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

No annotations are provided, so the description must disclose behavioral traits. It describes the tool as a 'snapshot' implying a read operation without side effects, but it does not explicitly state read-only, auth requirements, or rate limits. The description adds context about scores being percentages of baselines but lacks full transparency on 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 one long sentence but front-loaded with the core purpose and efficiently lists the returned elements. It is fairly concise with no wasted words, though it could be broken into multiple sentences for readability.

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

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

With no output schema, the description adequately describes the return structure: overall scores, per-category cards, condition state cards, and trend comments. It also explains score interpretation (percentages of baselines). The usage guidance adds completeness. Minor gaps: does not detail card structure or trend comment format.

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 coverage is trivially 100%. Per guidelines, baseline is 4. The description does not need to add parameter details since there are none.

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 it retrieves the current snapshot of the health dashboard, listing specific components like overall health status, cultural activity score, per-category cards, condition state cards, and trend comments. It distinguishes from siblings like get_recent_activities (activities), get_score_history (history), and query_records (general query).

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 explicitly advises to use this tool first for any 'how am I doing' question, providing strong usage guidance. It does not list exclusions or alternative tools for specific cases, but the context makes it clear this is the primary status tool.

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

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

Description reveals it returns human-readable lines with relative time and a backend limit of 8, but lacks disclosure on side effects given no annotations. Adequate for listed 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?

Two concise sentences front-load the main functionality and include important details without unnecessary text.

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 list tool with one parameter and no output schema, the description adequately covers functionality and constraints.

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%; the description mentions 'latest 8' which aligns with the parameter's default and max, adding no new meaning beyond 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?

Clearly states it lists recent activities across multiple sources with human-readable lines and relative time, distinguishing it from siblings like get_current_status or query_records.

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?

Implies usage for retrieving recent activities, but does not explicitly specify when to use vs alternatives or provide 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. It describes output structure (per-date rows with overall scores and optional category columns) and granularity by range. It does not disclose potential limitations like empty data, rate limits, or auth needs, but it is reasonably transparent for a read-only query 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?

The description is concise with two sentences, front-loading the main purpose and data structure. It efficiently conveys key details, though the default range could be explicitly highlighted instead of implied.

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 no output schema, the description explains output structure well. It covers granularity, optional categories, and category naming. It lacks pagination or limit info but is adequate for a simple query tool with two optional parameters.

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%, and the description adds value beyond schema: it states the default range (3m), lists valid category names, and provides usage advice to limit categories. This extra context aids correct parameter selection.

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 a score time series with overall health_score and cultural_score per date, plus optional per-category columns. It specifies granularity based on range and distinguishes from siblings like get_current_status (current snapshot) and get_recent_activities (activity list).

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 advises to add only needed categories to keep output small, which guides parameter selection. However, it does not explicitly state when to use this tool versus alternatives, though context signals imply it for time series vs. current state or recent activity.

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 relies on the word 'List' to imply a read-only operation. It lacks explicit statements about safety, authentication, or side effects, which would be beneficial for full 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?

Two sentences, no redundant information. The first sentence states the action and lists returned fields; the second provides a clear usage directive. Maximum efficiency.

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 no parameters and no output schema, the description adequately covers what the tool returns and its primary use case. It could mention any ordering or limits but is sufficient for a simple list 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 no parameters, so the input schema is trivial. The description adds meaning by detailing the output fields (category, display_type, classification, etc.), which helps an agent understand what information will be returned.

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 lists all configured data sources, specifying key attributes returned (category, display_type, etc.), and distinguishes itself from sibling tools by highlighting its utility for discovering valid source/category values for query_records.

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 explicitly tells when to use this tool: 'Use to discover valid source and category values for query_records.' It does not provide explicit exclusions but the context implies it is not for status or activity data.

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 provided, so description carries full burden. Discloses truncation behavior and grouping aggregation. However, does not mention return format, permissions, or rate limits. Adequate but could be richer.

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?

4 sentences, front-loaded with purpose, efficient. Every sentence adds value. Could be slightly more structured but overall concise.

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 query tool with 6 params and no output schema, description covers key aspects: data format, grouping, filtering, date range, limit, truncation, and reference to list_sources. Complete for typical usage scenarios.

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%, baseline 3. Description adds meaning beyond schema by explaining the data structure (one row per date x source x category) and that grouping aggregates sums. Provides context for source/category filtering via list_sources.

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 clearly specifies 'Query raw daily activity records' with detail on data structure (one row per date x source x category: minutes, raw_value, raw_unit). Distinguishes from siblings like get_recent_activities by focusing on raw daily records with filtering and grouping.

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?

States requirement for from/to date range, suggests filtering by source/category with reference to list_sources, and provides guidance to prefer grouping for ranges over ~2 months to keep output small, mentioning raw mode cap and truncation. Does not explicitly contrast with siblings but gives clear context.

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