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

With no annotations, the description carries the behavioral disclosure burden. It adds important non-obvious facts: it never returns token values, access tokens refresh automatically, and an expired access token with a stored refresh token still counts as a working session. This is strong for a zero-parameter status tool, though it does not explicitly state side-effect-free 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 with no fluff. The core purpose is front-loaded, and the critical security and refresh behavior follow in a compact paragraph.

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 status check with an output schema present, the description is complete. It tells the agent what the tool reports, what it will never return, and how to interpret an expired access token, leaving no missing information needed to call 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?

There are zero parameters, so the baseline is 4 and no parameter explanation is needed. The description appropriately focuses on the output semantics instead of inventing parameter-level details.

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 ('Report') and resource ('Oura session'), and precisely names the three things an agent learns: whether a session is stored, which scopes it has, and when it expires. This clearly differentiates it from data-fetching siblings and setup_authentication.

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: this is the tool for inspecting the stored auth session, its scopes, and expiration. It does not explicitly name alternatives or say 'use before calling data endpoints,' but the use case is unambiguous from the first sentence.

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 behavioral disclosure burden. It lists return fields but does not mention pagination/truncation behavior, timezone handling, authentication requirements, or any other operational traits. As a read-only getter, the lack of side-effect warnings is less critical, but the description still leaves behavioral details to the schema.

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 dense sentence with no filler or repetition. It front-loads the tool's purpose and then efficiently lists the returned metrics, making it easy to scan.

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 that an output schema exists and all parameters are fully documented in the input schema, the description is largely complete for a simple read-only getter. It clearly states what data is returned, though it could add a note about pagination or authentication prerequisites.

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 fully documents all four parameters, including defaults and the purpose of include_time_series. The description adds no parameter-level meaning, so the baseline 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 uses a specific verb and resource ('Get daily activity') and enumerates the exact metrics returned (activity score, steps, calories, distance, activity times, MET minutes, inactivity alerts). This clearly distinguishes it from sibling tools focused on sleep, stress, readiness, or workouts.

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 retrieving daily activity metrics, but it does not explicitly state when to use it over alternatives like get_daily_summary or get_workouts, nor does it mention any 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not mention that this is a read-only operation, nor does it hint at pagination via the next_token parameter, rate limits, or authentication needs. The description focuses solely on the meaning of the metric, leaving the agent to infer operational behavior from the tool name and schema.

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, tight sentence that leads with the action and resource, then provides essential context. There is no filler or redundancy, making it efficiently scannable for an agent.

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 that the tool is a simple query with optional parameters and an output schema exists, the description covers the core purpose and meaning of the data. It does not explain return structure, but that is handled by the output schema. The only gap is the absence of usage guidance, which is penalized separately; for the data itself, the description is sufficient.

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 all three parameters (start_date, end_date, next_token) fully documented in the schema. The description adds no additional parameter-level detail or context beyond what the schema already provides. Baseline of 3 is appropriate given the schema's thoroughness.

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 'Get' with a specific resource 'cardiovascular age' and explains it as Oura's estimate of vascular age from pulse wave velocity. This distinguishes it from the many sibling daily-metric tools like get_daily_activity or get_daily_stress, leaving no ambiguity about what this tool retrieves.

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 provides no guidance on when to use this tool versus alternatives. There is no mention of conditions, prerequisites, or scenarios that would favor this tool over the similarly named get_daily_* siblings. The only hint is the phrase 'to compare against actual age,' which suggests a purpose but does not offer explicit selection criteria.

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 bears the full burden. It discloses that the tool returns a score and contributors, and a deviation in degrees Celsius, which is useful. However, it omits any mention of authentication requirements, rate limits, pagination behavior (even though the schema has next_token), or that it is a read-only operation. The description provides some behavioral context but not comprehensive 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, information-dense sentence that front-loads the primary purpose (daily readiness scores) and follows with a concise enumeration of contributors and the deviation measure. It avoids redundancy and fluff, making it efficient and well-structured.

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?

An output schema exists, reducing the need to detail return structures. The description covers the score range and units, and the schema covers parameter details and pagination through next_token. The main missing context is a note about data availability or the expected multi-day nature implied by date range, but given the output schema and parameter descriptions, the description is sufficiently complete for an agent to call the tool 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 100%, with each parameter (end_date, next_token, start_date) already documented with defaults and explanations. The tool description adds no additional parameter semantics, such as date range behavior or token usage, so it provides no value beyond what the schema already offers. Baseline of 3 applies due to high 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 clearly states the tool retrieves daily readiness scores (0-100) and lists the contributors and body temperature deviation, making the function and output unambiguous. It is distinct from other daily metrics like cardiovascular age or stress, so a agent can immediately understand what this tool offers.

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 provides no guidance on when to use this tool compared to the many sibling daily-metric tools (e.g., get_daily_activity, get_daily_stress). It does not mention prerequisites, exclusions, or alternatives, leaving the agent to infer the appropriate context without explicit direction.

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 must carry the behavioral disclosure. It explains the output semantics (level and component values) but does not mention that data is returned for a date range, uses pagination (next_token), or that it is read-only. The schema covers defaults and pagination, but the description could be more explicit about the scope and any side effects. Overall, it provides some behavioral insight but not comprehensive.

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 is front-loaded with the main action ('Get daily resilience') and immediately provides the core semantics (definition, levels, components). Every phrase adds value, with no filler or repetition.

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 that an output schema exists (which would detail the return structure) and parameter descriptions are fully documented in the schema, the description covers the essential purpose and output semantics. There is nothing an agent needs to call this tool correctly that is missing—pagination and date defaults are in the schema, and the description clarifies what 'resilience' means in this 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 description coverage is 100%, with each parameter (start_date, end_date, next_token) already described in the schema. The tool description does not add any additional parameter-specific meaning beyond what the schema already provides, so it meets the baseline without exceeding it.

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') and resource ('daily resilience'), and defines what resilience means in this context ('ability to withstand and recover from physiological stress'). It enumerates the output levels (limited, adequate, solid, strong, exceptional) and components (sleep recovery, daytime recovery, stress contributors), clearly distinguishing it from sibling tools like get_daily_stress or get_daily_sleep.

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 usage when a user needs resilience data, and the definition of resilience makes it clear this differs from other daily metrics. However, it does not explicitly mention when not to use this or point to alternatives; the context is clear but no exclusions or sibling comparisons are provided.

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 correctly implies a read operation ('Get') but does not disclose pagination behavior (despite the next_token parameter) or authentication requirements. It also doesn't mention any rate limits or data freshness. While the safety profile is obvious (read-only), additional behavioral context would be valuable for an agent.

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 zero filler. The first sentence defines the tool's output and scope, and the second provides a clear routing to the sibling. It is perfectly front-loaded and efficient.

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 getter with 3 optional parameters and an output schema, the description covers the core purpose and routing. It could mention that results may be paginated (implied by next_token) and that the data is read-only (implied by 'get'), but these are minor gaps. The description is sufficient for an agent to call it correctly in most cases.

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 each parameter (end_date, start_date, next_token) already documented with defaults and formats. The tool description adds no extra parameter meaning, which is acceptable since the schema is comprehensive. The baseline of 3 applies because the schema carries the load.

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 gets daily sleep scores (0-100) and lists all contributors (deep sleep, efficiency, latency, REM sleep, restfulness, timing, total sleep). It explicitly differentiates from the sibling tool get_sleep_periods by naming it and specifying what that tool covers. This makes the purpose unambiguous.

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 explicitly states when to use an alternative: 'For durations, stages, heart rate and HRV use get_sleep_periods.' This is a clear when-not condition and names the specific sibling tool, leaving no ambiguity about which tool to choose for different needs.

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 disclosing behavior. It states the two metrics returned but does not mention pagination (despite a next_token parameter), potential latency, or any constraints beyond the ring requirement. It doesn't clarify that this is a read-only operation, though that is implied.

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, front-loads the core purpose, and adds a crucial requirement (Gen 3+ ring) without any waste. Every word contributes.

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 that an output schema exists, the description doesn't need to explain return values. It provides the essential purpose, a hardware requirement, and the temporal context ('during sleep'). It lacks mention of pagination or date range defaults, but those are covered by parameter descriptions. Overall, it's sufficient for an agent to decide when to call it.

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 each parameter already has a clear description (date range and pagination). The tool description adds no additional meaning beyond the schema, so a baseline 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 clearly states the tool retrieves average blood oxygen saturation (SpO2 %) during sleep and the breathing disturbance index. It uses a specific verb ('Get') and names the exact resource, making it distinct from other get_daily_* 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 description mentions a hardware prerequisite ('Requires a Gen 3 or later ring') but gives no guidance on when to use this tool versus alternatives like get_daily_sleep or get_heart_rate. There is no mention of when not to use it or which sibling to choose instead.

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 burden of explaining behavior. It discloses the output granularity (per day), the units (seconds), and the summary categories, which goes beyond the tool name. It does not mention pagination or read-only nature, but 'Get' implies a read operation and the schema covers pagination via next_token.

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 core purpose and then adds essential detail about the output. 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?

Given the output schema exists and the parameter schema is fully documented, the description is largely complete. It could clarify what 'daytime' means or how the summary categories are derived, but the combination of description and schema gives an agent enough to call the tool 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 100%, so the schema fully documents start_date, end_date, and next_token. The description adds no parameter-specific detail, but none is needed because the schema descriptions already explain defaults and pagination behavior.

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 resource ('daytime stress'), and enumerates the exact metrics returned: seconds in high stress, seconds in high recovery, and a day summary of restored, normal, or stressful. This clearly distinguishes it from sibling tools like get_daily_summary or get_daily_readiness.

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 tool's context clear: use it when you need daily daytime stress and recovery metrics. It does not explicitly name alternatives or exclusion criteria, but the specificity of the resource makes the intended use obvious among the 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 behavioral disclosure burden. It usefully discloses that durations are in seconds and that unavailable collections appear as 'unavailable' while other data is still returned. However, it does not mention auth requirements, read-only safety, or any other side-effect/availability caveats, leaving some 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?

The description is compact and front-loaded with the core purpose. The metric list is long but necessary for a summary tool, and the second sentence adds usage guidance plus an important edge-case behavior without repetition.

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 aggregates many metrics and already has an output schema, the description covers the essential context: cardinality (one record per day), included metrics, duration units, and partial-data behavior. It could mention authentication or fallback behavior, but it is largely complete for an agent to call this 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 100%: both start_date and end_date already have clear explanations of format and defaults. The description does not add parameter-specific semantics beyond the schema, 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 opens with a specific verb and resource: 'Get one record per day combining the headline numbers'. It enumerates the included metrics, distinguishing this aggregated summary from the many sibling daily-getter tools without needing to open any 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 phrase 'The best starting point for questions like "how have I been sleeping" or "how was my week"' gives clear contextual guidance for when to prefer this tool. It does not explicitly name alternative tools or state when not to use it, so it stops short of a full when/when-not explanation.

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 burden. It discloses that the tool returns every field including embedded time series, which is useful, and it implies the document comes from a list result. However, it does not mention authentication requirements, error behavior, or the full response structure (though an output schema exists). For a simple read operation, 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?

The description is two sentences, front-loaded with the primary action and scope, followed by a usage hint. Every word earns its place; there is no filler or repetition of schema details. It is concise and well-structured.

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 has only 2 required parameters, a complete enum, and an output schema, the description is fairly complete. It tells the agent when to use it (drilling into a single item from a list) and what to expect (full fields with time series). It doesn't mention error handling or authentication, but these are not critical for a simple getter and are partially covered by the output schema. It is slightly above average in completeness.

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%: both 'data_type' and 'document_id' have descriptions. The description adds the clarification that 'document_id' comes from a list result, but the schema already states that ('The document's 'id' field from a list result'). Thus the description adds minimal value beyond the schema, consistent with the baseline of 3 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 uses a specific verb ('Get') with a clear resource ('one Oura document by id') and explicitly mentions that it includes every field with embedded time series. It also distinguishes itself from sibling list/getter tools by stating its role: drilling into a single sleep period, workout, or session from a list result. This fully clarifies what the tool does.

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 provides clear context: it is meant to drill into a single item after obtaining a list result from sibling tools. It does not explicitly name alternatives or state when not to use it, but the intended workflow is implicit and actionable. It gives enough guidance to select this tool over the many sibling getters.

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 does not disclose that the tool is read-only, that results may be paginated (next_token), or how errors are handled. It only states what data is returned, leaving behavioral traits undisclosed.

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 concise sentences with no filler. The first sentence front-loads the action and resource, and the second adds a useful use case. It is appropriately sized, though the second sentence is not strictly necessary for invocation.

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 a full input schema and an output schema present, the description plus schema give an agent sufficient information to call the tool. It could mention pagination or read-only status, but those are either covered by the schema or implied by the action. A 4 reflects that the description is adequate given the structured 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 description coverage is 100%, and the schema already documents each parameter (start_date, end_date, next_token) with defaults and pagination semantics. The description adds no parameter-level meaning beyond that, so baseline 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?

States a specific verb ('Get') and resource ('tags the user logged in the Oura app') with concrete tag examples and returned data (start/end times, comments). No sibling tool appears to handle tags, so it is clearly distinct.

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?

Provides an implied use case ('Useful for explaining changes in sleep or readiness') but does not explicitly contrast with sibling tools or state when not to use it. No alternatives 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?

With no annotations, the description carries the full burden. It discloses the sampling interval and default window, but does not mention pagination via next_token, aggregation recommendations, error behavior, or any edge cases. The schema covers some of this, but the description itself is thin on behavioral 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?

A single, front-loaded sentence with no fluff. It immediately states the purpose, data details, and default behavior, making it efficient and easy to parse.

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 existence of an output schema and complete parameter descriptions, the description is adequate for a simple read operation. However, it lacks usage guidance and behavioral context that could help an agent decide when to use this tool or handle large result sets. It is not incomplete but not comprehensive either.

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% with descriptive parameter definitions. The tool description adds minimal value beyond schema—it mentions the default window and data characteristics but does not clarify parameter usage beyond what is already in the schema. Baseline 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 clearly states the tool retrieves heart rate samples in bpm at 5-minute intervals, tagged with source types, and mentions the default window. It is specific and distinct from other health-related siblings, though it does not explicitly contrast with alternatives.

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 guidance is provided on when to use this tool versus alternatives, nor are there exclusions or context about when to prefer aggregate vs raw data. The description only mentions defaults, which is not usage direction.

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. It discloses that fields without granted scopes return null, which is critical for the agent to set expectations. It also implies a read-only nature ('Get') and requires authentication implicitly via 'signed in user'. It does not mention side effects, but the null behavior is the key transparency point and is covered.

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 concise sentences with zero redundancy. The first sentence states the purpose and fields; the second explains the null behavior. 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 zero-parameter tool with an output schema, the description is complete. It lists all returned fields and explains null behavior, which is the only nuance an agent needs. The output schema presumably defines the exact format, so no further explanation is required.

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 does not need to explain them. It does add context about the returned fields, which is helpful even though it's output-related. The baseline for zero-parameter tools is 4, and the description meets that.

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?

Clearly states it gets the signed-in user's profile and enumerates the specific fields (age, weight, height, biological sex, email). This distinguishes it from sibling tools that retrieve activity, sleep, or auth data. The verb 'Get' and resource 'profile' are specific and unambiguous.

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 context clear (profile data for the signed-in user), which implicitly tells the agent when to use it. However, it does not explicitly state when not to use it or name alternatives, though the specificity of the fields makes the use case obvious. Slight lack of explicit exclusions.

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 for behavioral disclosure. 'Get' implies a read operation, but the description does not state that it is read-only, does not mention authentication requirements, pagination behavior, or rate limits, and offers no detail beyond the returned data.

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 sentence that clearly identifies the tool's purpose and output. It contains no unnecessary repetition or fluff, though some additional usage guidance could have been included without harming conciseness.

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 tool has a simple schema with fully documented optional parameters and an output schema, so the description is minimally sufficient for invocation. However, the lack of annotations and absence of any behavioral context (auth, read-only confirmation, pagination) leaves the description slightly incomplete for a fully informed 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 description coverage is 100%, so the input schema fully documents start_date, end_date, and next_token. The description adds no parameter-specific detail beyond the schema, 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 and resource ('Get rest mode periods') and indicates what is returned (start/end times and logged episodes). It does not explicitly differentiate from siblings like get_sleep_periods, but the resource is distinct enough for an agent to understand the tool's purpose.

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 mentions rest mode is typically used for illness or recovery, but it provides no guidance on when to choose this tool over siblings like get_sleep_periods or get_sessions. There is no explicit context for selection or exclusion of 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 carries the burden of behavioral disclosure. It does add useful behavior beyond the schema by mentioning charging state and the default-vs-window behavior, but it omits details like pagination behavior and time-window defaults, which are only covered by the schema.

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 concise sentences with no filler. The core purpose is front-loaded and the parameter guidance is compact and actionable.

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 plus the fully documented schema and output schema provide enough information for an agent to call this tool correctly. Minor gaps such as pagination and date defaults are already covered by parameter descriptions, so nothing critical is missing.

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 four parameters. The description adds context about the latest flag's effect, but does not materially enhance the meaning of the other parameters beyond what the schema provides.

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 identifies the resource (ring battery level) and the specific data returned (percentage and charging state). It is distinct from all sibling tools, which target different health metrics or configuration data.

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 explains the default behavior (latest reading) and how to change it (set latest to false for a window), giving clear operational guidance. It does not explicitly contrast with sibling tools, but the resource is unique enough that no alternative is needed.

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-only operation via 'Get' and lists returned fields, which is adequate for a simple getter. However, it does not disclose authentication requirements, potential absence of rings, or any other behavioral nuances that an agent might need to anticipate.

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 concise sentence that front-loads the action and resource, then lists the relevant data fields. Every word earns its place; there is 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 no-argument getter with an output schema, the description is largely complete: it states the purpose and the data fields returned. The main gap is the absence of any note about authentication or the behavior when no ring exists, but the output schema likely covers return structure and the tool is simple enough to call 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?

The tool has zero parameters, so the baseline is 4. The description adds meaning by listing the data fields the tool returns, which helps an agent understand the result even though no parameter documentation is needed.

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 clear resource ('the user's ring(s)') and enumerates the exact data fields returned: hardware generation, color, design, size, firmware, and setup date. This distinguishes it from all sibling tools, none of which target ring configuration.

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 usage when ring configuration is needed, but it provides no explicit when-to-use or when-not-to-use guidance, nor does it name alternatives. There are no closely related siblings, so the lack of alternatives is less critical, but the guidance is still only implicit.

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 exist, so the description carries the burden. It discloses the kind of data returned and that include_time_series pulls in heart rate, HRV, and motion, but it does not mention authentication, pagination/truncation, response size effects, or lack of side effects. These are meaningful gaps for a no-annotation 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 efficient sentences: the first establishes purpose and scope, the second highlights the one parameter worth calling out. No filler or repetition.

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 a rich input schema and an output schema present, the description covers the core semantics adequately: what a session is, what fields are returned, and the optional time series. It is slightly short on operational context like auth requirements and when to choose this over related tools, but those are secondary given the schema and sibling 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 description coverage is 100%, so the baseline applies; the schema already documents date formats, defaults, and next_token semantics. The description adds only a light reference to include_time_series and does not improve on the schema's parameter explanations.

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 verb and resource: 'Get guided and unguided sessions from the Oura app', and names concrete session kinds (breathing, meditation, rest) plus fields returned. This makes it easy to distinguish from sibling tools like get_workouts and get_sleep_periods.

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 naming the Oura session resource, and the second sentence gives an optional-parameter instruction, but there is no explicit when-to-use guidance or comparison to sibling alternatives such as get_workouts. The agent must infer which tool fits.

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, and it does disclose the returned fields and period-type taxonomy. It does not mention pagination/truncation, response size, or timezone/date-boundary behavior, even though the next_token parameter implies large results may be cut off.

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 front-loaded with the concrete purpose and then gives a useful, finite list of returned metrics. The period-type explanation earns its place, though the metric list is slightly dense and could be tightened without losing 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 read tool with a rich output schema and fully documented parameters, the core behavior is sufficiently described. The main missing context is selection guidance among the many sleep/readiness siblings and pagination caveats, so an agent may not know when this call is the right one.

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 each parameter (start_date, end_date, next_token, include_time_series) already has a meaningful description, so the baseline applies. The prose mostly describes output content rather than parameter behavior, adding little beyond what the schema already provides.

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 the exact resource ('sleep periods') and enumerates the returned metrics (bedtime start/end, sleep-stage durations, heart rate, HRV, breathing rate, readiness), which goes well beyond a vague getter. The distinction between 'long_sleep', 'sleep', 'late_nap', and 'rest' also separates this period-level tool from daily sleep-summary 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 phrase 'detailed sleep periods' and the explanation of period types imply it is for period-level sleep breakdowns rather than daily summaries, so usage is inferable. However, no alternative tool is named and no explicit when/when-not conditions are given, leaving some selection judgment to the agent.

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 present, so the description carries the burden of behavioral disclosure. It does mention that the window is calculated from recent sleep, but it does not disclose pagination behavior via next_token, authentication requirements, or the read-only nature beyond the word 'Get'.

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 clear sentence that front-loads the core purpose. No filler or redundant wording.

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 tool is simple with only optional parameters, all documented in the schema, and an output schema is provided. The main gap is the lack of usage alternatives and behavioral disclosures, but the description is adequate for a straightforward read-only retrieval 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 parameter descriptions already explain start_date, end_date, and next_token. The tool description does not add extra semantic value for these parameters, so the baseline of 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?

Description uses a specific verb ('Get') and resource ('Oura's recommended bedtime window') and clearly scopes it per day. It distinguishes itself from sibling sleep tools by specifying it returns a recommendation window, not actual sleep data.

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 purpose: retrieve a recommended bedtime window. However, there is no explicit guidance on when to choose this over get_daily_sleep or get_sleep_periods, and no when-not-to-use instructions.

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 burden for behavioral disclosure. 'Updated infrequently' is a useful freshness caveat, but the description does not mention authentication, pagination behavior, or the possibility of missing data, leaving meaningful 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?

The description is two short sentences with no redundant filler. It front-loads the core purpose and immediately follows with the one key behavioral caveat, making every word 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?

Given the simple read-only nature, fully documented optional parameters, and an output schema, the description plus schema is nearly sufficient. The main missing piece is explicit routing guidance relative to siblings, but the core invocation details are covered.

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%, so the parameters (start_date, end_date, next_token) are fully documented in the schema. The description does not add parameter-specific meaning beyond the metric's units, so it stays at the schema-driven baseline.

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 specifies an exact verb and resource: 'Get VO2 max (cardio capacity) estimates in ml/kg/min'. The units and parenthetical make the metric unambiguous and set it apart from sibling tools like get_daily_cardiovascular_age.

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 guidance on when to use this tool versus alternatives, and no explicit when-not-to-use conditions. 'Updated infrequently' hints at freshness constraints but does not direct the agent to a better tool or explain when this tool is appropriate.

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. It usefully discloses that results include both auto-detected and user-entered workouts and lists the returned fields, but it omits behavior such as pagination via next_token, authorization requirements, and the default date range behavior (which is only implied by the schema).

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 with no filler. It front-loads the action ('Get workouts') and immediately provides the useful scope 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 three-parameter endpoint with a complete schema and an output schema, the description is mostly sufficient, but it lacks usage differentiation among the large sibling set and does not state the authentication or pagination context. An agent could call it correctly from the schema, yet would rely on inference for when to choose it.

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 start_date, end_date, and next_token. The description does not add any parameter-level detail beyond this baseline; it only outlines result contents.

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 the specific verb-resource pair 'Get workouts' and enumerates the returned data fields (activity type, times, calories, distance, intensity, source). It is clear, though it does not explicitly distinguish get_workouts from sibling tools like get_sessions or get_daily_activity.

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 guidance is given about when to call this tool rather than alternatives. The phrase 'auto detected or entered by the user' clarifies the data source but does not say when to choose get_workouts over get_sessions or the daily summary 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?

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It says 'Get instructions,' which suggests a read-only operation, but the name 'setup_authentication' implies a mutating action. It doesn't state whether calling this tool changes state, requires user interaction, or returns a one-time code. This ambiguity is a significant 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?

A single sentence, front-loaded with the action and purpose. No wasted words. It is appropriately concise for a zero-parameter 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?

For a zero-parameter tool with an output schema, the description could be sufficient, but it leaves out key context: whether the tool is a read-only instructional endpoint or a mutating setup flow, what the output contains (URL, steps, token), and any preconditions like having a client ID or secret. The output schema may cover return format, but the description doesn't hint at side effects or prerequisites, which are essential for an authentication setup 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?

The tool has zero parameters, so the description doesn't need to explain any. The schema is empty, and there is nothing for the description to add. Baseline 4 applies because there are no parameters to document.

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 clear action: get instructions for connecting the server to an Oura account. It names the verb and resource, and it's obviously distinct from the sibling get_* data retrieval tools and check_auth_status. However, it doesn't explicitly contrast with check_auth_status, leaving minor ambiguity about whether this tool both initiates and returns instructions or just returns pre-existing instructions.

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 use when you need to connect the server to an Oura account, but it doesn't explicitly state when to use it versus check_auth_status (which presumably checks if auth is already set up). No mention of prerequisites or when not to use it. The usage context is implied but not explicit.

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