OKC Disc & Sciatica Next-Step Checker | Precision Care Chiropractic

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

No annotations exist, so the description carries the full behavioral burden. It does disclose the key 'NON-DIAGNOSTIC' nature and enumerates red-flag symptoms, but it does not explain what happens when redFlags=true, what the returned suggestion looks like, or any limitations or safety disclaimers.

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 sentences with no filler. The primary purpose is front-loaded, and the critical red-flag instruction is placed immediately after. 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?

The core purpose and one critical parameter are covered, but with 7 parameters and no output schema, the description leaves the return format and downstream use of the suggestion unspecified. It also does not position the tool relative to its siblings, so an agent gets limited workflow context.

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 100%, which sets a baseline of 3. The description adds value by specifying exactly which symptoms should trigger redFlags=true, going beyond the schema's generic 'urgent red-flag symptom' wording. Other parameters receive no additional elaboration, but the redFlags detail meaningfully improves invocation correctness.

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'), a clear resource ('next-step suggestion'), and a precise scope ('lower back / sciatica / disc symptoms'). It also distinguishes this tool from the sibling education/article tools by emphasizing a non-diagnostic, action-oriented output.

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 redFlags instruction gives clear situational guidance for setting that parameter, but the description does not explicitly state when to prefer this tool over siblings like run_sciatica_information_check or get_education_article. Usage context is implied by the tool's name and scope rather than spelled out.

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 disclosure burden. 'Get' clearly indicates a read-only operation and enumerates the payload contents. It omits details like whether an external request is made or any formatting caveats, but for a simple, zero-parameter restful getter this is sufficient transparency.

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 sentence that front-loads the verb and resource, then lists the three outcome categories with no filler. 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 zero-parameter tool with no output schema, the description identifies the key return categories (contact details, services, checker URL) and the clinic. The only small gap is that 'checker URL' and 'contact details' are not expanded with specific examples, but the high-level scope is clear enough for the intended use.

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 no parameters and the schema is an empty object, so the description has no parameter meanings to explain. Per the baseline rule for zero-parameter tools, a score of 4 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 uses a specific verb ('Get') and names a concrete resource ('Precision Care Chiropractic') plus the exact data types returned ('contact details, services, and the checker URL'). This makes the tool's purpose unmistakable and clearly distinct from sibling tools focused on education articles and patient assessment.

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 should call this when clinic contact details, services, or the checker URL are needed. However, there is no explicit guidance on when not to use it or which sibling tool to choose instead, though the zero-parameter, zero-output design makes misuse less likely.

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 indicates a read operation returning plain-text content, but it does not mention error behavior, permissions, or what happens if the slug does not exist. This is acceptable but not deeply transparent.

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 clean, front-loaded sentence that contains all essential information. There is no filler, and the key action and resource are stated immediately.

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 single-parameter retrieval tool with no output schema, and the description adequately explains what is returned ('full plain-text content') and how the article is identified ('by slug'). It could mention not-found behavior, but for this simple tool the definition is largely 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 schema already documents the single 'slug' parameter with 100% coverage, so the baseline is 3. The description adds that the slug identifies a single article and that content is returned, but it does not provide additional format details or constraints 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?

The description uses a specific verb ('Get') with a concrete resource ('single Education Center article') and a clear identifier ('slug'). It also specifies the output format ('full plain-text content'), which clearly distinguishes it from list/search sibling 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?

The phrase 'by slug' implies this should be used when the agent already knows the article slug, but the description does not explicitly mention when to use this instead of list_education_articles or search_education_articles. No alternatives or exclusions are named.

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 behavioral burden. It clearly communicates a read-only listing operation and the response contents (titles, categories, URLs). It does not mention ordering, pagination, or errors, but for a zero-parameter list operation the core behavior is adequately disclosed.

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 with no redundancy or filler. The action, target, and output fields are all front-loaded, and every word contributes to 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 simple, no-parameter list tool without an output schema, the description adequately specifies what is returned. The main missing context is when to choose this over the search/get siblings, but that is primarily a usage-guideline gap; the tool's own scope is described well.

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 there is no parameter semantics to document. The description correctly avoids inventing parameters, and the empty schema already fully defines the calling contract.

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'), names the resource ('Education Center articles'), and specifies the returned attributes ('titles, categories, and URLs'). The word 'all' distinguishes this from the 'search' and 'get' sibling tools, making the tool's role unmistakable.

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?

No explicit guidance is given about when to use this tool versus search_education_articles or get_education_article. The word 'all' implies broad listing is intended, but the description never states alternatives or conditions, so an agent has no direct decision 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 provided, the description carries the full burden, and it does well: it prominently discloses the educational-only nature, states that it screens for urgent red-flag signs, and explains that redFlags=true forces urgent-care routing. It does not delve into every behavioral consequence, but the key safety-related behavior is transparently communicated.

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 three tightly written sentences with no wasted words: a safety disclaimer, a clear summary of what the tool does, and a targeted instruction for the most important parameter. It is front-loaded and 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 7-parameter optional-input tool with no output schema and no annotations, the description covers the essential context: purpose, scope, safety caveat, red-flag behavior, and output type. It could be slightly more complete by describing what the generated 'information brief' contains or how non-red-flag cases are routed, but overall it 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?

Schema description coverage is 100%, so the schema already documents all seven parameters in detail. The description adds useful emphasis on redFlags behavior, but that meaning largely duplicates the schema's own description of redFlags. No significant additional parameter semantics are provided 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?

The description clearly states the tool's specific function: it organizes lower-back and leg symptoms, screens for red-flag warning signs, and returns a plain-language next-step information brief for an Oklahoma City patient. It is more specific than a tautology and clearly distinct from generic education-article tools, though it does not explicitly name or differentiate itself from siblings like assess_next_step.

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 context for use: it is for reported lower-back and leg symptoms and for an Oklahoma City patient. It also provides an explicit conditional usage instruction for redFlags=true to force urgent-care routing. It does not explicitly state when not to use the tool or name alternative sibling tools, but the intended trigger context is reasonably clear.

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 disclosing behavioral traits. It only says 'Search... by keyword or question' and does not mention whether results are filtered, ranked, paginated, limited in count, or what kind of matches are returned. The absence of any search behavior details is a notable gap.

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, short sentence with no filler words. It is concise and front-loads the core action and resource. It earns full structure credit but loses a point because the sentence is too sparse to carry richer behavioral guidance.

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 one parameter, full schema coverage, and a simple resource, the description is minimally adequate for a search operation. However, there is no output schema and no annotation safety context, and the description does not hint at result format or scope, so an agent is left guessing what a successful call returns.

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 single 'query' parameter is already documented in the schema. The description adds the notion that the query can be a keyword or a question, which is a small enhancement over the plain schema text. This matches the baseline-3 expectation for full 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?

The description states a specific verb ('Search') and resource ('Education Center articles'), and indicates the search is by keyword or question. It does not explicitly contrast with siblings like get_education_article or list_education_articles, but the action is clear enough to distinguish a search operation from retrieval or listing.

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 used when the agent needs to search articles rather than fetch one directly. However, it does not state when to prefer search_education_articles over get_education_article or list_education_articles, leaving the routing decision partly to inference.

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