does not explicitly state that the operation is read-only, what happens on an invalid slug, or any other behavioral traits. 'Get' implies retrieval but is not a strong disclosure.

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, well-structured sentence that front-loads the action and resource, then specifies the key return elements with zero redundancy. Every word 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 simple one-parameter retrieval tool with no output schema, the description covers the main action and return contents sufficiently. Minor gaps include lack of explicit usage guidance and error behavior, but these are not critical 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?

The input schema provides 100% coverage of the single parameter, including an example and a pointer to list_guides for finding slugs. The description adds no additional parameter semantics, so the baseline score of 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 states a specific verb ('Get'), a resource ('one comparison guide'), and a unique identifier ('by slug'), while listing what the response contains (compared options, per-option verdicts, purchase links). This clearly distinguishes it from sibling tools like list_guides or get_supplement.

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 rather than explicit: the slug parameter description says to find it via list_guides, but the tool description itself does not state when to choose this tool over alternatives or mention exclusions. There is no clear when-to-use/when-not-to-use 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 behavioral burden, and it does so well by enumerating the returned payload (per-claim grades, studied dose, safety, interactions, FAQ, PubMed references, buyUrl, pageUrl, translated fields). It does not state authorization needs or error behavior for unknown slugs, but the return-content disclosure is a genuine, non-trivial addition.

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 dense sentence with the verb and resource front-loaded, then a compact enumeration of the payload. No filler and 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 read-only detail tool with no output schema, the description enumerates the return fields adequately and points to search_supplements for slug discovery. Only edge behavior (unknown/invalid slug, localization fallback rules) is unaddressed, which is 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 description coverage is 100% and the single slug parameter is already documented with an example and a discovery hint in the schema. The description only restates "by slug," so it adds little beyond the schema — the 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 ("Get the full evidence analysis for one supplement") and constrains scope to a single item by slug. This clearly distinguishes it from search_supplements, which the description implies is the discovery path rather than the analysis source.

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 "by slug" and the schema's slug description routes the agent to search_supplements for discovery. However the description itself never explicitly says when to use this tool versus search_supplements or the guide tools, leaving the routing to inference.

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 clearly implies a read-only retrieval ('Get one training topic') and discloses the returned payload in detail, which is the main behavioral trait. However, it says nothing about failure behavior for an unknown slug, auth/prerequisite needs, or rate limits.

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?

Front-loaded with the verb and resource, then a single dense enumeration of the returned content. The long list is justified by a content-heavy response and no output schema, though the trailing translation note adds minor clutter.

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 necessary work of enumerating the response payload fields, and the sole required parameter is fully covered. It stops short of describing error behavior for a missing/invalid slug, which is the one real gap for a lookup 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 description coverage is 100% and the single 'slug' parameter is already documented in the schema, including the 'training-volume' example and the pointer to search_training. The description adds no syntax or format meaning beyond the schema, so the 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 ('Get one training topic by slug') and then enumerates the exact content domain (grades, sets/reps/rest, technique, cautions, FAQ, PubMed refs, related supplements, pageUrl), which cleanly separates it from the parallel get_guide/get_supplement fetchers. An agent can tell what uniquely comes back from this tool without opening the 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?

Usage is only implied: fetch by a known slug, with the 'find it via search_training' hint living in the schema rather than the description. There is no explicit when-to-use/when-not statement and no comparison against search_training or the sibling get_* 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 behavioral burden. 'List' implies a read-only operation, and the topic enumeration adds useful context, but it does not describe the return format, ordering, or whether each guide contains structured data or free text. For a simple listing tool this is adequate but not rich.

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 immediately states the action and resource, then uses a compact parenthetical and colon list to enumerate content. No filler or repetition; 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?

This is a simple, parameterless listing tool with no output schema, so the description covers the essential purpose and scope. It might have mentioned how results are presented (e.g., titles/IDs), but the low complexity means the current description is sufficient for correct invocation.

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?

There are zero parameters, so the description is not required to add parameter meaning. The description's list of guide topics effectively communicates what the result set contains, which is the only relevant semantic content for this tool.

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 ('List') and clearly identifies the resource ('comparison guides'), then enumerates the exact topics included. This distinguishes it from siblings like get_guide (which presumably returns one guide) and search_supplements (which searches supplements).

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 makes the use case evident: call this tool to see available comparison guides on specific supplement forms. It does not explicitly state when not to use it versus get_guide or search_supplements, but the enumeration of guide topics provides clear context for selection.

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 the catalog size, that results include slug, evidence grade, and summary, and that it is a search operation. However, it does not describe search matching semantics (e.g., partial or exact), result ordering, or pagination behavior beyond the schema's limit parameter, leaving some behavioral gaps.

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 compact sentences with no wasted words. The primary action and scope are front-loaded in the first sentence, and the second sentence adds a clear routing instruction to a sibling tool. Every sentence 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 simple search tool, this is nearly complete: all parameters are schema-documented, the returned fields are named, and the path to deeper detail via get_supplement is clear. The only minor omission is an explicit statement that results are returned as a list or array, but the field enumeration makes the response shape largely inferable.

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 already documents both parameters with 100% coverage, so the baseline is 3. The description adds meaningful context by specifying that 'query' can be a name, category, or topic, which clarifies what kinds of search terms are valid. The 'limit' parameter is not elaborated in the description, but the schema already explains its default and maximum.

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 ('Search'), a defined resource ('catalog of 993 evidence-graded supplements'), and the dimensions of search ('by name, category, or topic'). It also explicitly routes users needing full analyses to the sibling get_supplement, which cleanly distinguishes this tool from its siblings.

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 clear usage context: use this to search the catalog and get brief matches, and it explicitly points to get_supplement for the full analysis. It does not mention all sibling tools (get_guide, list_guides) or when to avoid this tool, but the alternative guidance it provides is concrete and sufficient for the primary decision.

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 the return fields (slug, type, grade, summary), which is genuinely useful behavior context, but it does not state that the operation is read-only, how result ranking/pagination behaves, or that missing topics return empty results. Adequate but with gaps for an unannotated tool.

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 compact sentences, zero filler, and the corpus scope is front-loaded before the return shape and the sibling reroute. Every clause 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 read-only search tool with no output schema, the description covers the corpus, the returned fields and the escalation path to get_training, which is enough to call it correctly. It stops short of describing ranking, result shape details, or behavior on no matches.

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%, with the type enum and limit bounds (default 10, max 25) already documented, so the baseline is 3. The description's topic examples loosely illustrate what the query and type parameters accept but add no format or matching semantics beyond 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?

States a specific verb+resource ('Search the evidence-graded training topics') and immediately scopes the corpus with concrete domain examples (variables, methods, exercises, weight-loss, myths). It also names the sibling get_training as the full-page alternative, so an agent can distinguish it from get_training 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?

The closing sentence 'Use get_training for the full page' gives an explicit alternative and the condition that selects it (summary vs full page). It lacks explicit when-not guidance (e.g., when to prefer search_supplements or list_guides instead), but the search/discover vs fetch split is clear.

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