Cadencz

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 discloses the core action and implied outcome, but does not explain side effects, whether the plan item is consumed or removed, reversibility, or what response the caller should expect.

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 with no filler. It is concise and easy to parse, though it achieves brevity by omitting useful context.

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 mutation tool with no annotations and no output schema, the description is too thin. It leaves key operational context implicit: what approval means, whether a scheduled post is immediately created, and what conditions must be true for the plan item to be eligible.

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 has a single item_id with 0% description coverage. The description adds some meaning by relating the parameter to 'a plan item', but it does not explain the ID format, where it comes from, or how it connects to plan-related sibling tools.

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 action ('Approve') and a clear resource ('a plan item') with an outcome ('into a scheduled post'). This helps distinguish it from siblings like schedule_post and cancel_scheduled_post, though it does not fully describe the resulting state change.

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 such as schedule_post, plan_week, or publish_now. No prerequisites, exclusions, or conditions are mentioned, so the agent must infer usage from the 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?

With no annotations, the description is the only source of behavioral information. It discloses the key state transition: a scheduled variant becomes a draft. However, it does not mention permissions, reversibility, or whether the original scheduled item is fully removed or simply reverted, leaving some ambiguity for a mutation-like operation.

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, front-loaded sentence with no filler. Every word contributes meaning, and the core behavior is immediately clear.

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 one required parameter and no output schema, and the description conveys the essential state change. However, it leaves the agent to infer the precise identity and source of variant_id, and it offers no guidance about related sibling tools, so the description is adequate but not 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?

Schema description coverage is 0%, so the description must compensate for the undocumented variant_id parameter. It offers only a hint that the variant is 'scheduled', but it never explicitly explains what variant_id refers to, where to find it, or what format it should take.

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 ('pull back to draft') and the resource ('a scheduled variant'), so an agent can tell this tool un-schedules a post. It does not explicitly differentiate from siblings like publish_now or schedule_post, but the meaning is reasonably 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 implies the tool is used when a scheduled post should no longer be scheduled, but it provides no explicit guidance on when to choose it over alternatives such as publish_now, schedule_post, or listing scheduled posts. There is no exclusion criteria or mention of 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 carries the full burden of behavioral disclosure. It discloses that the tool writes exactly one post, grounds content in the Brain, defaults to the workspace Brain, allows a different Brain via brain_id, and consumes one AI generation. It stops short of saying whether the post is a draft or immediately publishable, but the sibling names make that distinction inferable.

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 compact sentences front-load the action, then add the grounding behavior and the one-generation cost. Every sentence earns its place, and there is no redundant restating of the tool name or schema.

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 covers core purpose, input source, Brain defaulting, and generation cost. But it omits platform parameter semantics and the post's lifecycle stage, which is relevant given the sibling tools schedule_post and publish_now. It is adequate but leaves meaningful gaps for an agent deciding how to invoke 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?

Schema description coverage is 0%, so the description must compensate. 'idea' is effectively explained by 'from an idea', and brain_id is explicitly explained via 'unless brain_id names another'. However, the platform parameter is not directly explained beyond the word 'platform-native', leaving its accepted values and default behavior unclear.

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 a specific action ('Write') and a specific resource ('one platform-native post'), plus the source ('from an idea') and grounding context (the Brain). It does not explicitly call out sibling tools, but the action is clearly distinguishable from schedule_post, publish_now, and query_brain.

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 when to use the tool: when you have an idea and want one grounded post generated. It also explains the brain default and override. However, it gives no explicit guidance about when not to use it or when to prefer siblings like schedule_post or publish_now.

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 explaining behavior. It does convey that the tool returns aggregated totals rather than raw engagement data, and that results are scoped to a time window. It does not disclose defaults, data freshness, platform scope, or whether zero-engagement platforms are included, leaving some behavioral ambiguity.

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 key output concept, 'engagement totals per platform', and communicates the main scope, 'over a window', without 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?

For a tool with one optional parameter and no output schema, the description gives the essential return shape: engagement totals per platform. It is minimally viable but leaves gaps around the default window, what counts as engagement, and the exact platform list, which an agent may need to infer.

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 no description for the days parameter, so the phrase 'over a window' adds some contextual meaning. The parameter name, type, and min/max constraints make its role largely inferable, but the description does not explain the default behavior when days is omitted, which is a notable gap.

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 what the tool returns: engagement totals grouped by platform over a time window. It is specific enough to distinguish from sibling tools like list_scheduled_posts or get_plan_usage, but it lacks an explicit verb like 'retrieves' and does not directly contrast itself with any sibling.

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 usage is implied: an agent should call this when the user wants engagement analytics per platform over a period. However, there is no explicit guidance about when not to use it, no mention of prerequisites, and no comparison to closely related tools such as get_plan_usage.

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, but it only offers a noun phrase. It does not state that this is a read-only operation, whether authentication is required, or what happens if no current plan exists.

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 phrase with no unnecessary words, which is appropriate for a parameterless tool. Adding an explicit verb could strengthen it, but the brevity is not a flaw.

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 tool with no parameters, this description may be minimally sufficient, but it lacks detail about what the items contain, what the return format looks like, and whether a plan must already exist. With no output schema, the agent has to infer most response details.

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 and schema description coverage is 100%, so there are no parameter semantics for the description to add. A baseline of 4 is appropriate.

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

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

The description clearly identifies the resource as 'current weekly content plan and its items,' and the tool name 'get_current_plan' reinforces retrieval intent. It is distinct from siblings like get_plan_usage or plan_week, though the description itself does not explicitly differentiate 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 is given about when to use this tool versus alternatives such as get_plan_usage or plan_week. There is no mention of prerequisites, context needed, or what 'current' means in relation to the planning workflow.

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 behavioral burden. It conveys a read-only usage retrieval and a time scope, but it does not clarify how the period is defined, whether data is real-time, or what happens when no plan or allowance exists.

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 that leads with the resource and key constraints. 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?

For a no-input getter with no output schema, the description is largely self-sufficient. The main gaps are the exact return shape and exact definition of the current period, but these are minor for this simple 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 zero parameters, and schema description coverage is trivially 100%. There are no parameter semantics for the description to clarify, so the baseline of 4 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 concrete get operation for 'allowance usage', scoped to 'the plan's caps' and 'this period'. This clearly distinguishes it from siblings like get_current_plan or get_analytics.

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 when to use the tool: when checking allowance consumption against plan caps. However, it does not explicitly mention alternatives or provide when-not-to-use guidance, leaving some inference 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 provided, so the description carries the full burden of behavioral disclosure. It identifies what the tool concerns but does not disclose read-only behavior, return format, pagination, or side effects beyond what the name 'list' already implies. This is only marginally more informative than a tautology.

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 very short and contains no filler or repetition. However, it is not structured as a complete sentence and omits the action verb, so it is concise at the cost of clarity. Still, every word earns its place.

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

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

For a zero-parameter list tool, calling it is mechanically simple, but the description gives no indication of what the returned brains look like, whether this is a read-only operation, or how this relates to sibling tools such as list_channels and list_workspaces. Without annotations or an output schema, this is incomplete.

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 and the input schema is empty, so there is no parameter semantics burden for the description. The baseline of 4 applies because no additional parameter explanation 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 names the resource ('Website Brains') and the scope ('in this workspace'), so an agent can guess the tool lists brains in the workspace. However, it is a noun phrase rather than a verb statement, and it does not explicitly say 'lists' or 'retrieves'. It partially distinguishes itself from siblings by naming a distinct resource, but the action is left to inference from the tool name.

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 about when to use this tool versus alternatives like list_channels, list_workspaces, or query_brain. The phrase 'in this workspace' hints at a scoping condition, but there is no explicit when-to-use or when-not-to-use guidance.

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

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

With no annotations, the description carries the full behavioral burden. It only provides a noun phrase about connected social accounts and plan coverage; it does not explicitly state that this is a read-only list operation, what response format to expect, or what 'covers' means behaviorally.

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 text is efficient and front-loads the key attribute: plan coverage of connected accounts. It loses a point because it is an incomplete sentence rather than a clear action statement.

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 there are no input ambiguities, and the description gives a broad summary of the expected output. However, it leaves 'the plan' vague and does not explain the output structure, which matters more because no output schema 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?

The input schema has zero parameters, so the baseline is 4. The description does not need to explain parameter behavior 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 identifies the resource as connected social accounts and adds a distinguishing attribute: whether the current plan covers them. This is clearer than a bare restatement of the tool name, though it lacks an explicit verb and does not differentiate against sibling list 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?

No guidance is given about when to use list_channels as opposed to list_workspaces, list_brains, or list_scheduled_posts. The name implies a listing operation, but the description provides no usage context 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 must carry behavioral disclosure. It adds the useful facts that these posts are 'committed' and scheduled 'in the coming days,' but it does not state read-only behavior, default window, ordering, or pagination. The list_* name makes non-destructive behavior inferable, so this is slightly above absent but still minimal.

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 with no wasted words, and the temporal scope is front and center. However, it is a noun phrase rather than a verb-led directive, so the structure is slightly less clear than it could be.

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 tool with no output schema and no annotations, the description leaves out the effect of the days parameter, return value shape, and any default behavior. It names the domain but is not sufficient for an agent to decide whether to pass days or what result to expect.

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 no description for the single 'days' parameter (0% coverage), so the description must compensate. The phrase 'in the coming days' hints at the parameter's purpose, but it never explains that days controls the lookahead window, its default, or its units, leaving the only user-configurable behavior underspecified.

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 identifies the resource (posts committed to publish in the coming days) and, together with the tool name, makes clear this is a listing operation. It does not use an action verb or explicitly differentiate from schedule_post/cancel_scheduled_post, but the scope is specific enough to avoid confusion with other list_* 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?

There is no guidance on when to call this tool versus schedule_post, cancel_scheduled_post, or publish_now, and no mention of prerequisites. The intended use is only implied by the name and the noun-phrase description, so an agent gets no decision support.

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 behavioral disclosure burden. It does add a useful scoping fact—results are limited to what the current token can see—but it does not describe return shape, pagination, or failure behavior. For a zero-parameter list operation, this is acceptable but minimal.

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 is a noun phrase rather than an imperative, but every word contributes meaning and the key scoping detail 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 no-parameter, no-output-schema list tool, the description is reasonably complete: it names the resource, the visibility scope, and the token dependency. It does not describe the returned fields, but the simplicity of the tool makes that a minor gap.

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 zero parameters and schema coverage is 100%, so the description does not need to explain parameters. The baseline of 4 applies because there is nothing for the description to add.

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 (workspaces) and the access scope (workspaces the current token can see), so the purpose is understandable. It lacks an explicit action verb and does not differentiate from sibling list tools, but the tool name supplies the 'list' action.

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

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

Usage context is implied rather than stated: call this tool when you need workspaces visible to the current token. There is no explicit when-not-to-use guidance or mention of alternatives, though sibling tools operate on different resources like brains and channels.

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?

Without annotations, the description carries the disclosure burden. It usefully reveals that running the plan consumes the shared AI-generation allowance, a relevant operational side effect. It does not describe return values, whether published posts are created, or whether the operation is repeatable, but the quota note provides meaningful behavioral context.

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 terse sentences with no filler; the first states the action and the second adds the key cost implication. It is appropriately front-loaded and minimal 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 simple no-argument action the description is mostly sufficient, and the AI-generation allowance warning is a key operational fact. However, it omits the relationship between the generated planned posts and the approval/scheduling flow visible in sibling tools, so an agent gets only a partial picture.

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 is empty and there are no required parameters, so there is nothing for the description to add beyond what the schema already shows. The baseline of 4 for a zero-parameter tool 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 uses an explicit imperative, 'Run Plan My Week,' and names the resource being acted on, making the tool's action clear. It doesn't explicitly contrast with sibling planning tools such as get_current_plan or schedule_post, so it falls just short of a 5.

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 invoke plan_week versus approve_plan_item, get_current_plan, schedule_post, or publish_now. The allowance sentence is a cost caveat, not a routing rule, and there are no prerequisites, exclusions, or alternative recommendations.

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 of behavioral disclosure. It does disclose two critical behaviors: the operation is irreversible and requires confirmation. However, it does not explain what 'queue for immediate delivery' actually does at the system level, such as effects on existing scheduled posts or required permissions.

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 packs the core action, irreversibility, and the confirm requirement with no wasted words. The semicolon structure separates the main action from crucial caveats effectively.

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 covers the essential safety and confirmation requirements for an irreversible action, but it is incomplete. With no output schema and no annotations, it lacks details about what 'immediate delivery' entails, how to obtain variant_id, or any side effects. It remains minimally viable but has clear 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 0%, so the description must compensate. It adds meaning for 'confirm' by saying it must be true, but it provides no explanation for 'variant_id.' Partial compensation at best.

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 action ('queue') and resource ('variant') with a clear time scope ('immediate delivery'). It is clear enough to distinguish from sibling tools like schedule_post, though it doesn't explicitly name 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 about when to use this tool versus alternatives. The description mentions 'requires confirm: true' and 'irreversible,' which are cautions, but there is no explicit 'use this when...' or comparison to schedule_post.

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 discloses a key trait—defaulting to the workspace's Brain when brain_id is omitted—but does not explicitly state whether the operation is read-only, what output format to expect, or any error conditions. The word 'retrieve' suggests safety but does not fully substitute for missing annotations.

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

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

The description is a single sentence that front-loads the core action and then covers the key default behavior. There is no filler, repetition, or unnecessary 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 query tool, the description covers the essential invocation details: what it does, the required question, and the optional brain_id default. However, without an output schema or annotations, the agent must infer the return shape and any potential side effects, which limits 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?

With 0% schema_description_coverage, the description must compensate for missing parameter documentation. It explains that brain_id is optional and defaults to the workspace's Brain, and 'question' is implicitly the query text. This adds meaning beyond the schema's bare type declarations, though it could be more explicit about the expected format of the question.

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 a specific verb ('Retrieve') and a distinct resource ('product context from a Brain'), and identifies the input ('a question'). This differentiates it from sibling tools like list_brains, which enumerate brains rather than querying 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?

The description implies the tool is used to obtain product context for a question, but it does not explicitly state when to prefer this tool over alternatives or when not to use it. The defaulting behavior is explained, but no comparison with siblings such as list_brains or plan_week 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?

With no annotations, the description carries the full burden of behavioral disclosure, but it only states that the tool schedules something. It does not mention side effects, validation, timezone behavior, whether rescheduling overwrites an existing schedule, or any prerequisites.

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 and front-loaded with the action verb, but it is so sparse that it sacrifices useful detail. It is not bloated, yet the brevity contributes to the overall vagueness rather than 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?

For a low-complexity tool with no annotations and no output schema, the description should provide enough context to invoke it correctly. It leaves ambiguity around timezone handling, required draft state, whether scheduled_at must be in the future, and the result of scheduling, so the definition is incomplete.

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 33%, so the description should compensate by explaining the parameters, but it does not mention timezone or variant_id explicitly. It only loosely maps 'draft variant' to variant_id and 'moment in time' to scheduled_at, leaving the timezone semantics undocumented.

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 action, 'schedule', on a specific resource, 'draft variant', for a moment in time. It is clear about the tool's core function, though it does not explicitly differentiate itself from siblings like publish_now or cancel_scheduled_post.

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 phrasing implies the tool is for future scheduling of draft variants, which loosely separates it from immediate publishing or cancellation. However, it provides no explicit guidance about when to choose this tool over publish_now, cancel_scheduled_post, or plan_week.

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