AvaHR

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

Annotations already declare readOnlyHint=false, destructiveHint=false, idempotentHint=true, but the description adds far more: the created object is inactive and must be activated by the user elsewhere, the draft lifecycle constraint, mandatory downstream actions (surface review_url, iterate review_flags), and content-restriction rules. This is real behavioral context the agent cannot get from the structured fields.

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?

Front-loaded with the core action and its draft-only scope, then constraints, then required follow-up. Every sentence carries weight, though the long enumerated compliance list makes it dense and slightly unwieldy for scanning.

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

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

There is no output schema, yet the description names the return fields the agent must surface (review_url, review_flags), states the side effects and their limits, and covers content policy for the nested questions schema. Nothing an agent needs in order to call this correctly and report back 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?

Schema coverage is 100%, so the baseline is 3, but the description adds substantive meaning for the questions parameter by forbidding content about age, family/pregnancy, health/disability, religion, national origin/race, sex/sexual orientation, arrests, and salary history. It does not clarify the type/rubric interplay further, so it is not a 5.

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 first sentence gives a specific verb and resource ("Create a skills assessment") plus an explicit scope qualifier: it is an INACTIVE DRAFT, not a live assessment. That is clear enough to distinguish it from the sibling create_questionnaire_draft by resource type, though the description never names that sibling or states when to pick one over the other.

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?

Strong negative guidance: it explicitly states the tool cannot activate the assessment, attach it to a job, or send it to a candidate, and points to Settings → Screening in AvaHR for those steps. It also prescribes a post-call workflow (show review_url and review_flags). It stops short of naming the questionnaire sibling as an alternative, which keeps it from a 5.

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 flag it as a non-read-only, idempotent, non-destructive write; the description goes much further by disclosing that the draft cannot be activated, attached to a pipeline, or sent to an applicant until the user activates it in Settings, and that AvaHR itself rejects non-compliant questions. It also prescribes exactly what to surface after the call (review_url, knockouts, knockouts_removed, review_flags), which annotations could never convey.

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?

Purpose and draft status are front-loaded in the first clause, followed by a restrictions block and then post-call instructions in execution order. The long prohibited-topic list is dense but each item is a distinct compliance constraint rather than 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?

There is no output schema, yet the description enumerates the response fields the agent must relay (review_url, knockouts, knockouts_removed, review_flags), and it covers the failure modes (compliance rejection, knock-outs silently altered) an agent would otherwise be blind to. For a 4-parameter creation tool that is as complete as it needs to be.

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, and the description earns above baseline by explaining the business consequence of knockout_answers (automatic rejection) and warning that they must be limited to lawful, requested requirements. It adds no new detail on name, category, description, or question ordering, which stays the schema's job.

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

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

States a specific verb and resource ("Create a screening questionnaire in AvaHR") and immediately pins down the lifecycle state it produces ("as an INACTIVE DRAFT"), which separates it from the sibling create_assessment_draft without the agent needing to open either 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?

Gives explicit conditional guidance on the riskiest sub-feature ("add them only when the user asks for them, for genuine job requirements") plus a hard list of topics never to ask about, so the agent knows when and when not to use knock-outs. It stops short of naming alternative tools or prerequisites for the surrounding hire workflow, so routing versus create_assessment_draft is left implicit.

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, non-destructive and closed-world, so the description earns credit for going beyond them: it discloses that resume and cover letter text is conditionally present only if the account enables it, and it warns that candidate_supplied_text is untrusted author-written content to be treated as data, not instructions. It does not cover error behavior for a missing or out-of-scope candidate_id.

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 short sentences, front-loaded with the core purpose and payload, followed by the conditional field and the safety note. Each sentence contributes something, though the prompt-injection sentence is slightly verbose in phrasing.

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

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

There is no output schema, and the description compensates by naming the returned fields and the conditional candidate_supplied_text field. For a read-only single-record fetch with full annotation coverage, nothing an agent needs in order to call it correctly appears to be 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 100% for the single candidate_id parameter, so the schema already documents the input fully. The description adds no syntax, format, or sourcing guidance for the ID, which matches the baseline of 3 when the schema carries the parameter burden.

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 ('Get one candidate') and enumerates the returned fields (contact details, job, stage, rating, tags), which lets an agent distinguish it from search_candidates by the singular, ID-based nature of the fetch. It stops short of naming the sibling tool explicitly, so the differentiation is inferred rather than stated.

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

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

Usage is only implied: the agent must already have a candidate_id and want a full record for one candidate. There is no explicit when-to-use, no exclusion pointing to search_candidates when only an ID is unknown, and no guidance for the not-found case.

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=true, idempotentHint=true, destructiveHint=false and a closed world, so the safety profile is fully covered. The description adds only that the full description text is included in the payload, which is modest extra context beyond the structured fields; nothing is said about error behavior for unknown ids.

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

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

A single front-loaded sentence with zero filler, and the notable payload detail ('including its full description') is placed where it will be read. It is efficient but borders on under-specified rather than maximally informative.

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 one-parameter read with full annotation coverage and no output schema, the description is adequate but thin: it does not indicate what job fields come back, whether missing/invalid ids error or return empty, or how it relates to list_jobs. These gaps are minor for such a simple tool but real.

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% and the single job_id parameter is documented with type and bounds, so the schema carries the load. The description adds no format, range, or sourcing detail about the id beyond what the schema already states, so baseline 3 applies.

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

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

States a specific verb and resource ('Get one job posting') and signals single-item retrieval, which implicitly contrasts with the sibling list_jobs. It never names the alternative explicitly, so an agent must infer the distinction from the singular phrasing.

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

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

Usage is only implied: 'one job posting' suggests fetching a known job by id rather than enumerating jobs, and the required job_id reinforces this. There is no explicit when-to-use, when-not-to-use, or pointer to list_jobs/search_candidates for the lookup-by-attribute case.

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, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description contributes the meaningful extra that only *active* members are returned (implying deactivated users are filtered out) and what fields come back, but says nothing about ordering, result size, pagination, or permission requirements. Reasonable value-add on top of a well-annotated tool, 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?

A single front-loaded sentence with no filler; the returned fields are mentioned in the same breath as the action. Nothing is padded or repeated.

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, side-effect-free list call with full annotation coverage and no output schema, the description supplies what an agent needs: what it lists and what each record contains. The only gap is result-set behavior (size, ordering, whether it spans the workspace), which is minor at this complexity.

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 takes zero parameters, so there is no parameter semantics to explain and the baseline applies. The description correctly implies no input is needed to produce the roster.

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 gives a specific verb and resource ("List the active members of your AvaHR team") and adds what each entry contains (titles, email addresses). It is clear on its own, though it never distinguishes this roster from the candidate/job listing siblings, and the slight drift between the name's "hiring team" and the description's "your AvaHR team" leaves scope mildly ambiguous.

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

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

Usage is only implied — an agent can infer this is the roster lookup for finding colleagues, but the description never states when to reach for it over the sibling list_* tools or any prerequisites (e.g. whether it is scoped to the caller's workspace or to a specific job's hiring team). No exclusions or alternatives are named.

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 readOnly, idempotent, non-destructive, and closed-world. Beyond those, the description adds genuine behavior: the 90-day cap, the default window, UTC handling, and the rule that supplying one end auto-extends the range 30 days.

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 tight sentences with the date-range rule front-loaded and the single-end fallback immediately after. No filler.

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

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

For a paginated read-only list with fully described parameters and no output schema, the description covers scope, defaults, and limits. The return shape is covered by the cursor parameter's schema description.

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 each parameter is already documented. The description adds only the derived behavior when from or to is omitted, which is useful but narrow; it does not elaborate on cursor or job_id 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 names a specific verb and resource ('List scheduled interviews') and scopes it to a date range. It is easy to distinguish from the create_/get_/search_ siblings, though it does not explicitly name an alternative listing 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?

It supplies the operational context an agent needs (UTC dates, 90-day maximum, 30-day default either side of today), but it gives no guidance on when to use this tool versus alternatives such as search_candidates.

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=true, destructiveHint=false, idempotentHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavioral context beyond that: results are returned 'newest first' and each row carries status, location, pay and candidate counts. It omits pagination behavior (that a cursor is needed to continue), which the schema covers but the description does not reinforce.

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, zero filler, front-loaded with what the tool returns before mentioning the filtering options. Every clause carries information: the ordering, the returned fields and the two filter axes.

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's payload summary ('status, location, pay and how many candidates each has') is doing real work and is appropriately included. For a five-parameter, all-optional read tool it is nearly complete; the only shortfall is that paging behavior and total-count semantics are left to the 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 100%, so all five parameters (query, cursor, status, page_size, posted_within_days) are already documented in the schema, including the enum meanings and defaults. The description only restates that status and title query can be used for filtering, adding no format or interaction detail beyond the schema. Baseline 3 applies.

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

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

States a specific verb and resource ('List job postings in your AvaHR account') and immediately distinguishes itself from get_job by describing a multi-item, ordered list with per-item summary fields. The ordering ('newest first') and payload summary make the tool's identity unmistakable among siblings like list_job_stages and list_pipelines.

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 through 'Filter by status or search titles,' which tells the agent two useful narrowing paths but never states when to prefer this tool over get_job for a single record or over search_candidates. No exclusions or alternative routing guidance is given, so the agent must infer the boundary between list and detail tools.

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=false, so the safety profile is covered. The description adds only the ordering guarantee ("in order"), which is a meaningful but small addition; it says nothing about pagination, empty pipelines, or whether archived stages appear.

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, front-loaded with the action and scope, with zero filler. The pipeline-copy sentence earns its place by differentiating from list_pipelines.

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-param read-only list tool with rich annotations and full schema coverage, this is nearly sufficient. The only modest gap is that ordering is mentioned but the shape of a returned stage is not, which is acceptable given there is no output 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?

There is a single parameter with 100% schema description coverage ("The job id."), so the schema carries the semantics. The description only reinforces that the id identifies one job and adds no format or constraint detail beyond that.

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

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

States a specific verb and resource ("List the hiring stages of one job"), scopes it to a single job, and the second sentence explains that stages belong to a per-job copy of a pipeline, which distinguishes it from the sibling list_pipelines.

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: call it when you have a job_id and need that job's stage sequence. The note about each job owning its own pipeline copy implicitly steers the agent away from list_pipelines, but no alternative is named and no exclusions are stated.

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=true, idempotentHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is fully covered. The description adds the useful clarification that these are templates rather than per-job stage data, but says nothing about result format, ordering, or comprehensiveness of the returned list.

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 with zero filler: purpose first, disambiguation second. Every clause 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 parameterless read-only list tool with no output schema, the description covers what the resource is and how it differs from the nearest sibling. It could note what each template entry contains (e.g., naming or stage composition), but that is a minor gap for such a 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 tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless tool applies. The description does not introduce any misleading filtering implications.

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

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

States a specific verb and resource ("List the hiring pipeline templates") plus the scoping detail that these are templates "new jobs are built from," which distinguishes it from job-specific stage data. An agent knows exactly what this returns without inspecting 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?

Explicitly routes the agent to the alternative: "For the stages of a particular job, use list_job_stages." That names the sibling and the condition that selects it, so the boundary between the two tools is unambiguous.

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 cover read-only, idempotent, non-destructive, and closed-world, so the description's added value is real: it discloses ordering ('newest first'), what the records contain (contact details, job, pipeline stage), and that results default to active candidates unless archived ones are requested via include_archived. It does not discuss pagination limits or that cursor errors behave, which keeps it from a 5.

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 tight sentences: the identification and result shape come first, the search/filter modes second. Every clause carries information and nothing is repeated.

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 takes on the job of describing the returned shape and does so (contact details, job, stage, ordering), and the six parameters are fully covered by the schema. Pagination behavior is only implicit in the curated cursor parameter, a minor gap for a listing 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 100%, so each parameter is already documented with defaults, bounds, and enum values. The description reinforces query and the two filter dimensions but adds no syntax, matching behavior, or default-page-size detail beyond the schema, so the baseline 3 applies.

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

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

The description uses a specific verb and resource ('Find candidates (applications)') and clarifies the result ordering, returned fields, and the two search modes (text query vs. job/stage filtering). It is clearly distinguishable from list_jobs and get_candidate, though it never names a sibling to route the agent away from.

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

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

It explains how to use the tool ('Search by name, email or headline; filter by job or stage group'), which implies the search-vs-listing choice, but gives no explicit when-not-to-use guidance or pointer to get_candidate for fetching a single candidate by ID.

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