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 enumerates returned data fields but says nothing about authentication, rate limits, whether the range is inclusive, or what happens on missing days — meaningful gaps for a data-fetch tool with zero annotation coverage.

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 tight sentence with the resource and its key contents front-loaded; every word earns its place and there is no 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 simple two-parameter read tool with fully documented schema and no output schema, the description is nearly sufficient: it names the resource and the fields returned. It only lacks confirmation of read-only nature and date-range semantics.

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 both start_date and end_date are already documented as YYYY-MM-DD with end_date optional. The description adds no parameter-level meaning (e.g., max range, inclusivity), 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 ('Get') plus resource ('daily activity data') and enumerates the returned fields (steps, calories, activity score). It is clear on its own, though it never explicitly contrasts itself with siblings like oura_readiness or oura_heartrate, which also aggregate daily metrics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance: no note that this is for activity/steps tracking versus the sleep or readiness siblings, and no mention of the date-range requirement or default behavior. The agent must infer the selection context from the tool name alone.

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 burden, yet it discloses almost nothing: no return granularity (samples vs. aggregates), no pagination or size limits, no auth requirements, and no statement that this is a read-only operation. 'Over time' hints only vaguely at a time series.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, front-loaded sentence with no filler or redundancy. It is efficient, though arguably too terse to be maximally useful given the missing behavioral detail.

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 two-parameter read tool this is minimally adequate: the schema covers the inputs and no output schema exists to explain. However, with no annotations and no output schema, the description should say more about what a heart rate 'time series' response looks like and how large a range can be requested.

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 both start_date and end_date with format guidance. The description adds no extra semantics such as default ranges, timezone handling, or whether end_date is inclusive, so 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?

The description states a specific verb ('Get') and resource ('heart rate data') with a temporal scope ('over time'). It does not explicitly differentiate from siblings, but the sibling tools (sleep, readiness, activity) cover distinct data domains, so there is little real ambiguity.

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, nor any mention of prerequisites such as Oura authentication or data availability. The only implied usage is the date-range focus carried by the parameter names.

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 doesn't state that this is a read-only operation, what authentication it needs, how far back dates can go, whether end_date is inclusive, or what the response looks like. Only the list of returned metrics adds any behavioral signal.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with the resource named first and no redundant or filler content. Nothing to trim.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, and the description partly compensates by naming the four returned metrics, which is genuinely useful. However, for a date-range read tool with no annotations, it omits output format, date-range limits, and behavior when end_date is absent, leaving real gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with both start_date and end_date documented as YYYY-MM-DD strings, so the baseline is 3. The description adds nothing beyond the schema about parameter behavior (no range limits, no default when end_date is omitted).

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?

Specific verb 'Get' plus a named resource ('daily readiness score') and an enumeration of the returned metrics (HRV balance, resting heart rate, body temperature). This clearly separates it from oura_sleep/oura_activity/oura_heartrate even though those siblings are never named. It stops short of explicit sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: the word 'daily' and the readiness-specific metrics tell an agent this is the recovery/readiness endpoint rather than sleep, activity, or heart-rate. There is no explicit statement of when to prefer this tool over its siblings and no mention of any date-range restrictions.

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 disclosure burden. 'Get' implies a read, but the description says nothing about whether days with missing data are omitted, whether end_date defaults to today, rate limits, or auth requirements. For a data-retrieval tool with zero annotation coverage, that is a substantial 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 efficient sentence with the core capability front-loaded and no wasted phrasing. It could be slightly tighter but nothing is redundant.

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 two-parameter read with no output schema, the description covers what data comes back, which is helpful. It omits date-range behavior and any reference to alternatives, leaving the agent to infer the query semantics.

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 both date parameters and their YYYY-MM-DD format are already documented in the schema. The description adds no parameter-level meaning (e.g., what happens when end_date is omitted), so the baseline 3 is correct.

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 ('daily sleep data') and enumerates the returned fields (sleep score, sleep stages, duration). It is distinguishable from the oura_readiness/activity/heartrate siblings via the resource name, though it never explicitly contrasts itself with them.

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 on when to use this versus the sibling Oura tools, and no prerequisites or date-range conventions stated. The word 'daily' weakly implies a per-day date-range query, but nothing tells the agent how to choose between this and oura_readiness or how wide a range to request.

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