new-hire-onboarding-tasks

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

Annotations already indicate this is not read-only and not destructive, and the description adds useful behavioral detail: existing data under the token stays, and a wrong or expired key changes nothing. This goes beyond the annotation hints by explaining failure semantics and safety of the 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 two sentences with no filler. It front-loads the core action, then gives the key format and safety guarantees, and closes with the verification tool. Every sentence contributes essential 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 single-parameter activation tool with annotations covering the safety profile, the description is complete: it states what the tool does, what input is needed, what happens on failure, and how to confirm success. There is no missing critical information for an agent to call it correctly.

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

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

The schema already documents the key parameter and its format with 100% coverage. The description adds meaning by specifying that the key must be issued at checkout for this server or the bundle, which clarifies validity requirements not present 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?

The description uses a specific verb and resource: it 'turns Pro on' for the connection using a license key. It also distinguishes itself from the sibling license_status tool by saying license_status confirms the activation. This leaves no ambiguity about what the tool accomplishes.

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

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

The description provides clear context for use: the key must be an MCPL1.<payload>.<signature> issued at checkout for this server or the bundle. It does not explicitly list exclusions or alternative tools, but it does reference license_status as the confirmation path, giving the agent a sense of the 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds useful context beyond annotations by specifying the JSON response contents and stating 'nothing changes,' reinforcing the read-only nature of the call.

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 dense sentences cover output, purpose, usage context, and side-effect guarantee. Every sentence earns its place and the most important 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?

With no output schema, the description sufficiently describes the return value. With no parameters, annotations covering safety, and a clear use case, nothing essential is missing for an agent to invoke this tool correctly.

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

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

There are zero parameters and the schema already fully documents that fact. The description explicitly says 'No arguments,' which is accurate and reinforces the schema without needing further elaboration.

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 begins with a specific verb ('Report') and a precise resource ('this endpoint's licence state for your token'), and enumerates the exact output fields: product, tier, reason, and checkout URL. This clearly distinguishes it from sibling tools like license_activate.

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

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

The description explicitly states when to call it: 'Call it to explain a free-tier refusal.' This is clear contextual guidance, though it does not name alternatives or explicitly state when not to use it.

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 all false and do not convey safety or idempotency, so the description carries the behavioral burden. It discloses that the tool creates a hire, returns an H-NNNN id, and normalizes the role to lower-cased and hyphenated form. This adds useful behavior beyond the bare schema.

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

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

Two sentences convey the core action, return value, required fields, role transformation, and related tools without waste. The most important 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 3-parameter create tool with no output schema, the description covers inputs, return id, and next-step alternatives. Minor omissions such as failure modes or what happens with duplicate names are not critical given the tool's simplicity.

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%, but the description adds meaning by framing role as a 'grouping key' and indicating that name, role, and start date are the core inputs. It reinforces the role transformation rather than merely restating the parameter names.

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

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

The description uses a specific verb ('Add') and resource ('a new hire') and tells the agent the tool returns an H-NNNN id. It also distinguishes itself from related siblings by pointing to onboarding_task_add and onboarding_template_apply for follow-up work, so there is no confusion with list/progress tools.

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

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

The description names the relevant alternative tools and suggests when to use them after adding a hire. It does not explicitly state when not to use this tool or compare it directly to template_apply, but the context is clear enough for a create operation.

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 all false, so the description carries the behavioral disclosure burden. It usefully adds the 500-row limit and 'newest change first' ordering, which are not visible in the schema. It does not explicitly state that the tool is read-only or has no side effects, though the list framing strongly implies this; there is no direct contradiction with the 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 three short sentences with no filler. It front-loads the returned fields, then states filtering, then the row cap and ordering, making every sentence informative and easy to scan.

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

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

With only two optional parameters and no output schema, the description covers the essential call-time facts: what fields are returned, how to filter, the maximum result size, and the sort order. It does not mention pagination or authentication, but for a simple list tool with no required parameters this is not a critical 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?

Both parameters are already fully documented in the JSON schema, including lower-case hyphenation matching for role and case-insensitive contains for name, so schema coverage is 100%. The description's 'Filter by role or by a word in the name' adds no new semantic detail beyond what the schema provides. The baseline of 3 is appropriate.

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

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

The description clearly states that the tool returns hire information with role, start date, task counts, percent complete, and overdue count. The listed fields and 'Every hire' framing distinguish it from focused sibling tools like onboarding_overdue or onboarding_progress. It would be stronger with an explicit verb, but the title 'List hires' supplies that 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?

The description explains how to narrow results via role or name filter and notes the 500-row cap, which gives useful invocation context. However, it never explicitly contrasts this tool with siblings such as onboarding_overdue, onboarding_progress, or onboarding_hire_add, so when-to-use versus alternatives is only implied.

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 already declare read-only, idempotent, and non-destructive behavior. The description adds useful behavioral context: returns at most 500 rows, orders by most overdue first, and includes days-late information. This goes beyond the schema and annotations without contradicting 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?

Two tightly written sentences: the first defines the resource and scope, the second communicates limit, ordering, and the days-late output. There is no filler or redundant restatement.

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

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

For a read-only list operation with one optional parameter and no output schema, the description supplies everything needed to invoke it correctly: scope, result size cap, ordering, and key output content. No critical behavioral or invocation detail is missing.

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

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

The single optional parameter is already fully described in the schema: 'Only this hire's overdue tasks. Omit for every hire.' The description mirrors this scope but adds no new parameter-level meaning, so the schema carries the semantic weight.

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 tool as listing tasks that are outstanding past their due date, with scope across all hires or a single hire. It is distinct in substance from siblings like onboarding_progress or onboarding_task_add, though it does not explicitly name an alternative it is not.

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

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

The intended use is implied: call this when you need overdue onboarding tasks, optionally filtered by a hire. However, it never states when to prefer this over related tools like onboarding_progress or onboarding_hire_list, and no exclusions are given.

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 provide no behavioral hints (readOnlyHint=false, etc.), so the description must cover behavior. It discloses that the tool returns a full plan and that CSV export is Pro-only, which is useful. But it does not state whether this operation is read-only, whether it modifies anything, or any side effects. Given the absence of annotations, a 3 is reasonable because it adds some context but misses a clear statement of read-only nature.

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, compact and front-loaded with the core purpose. The CSV note is appended succinctly. It could be more concise by trimming redundant words like 'whole plan' but overall efficient and focused.

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 moderate complexity (2 parameters, no output schema, no nested objects), the description covers the main behavior and the CSV option. It doesn't describe return format in detail, but since there is no output schema, the agent might need to infer the structure. However, the description lists the data elements (percent complete, overdue count, outstanding), which is sufficient for most use cases. Slight gap on CSV format details, but acceptable.

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

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

Schema description coverage is 100%, so both 'hire' and 'as_csv' are already well-documented in the schema. The description reinforces what 'hire' means (the hire's progress) and adds the Pro-only constraint for as_csv, which is a small addition. Since the schema does most of the work, 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 identifies the tool as showing a single hire's complete onboarding plan, listing specific components (tasks, owners, due dates, status, percent complete, overdue count, outstanding items). It distinguishes from sibling tools like onboarding_overdue by scope (one hire's whole plan vs. overdue items) and from onboarding_hire_list by focus on progress details.

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 states its primary use (showing a hire's progress) and hints at the CSV option for Pro users, but it does not explicitly say when NOT to use it or mention alternatives. However, the scope is clear enough that an agent can infer it is for a single hire's plan, not for listing hires or tasks.

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 already establish that this is not read-only, destructive, or idempotent. The description adds useful behavioral context beyond those annotations by specifying that the response is a K01-style id and by clarifying that the due date is counted from the hire's start date. It does not contradict the 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 two sentences with no filler. The first sentence states the action and return value, and the second clarifies date counting. It earns its place without duplicating schema details unnecessarily.

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?

All four required parameters are documented in the schema, and since there is no output schema, the description supplies the missing return contract. For a simple create tool, this is complete enough for an agent to call it correctly.

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

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

Schema description coverage is 100%, with each parameter fully described including the owner enum and due_offset semantics. The description mostly restates the due_offset behavior rather than adding new parameter-level meaning, so the baseline score of 3 is appropriate.

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

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

The description states a specific verb ('Add'), a specific resource ('a hire's plan'), and the expected result ('return its K01-style id'), while listing the key attributes involved. This clearly separates it from siblings like onboarding_task_done and onboarding_template_apply, which operate in the same domain but perform different actions.

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 explicit guidance about when to use this tool versus alternatives, such as 'use this for individual task creation rather than applying a template'. The phrase 'Add one task' and the sibling tool names imply the intended use, but the agent must make that inference rather than being told.

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 only indicate readOnly=false, destructive=false, and idempotent=false. The description adds meaningful behavioral context: done counts toward percent complete, skipped is a deliberate dismissal that never counts, and todo reopens the task. This goes beyond the structured fields without contradicting 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?

Three sentences with no filler. The main action is front-loaded, each status is given meaningful context in a compact way, and the re-open note earns its place by completing the status model.

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 four-parameter mutation tool with a complete schema, the description covers the status behavior and even the date aspect. No output schema exists, but for a state-change tool the return value is not essential for correct invocation. The definition is sufficient for an agent to use 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?

The input schema documents all four parameters at 100% coverage, including the date format, hire id/name, task id, and status enum. The description reinforces the status semantics but does not need to repeat parameter-level details; the schema carries the load.

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

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

The description states a specific action and resource: 'Mark one task on a hire done or skipped, with the day it happened.' It also clarifies the statuses (done, skipped, todo) and the semantic distinction between them, making it easy to separate from siblings like onboarding_task_add or onboarding_progress.

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: whenever a single task's status needs to be changed. It explains the meaning of each status choice, but it does not explicitly name alternatives or state when not to use this tool, so the guidance is mostly implied.

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?

The description goes beyond the annotations by disclosing important side effects: a version is recorded, later edits to the template do not affect already-started hires, and a missing template is auto-created from the provided tasks. This is meaningful behavioral context for a mutating 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?

Three sentences deliver all the essential information: the action, the free/Pro distinction, version recording, immutability of existing hires, and fallback template creation. No filler or 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 description is largely complete for selecting and invoking the tool: it covers scope, versioning, post-edit behavior, and template creation. However, it does not mention return values or edge cases like re-applying a template to a hire that already has tasks, and there is no output schema to fill that 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?

Schema description coverage is 100%, so the baseline is 3. The description reinforces the hire plurality and the tasks fallback behavior but does not add significant new meaning beyond what the input schema already documents for each 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?

The description clearly identifies the operation as applying a role template to a hire, specifies the main effect (copying tasks into the hire), and notes the version-recording behavior. It is distinct from sibling tools like onboarding_task_add or onboarding_hire_add because it operates on templates and hires at the template level.

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

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

The description gives clear usage context: one hire on free plans, many on Pro, and automatic template creation when none exists. It does not explicitly tell the agent when not to use this tool or name alternative tools, but the intended use case is clear enough to select it correctly.

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