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

With no annotations, the description must disclose all behavioral traits. It only states inputs and outputs, omitting details like persistence, idempotency, required permissions, error handling, or side effects. This is insufficient for a creation 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 a single, well-structured sentence that front-loads the core purpose and immediately lists return values. Every word is necessary, and there is no redundancy.

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 5 parameters and no output schema, yet the description only covers creation and return types. It lacks context on error handling, slug uniqueness, or prerequisites like project existence. Adequate but incomplete for an agent to use reliably.

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 80%, so the schema already documents most parameters. The description adds marginal value by mentioning 'from HTML' and the return values, but does not elaborate on parameter usage or constraints beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the action ('Create'), the resource ('landing page in maasy'), the input format ('from HTML'), and the outputs ('landing_id and editor_url'). It clearly distinguishes from sibling tools like maasy_create_skill.

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 any usage prerequisites or exclusions mentioned. The description is purely declarative.

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 full burden. It discloses auto-generation of action pills after creation and loading behavior based on tool usage. However, it does not mention side effects, permissions, or whether the operation is idempotent.

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?

Three sentences, each adding value: purpose, content type, and auto-generation/loading behavior. No redundancy or unnecessary words.

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 7 parameters and no output schema or annotations, the description lacks return value information and does not explain priority/max_tokens. It is somewhat incomplete for a moderate-complexity 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 coverage is high (86%), so baseline is 3. The description adds minimal value beyond schema, only repeating 'markdown' for content. Parameters like priority and max_tokens are not explained further.

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 creates a new knowledge skill, specifies content type (markdown frameworks, checklists, strategies), and distinguishes from siblings by noting auto-generation of action pills and loading behavior based on tool context.

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 creation of new skills but does not explicitly state when to use this tool versus alternatives like maasy_update_skill or maasy_delete_skill. No when-not-to-use guidance is 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 full burden. It states 'permanently delete' implying irreversibility, but omits details like permission requirements or side effects. It is adequate 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?

Two short sentences, perfectly concise with no filler. All information is front-loaded.

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 delete operation with one parameter and no output schema, the description is mostly complete. It could mention that the action is irreversible or that no confirmation is given, but overall it provides the necessary information.

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

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

The input schema already provides 100% coverage for the single parameter (skill_id described as 'Skill UUID'). The description adds no additional meaning beyond the schema, 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?

The description clearly states 'Permanently delete a skill' which combines a specific verb (delete) and resource (skill), and it distinguishes from sibling tools like maasy_create_skill and maasy_update_skill.

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 tool versus alternatives, no prerequisites, no mention of irreversible consequences or required permissions.

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 full burden for behavioral disclosure. It indicates the output includes clusters and scores but does not mention whether the operation is read-only, requires authentication, or any side effects. This is insufficient 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?

The description is a single sentence with no wasted words. It conveys the core purpose clearly. However, it could include slightly more detail without becoming verbose.

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 lack of output schema and annotations, the description is too brief to be fully contextually complete. It does not explain the structure of the returned data (e.g., format of clusters, volume units) or any usage 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% and each parameter has a clear description. The tool description adds no additional meaning beyond what the schema already provides, so 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 clearly states the tool discovers keywords and provides clusters, volume estimates, and difficulty scores. It uses the specific verb 'discover' and resource 'keywords', and since no sibling tool has a similar function, it is well-distinguished.

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

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

No explicit guidance on when to use this tool versus alternatives. The description implies keyword discovery context, but does not mention when not to use it or provide comparisons to sibling tools like maasy_get_seo_status.

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?

Annotations are absent, so the description must convey behavioral traits. It fails to disclose side effects, permissions, idempotency, or error conditions for the various actions. For a mutation tool, this is insufficient.

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?

Single sentence with examples is efficient. Front-loads the verb. However, could benefit from bullet points or grouping of action categories for clarity.

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 or annotations, the description should explain return values, typical usage flow, or prerequisites for actions. It omits these, leaving an agent underinformed.

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 description adds meaning to the 'action' enum by listing concrete examples (generate report, redistribute budget), which complements the schema where action has no description. 'project_id' is already explained as 'Brand UUID' in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'Execute a copilot action' with examples like generate report, rotate creatives, etc. This differentiates it from sibling CRUD tools (e.g., maasy_create_landing, maasy_generate_ads) but does not explicitly clarify nuance between executing an action via this tool versus calling a more specific generate tool.

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 tool versus alternatives. For example, rotating creatives could be done via execute_action or a dedicated tool. The description does not provide criteria for selection or exclusion.

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 must bear the full burden. It indicates the tool creates new content, but does not mention idempotency, safety, permissions, or side effects. Key behavioral traits like rate limits or whether it overwrites existing data are absent.

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

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

The description is a single, well-structured sentence that front-loads the action and purpose. While it is concise, it sacrifices important details; however, the brevity does not cause confusion.

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's complexity (generating ad creatives with multiple platforms and parameters) and no output schema, the description is too sparse. It does not specify the output format, how the brief should be structured, or how to handle errors. Sibling tools exist but no differentiation is provided.

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 50% (two of four parameters have descriptions). The tool description adds no explanation for the 'platform' or 'count' parameters beyond the schema, and does not clarify how 'brand DNA' maps to 'project_id'. The description does not compensate for the schema gaps.

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 generates ad creatives (copy and concepts) for Meta or Google, using brand DNA and a brief. It distinguishes from sibling tools like maasy_generate_content by being specific to ads, though the platform list in the description omits TikTok, which is in the schema.

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

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

No guidance is provided on when to use this tool versus alternatives like maasy_generate_content or maasy_create_landing. The description does not specify prerequisites, ideal contexts, or exclusion 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?

With no annotations, the description carries the burden of behavioral disclosure. It states the tool respects brand DNA, tone, and ICP, but does not disclose error handling, authorization needs, rate limits, or side effects. The description is moderately transparent but lacks depth about consequences.

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 extremely concise with two sentences: one for the primary action and one for key constraints. No unnecessary words, front-loaded with purpose.

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's simplicity (3 parameters, no output schema), the description adequately covers purpose and constraints. It could mention output format or typical response, but not required. Overall complete for a straightforward generation 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 input schema has 67% description coverage, and the description adds little beyond what is already in the schema. It does not elaborate on parameter formats or usage, but the schema itself is clear. 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 generates on-brand social content using maasy AI, with specific verbs ('generate') and resource ('social content'). It respects brand DNA, tone, and ICP, which distinguishes it from siblings like maasy_generate_ads (ads) and maasy_create_landing (landing pages).

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 for social content generation but provides no explicit guidance on when to use this tool versus alternatives (e.g., maasy_generate_ads) or when not to use it. No prerequisites or exclusions are mentioned.

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 whether the tool is read-only, if it requires specific permissions, or any side effects. The name implies a read operation, but no explicit behavioral details are given.

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

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

The description is a single short sentence that immediately states the topic ('Pending copilot alerts') followed by a list of categories. It is brief, but lacks a verb for the action. However, it is front-loaded and not verbose.

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 there are 20 sibling tools and no output schema, the description is incomplete. It does not explain what a 'pending copilot alert' is, how the response is structured, or how results are ordered. An agent cannot fully understand the tool's output without additional information.

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 description does not mention either parameter. The schema provides a description for 'project_id' but not for 'limit'. With 50% schema description coverage, the tool description fails to compensate by explaining how parameters affect results or their meaning in context of alerts.

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 lists alert categories ('campaign anomalies, lead opportunities, content gaps, SEO drops') but uses no verb like 'get' or 'retrieve'. It indicates the tool returns pending copilot alerts but does not clearly state the action, and it fails to differentiate from siblings like 'maasy_get_campaign_metrics' or 'maasy_get_seo_status' which might return overlapping 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?

No guidance is provided on when to use this tool versus its siblings. There is no mention of prerequisites, context for when alerts are available, or cases where the tool should be avoided.

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 all behavioral information. It states what data is returned but does not disclose read-only nature, performance characteristics, or effects when project_id is omitted.

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

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

One clear sentence front-loads the purpose, followed by essential context. No unnecessary information.

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

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

Given the tool has one parameter and no output schema, the description sufficiently explains the return value and use case. However, it does not clarify behavior when project_id is missing, nor does it mention prerequisites or relation to sibling tools.

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?

Input schema covers 100% of parameters with a description ('Brand UUID'), so baseline is 3. The description does not add any additional semantic meaning beyond the schema for the parameter.

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 defines the tool's function: retrieving full brand details (name, industry, etc.). It uses specific verbs and nouns, and differs from siblings like maasy_list_brands which lists brands without context.

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?

Implicitly indicates use for 'on-brand generation', but does not explicitly state when to use versus alternatives like maasy_list_brands or maasy_get_skill. Given the hint, it is clear but lacks detailed 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?

With no annotations, description bears full burden. Only lists metrics but omits behavioral details like data freshness, aggregation method, or permission requirements.

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?

Single sentence, directly states purpose and included metrics. Efficient and front-loaded.

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?

No output schema or annotations. Description covers returned metrics but omits pagination, formatting, or limits. Adequate for a simple query 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 descriptions cover both parameters (project_id, days) at 100%. Description adds value by listing output metrics but does not deepen parameter understanding.

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 retrieves ad campaign performance metrics (spend, impressions, clicks, etc.). Distinguishable from sibling tools like maasy_get_daily_summary by focusing on campaign-level 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?

No guidance on when to use this tool versus alternatives. Does not mention prerequisites or conditions like active campaigns or required roles.

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 fully disclose behavior. It mentions filtering by status and time, but does not state whether it is read-only, what authentication is needed, or any other traits. This is insufficient for an agent to understand side effects.

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

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

The description is a single short sentence, but it is cryptic and lacks structure. It is not overly verbose, but it fails to efficiently convey key information.

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

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

Given the complexity (2 parameters, no output schema, no annotations), the description is incomplete. It does not explain what the tool returns, how the days parameter works (e.g., creation date vs. modified date), or the exact list of statuses. Many details are 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 coverage is 50% (project_id has description, days does not). The description adds context for 'days' as 'last N days', which clarifies its purpose. However, it does not explain project_id beyond the schema's 'Brand UUID'. Overall, some added value but not substantial.

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 'Content pipeline: drafts, scheduled, published, by status, last N days.' suggests it retrieves content items with various statuses and time range, but lacks a verb and is vague. It distinguishes from siblings like maasy_generate_content but could be clearer. Score 3 is appropriate as it is not a tautology but not fully specific.

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 tool versus alternatives, such as maasy_get_alerts or maasy_get_brand_context. The description provides no context for tool selection.

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

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

No annotations are present, so the description must disclose behavioral traits. It only lists output fields and does not mention side effects, authentication needs, or rate limits. The tool appears read-only but this is not explicitly stated.

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 extremely concise, consisting of a single phrase. It is front-loaded and contains no superfluous words, though it could be rephrased as a full sentence for better 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?

The description enumerates the key data points returned (leads, hot leads, etc.), which is helpful given the lack of output schema. However, it does not specify the structure (e.g., aggregated numbers or list) or formatting.

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

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

The schema covers 100% of parameters with a description for 'project_id' as 'Brand UUID'. The description adds no additional meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool provides CRM pipeline data including leads by status, hot leads, contacts, opportunities, and total pipeline value. The verb 'get' is implied by the name, making the purpose understandable.

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 siblings like maasy_get_brand_context or maasy_get_daily_summary. The description lacks usage context 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?

With no annotations, the description bears full responsibility for disclosing behavior. It does not mention whether the tool is read-only, requires authentication, or has any side effects. The mention of 'recommended actions' is vague and does not clarify if the tool actually performs actions or just suggests them.

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 at 10 words, covering the key aspects: events ('what happened'), attention items, and recommendations. It is well-structured as a single sentence, though it could benefit from more detail without becoming verbose.

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 lack of an output schema, the description should thoroughly explain the return format. It provides a high-level idea of the content but omits details like timezone, data granularity, and whether the summary is per brand or aggregated. The optional parameter's impact on the output is also not clarified.

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

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

The schema provides a description for the single parameter ('Brand UUID'), achieving 100% coverage. The tool description does not add any additional meaning, such as whether the parameter is optional, how to obtain the UUID, or what happens if omitted. Since the schema already documents the parameter, a 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 clearly states that the tool provides a summary of today's operations including events, attention items, and recommended actions. However, it does not differentiate itself from sibling tools like maasy_get_alerts or maasy_get_crm_summary, which may offer similar summaries.

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. For example, it doesn't explain under what circumstances to use the daily summary instead of maasy_get_alerts for attention items or maasy_get_crm_summary for operational updates.

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, and the description does not disclose any behavioral traits (e.g., read-only, no side effects, rate limits). The agent must infer this is a read operation from the name, but the description fails to confirm.

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 phrase, but it is a list rather than a structured sentence. It could be improved with a clear verb and structure, but it is not overly verbose.

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?

No output schema exists, so the description is the sole indicator of return values. It lists multiple metric types but lacks details on format, pagination, or how results are structured. This is incomplete for a tool that likely returns complex data.

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

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

The input schema has one parameter (project_id) with description 'Brand UUID'. Schema coverage is 100%, so the description adds no extra meaning. Baseline at 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 lists data types (SEO/GEO scores, keyword rankings, visibility trends, top queries) which gives some idea of output, but does not explicitly state the action (getting/reporting). The tool name 'get_seo_status' implies the action, but the description is a noun phrase, not a clear statement of 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?

No guidance on when to use this tool versus siblings like maasy_discover_keywords or maasy_get_alerts. No prerequisites or context 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 must disclose behavior. It indicates the tool returns 'content and auto-generated quick action pills', which is helpful, but it does not mention that the operation is read-only, any authentication needs, or rate limits. The description 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 a single sentence that is front-loaded with the action verb and resource. Every word is necessary and there is no extraneous information.

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

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

Given that there is no output schema and no annotations, the description provides a reasonable overview of what the tool returns (content and quick action pills). It could be more detailed about response structure or side effects, but for a simple retrieval tool it is fairly complete.

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

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

The input schema has 100% coverage with skill_id described as 'Skill UUID', which is clear. The description adds context about the return value but does not further clarify the parameter meaning beyond what the schema provides. 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 'Get full details of a skill', using a specific verb and resource. It distinguishes from sibling tools like maasy_list_skills by mentioning 'full details', but does not explicitly name alternatives, so a 4 is appropriate.

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 skill_id is available and full details are needed, but lacks explicit guidance on when to use this versus alternatives like maasy_list_skills or maasy_update_skill. No exclusions or prerequisites are mentioned.

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 must convey behavioral traits. It indicates a read-only listing operation with no side effects. However, it doesn't specify authentication needs or rate limits, though for a simple list tool this is sufficient.

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, clear sentence with no wasted words. The verb 'List' is front-loaded, making the purpose immediately obvious.

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's simplicity (no parameters, no output schema), the description is mostly complete. It tells the agent what it does and what to expect ('basic info'). Slightly improved by specifying common fields, but adequate.

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

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

The input schema has no parameters and 100% coverage. The description adds value by hinting at the output with 'basic info', which implies limited fields like name and ID, though not detailed.

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 lists all brands (projects) with basic info. It uses a specific verb 'list' and resource 'brands', and differentiates from sibling 'maasy_get_brand_context' which likely provides detailed info for a single brand.

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

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

No explicit when-to-use or alternatives are provided. The usage is implied: when a user wants an overview of all brands, but no guidance on when not to use it or comparison with other tools like maasy_get_brand_context.

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 solely handles transparency. It states 'list' implying read-only, but does not explicitly confirm non-destructiveness, mention default filter behavior (active_only=true), or describe any side effects or limitations.

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 purpose. Every word adds value; no redundant information.

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

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

For a simple list tool with no output schema, the description is adequate but incomplete. It does not mention what the return format is, whether pagination exists, or that categories can be filtered. Additional context would improve 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 0%, so the description must compensate. It briefly mentions examples of skill content but does not explain the category or active_only parameters. The description adds little meaning 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 clearly states the verb (list) and resource (maasy copilot skills), and explains what skills are (modular knowledge packages). It distinguishes from sibling tools like create_skill or get_skill which address individual skill operations.

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

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

Usage is implied by the name and description, but no explicit guidance is given on when to use this tool versus alternatives like get_skill or other list tools. No when-to-use or when-not-to-use information is 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 bears full burden. It discloses the output format (traffic-light status per area) and implies read-only behavior ('scan'), but does not mention side effects, performance, or authorization requirements. The description 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 purpose and key output details. No unnecessary words.

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 scan tool without output schema, the description sufficiently explains the aggregated output (traffic-light status per area) and scope. It could mention that it combines multiple sub-scans, but the sibling names already hint at individual tools. Overall, it meets the needs for selection and invocation.

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

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

The input schema fully describes the only parameter (project_id) with a clear description. The tool description does not add further parameter context (e.g., examples, format). Since schema coverage is 100%, 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 performs a deep health scan across multiple brand areas (DNA, campaigns, content, CRM, SEO, alerts) and returns traffic-light status per area. This distinguishes it from siblings that focus on individual areas (e.g., maasy_get_crm_summary, maasy_get_seo_status).

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 for a comprehensive brand health check, but does not explicitly state when to use this tool versus individual sibling tools (e.g., for a specific area like SEO). No when-not-to-use guidance is 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 provided, so the description must cover behavioral traits. It only states return values and omits side effects (e.g., mutation of data), authentication needs, or what happens when scheduled_at is omitted (draft saving is only in schema). Minimal 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?

Single sentence, front-loaded with key information. No wasted words.

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 6 parameters, no output schema, and no annotations, the description is too sparse. It does not summarize important details like draft vs scheduled behavior or content_type defaults that are only in schema.

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 high (83%), so the description adds limited value beyond what schema already provides. The mention of return values is helpful but not related to parameter meaning.

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 action ('Schedule a social media post') and the resource, along with what it returns. It is specific and distinguishes from sibling tools that perform other functions like generating or scanning.

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 tool versus alternatives (e.g., creating a draft vs scheduling, or using maasy_generate_content for content creation). The description lacks context on prerequisites or typical use cases.

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, and the description does not disclose behavioral traits such as whether the trigger is destructive, idempotent, or has side effects (e.g., sending emails). The agent lacks critical safety information.

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 captures the core purpose efficiently. It is concise but could be improved by front-loading key usage cues at no extra length.

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 and no annotations, the description lacks essential context such as return values, error handling, or workflow execution details. It is insufficient for a tool that may have side effects.

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 baseline is 3. The description adds no extra meaning beyond the schema's parameter descriptions; it simply restates the tool's purpose without enhancing parameter understanding.

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 'Trigger a maasy workflow manually — automations, sequences, CRM flows' clearly states the specific action (trigger) and resource (workflow), distinguishing it from sibling tools like create_skill or list_brands.

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 vs alternatives, prerequisites, or when not to use it. The description is purely declarative without conditional advice.

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 must cover behavioral traits. It only mentions regeneration of quick action pills on content change, lacking other important aspects like idempotency, partial update behavior, permissions, or rate limits.

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

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

The description consists of two concise sentences, front-loaded with the verb and resource, and no redundant information.

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

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

Given no output schema, no annotations, and 8 parameters with low schema coverage, the description fails to provide sufficient context. Missing: return value, constraints, usage patterns, and behavior when multiple fields are updated.

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 only 13% (only skill_id described). The description lists updatable fields (content, category, priority, active status) but does not explain other parameters (name, description, max_tokens) or the meaning of the category enum. It adds marginal value but does not compensate for low 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 updates specific fields of a skill (content, category, priority, active status) and mentions a side effect (regenerating quick action pills). This distinguishes it from sibling tools like maasy_create_skill and maasy_delete_skill.

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 (e.g., when to update vs. create a new skill). It does not mention any prerequisites or exclusions.

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