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

The readOnlyHint annotation already signals safety, and the description adds relevant behavioral context: token identity is attributed to every recorded change, and caller identity may be forwarded by a gateway. This goes beyond the annotation without contradicting it.

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 the core action first, followed only by consequential detail about attribution and caller identity. There is no fluff or repetition of the title.

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 tool, the description conveys the main outputs: deployment capabilities, token owner, and caller identity. It does not specify exact response formatting or failure behavior, but the tool's simplicity and readOnly annotation make this 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 tool has zero parameters and the empty schema fully describes the input surface, so there is nothing for the description to add about parameter semantics. 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?

The description opens with a specific verb and resource: 'Verify the token and organization' and states what the tool reports (deployment capabilities, token owner, caller identity). This makes its role distinct from sibling data-operation tools like productive_get or productive_create.

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 clearly establishes the context — validating the Productive token and organization and surfacing what the deployment can do — so an agent knows to call it for connection/auth checks. It does not explicitly name alternatives or when-not conditions, but the absence of parameters and the verification purpose make the intended use obvious.

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?

Beyond the minimal readOnlyHint=false annotation, the description discloses two important behaviors: the operation is hashed and altered operations are refused, and the change must be shown to the requester before committing. This is valuable safety-relevant context for an agent.

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, purposeful sentences with no fluff. Purpose, usage constraint, and mandatory approval step are all front-loaded and directly actionable.

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 what matters most for a commit operation: exact object reuse, hash enforcement, and user approval. It does not describe the success response or explicitly name a prepare tool, but the workflow is sufficiently constrained for correct invocation.

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

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

The schema has 0% description coverage, and the single nested 'operation' parameter has no field-level documentation. However, the description compensates by instructing the agent to pass the exact object back and explaining the hash invariant, which materially reduces the risk of misuse despite lacking field-by-field semantics.

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

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

Description states a specific verb and resource: 'Execute a write that a prepare step staged.' This clearly identifies the tool as the commit step for a staged operation, distinguishing it from direct create/update/delete siblings by the staged-operation framing.

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 clear usage context: use after a prepare step, pass the operation object back exactly as returned, and show the change before committing. It does not explicitly name alternatives or say when not to use it, but the staged-operation workflow is unmistakable.

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 mark readOnlyHint=false, so the description carries the burden of explaining mutation nuance. It discloses the staging behavior, the validation-before-write behavior, and the fact that commit is required on certain resources. This is meaningful behavioral context beyond the 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?

Three sentences, no filler, with the core action first, then validation, then the exception case. Every sentence adds actionable 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 create tool with no output schema, it explains the essential invocation path, including when commit is required. It could say more about return shape or failure behavior, but the description and schema together cover the necessary 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 schema already describes attributes and relationships in detail, covering 2 of 3 parameters. The tool-level description adds no parameter-specific detail; `resource` remains minimally described, though it is self-evident and explained at a high level as 'any writable resource.'

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 exactly what it does: create a record on any writable resource. The explicit mention of productive_commit_operation distinguishes it from update/delete/list/get siblings. No ambiguity about the operation performed.

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?

Explains the resource-type condition that changes behavior: financial/administrative resources stage an operation rather than creating, and directs the agent to productive_commit_operation to finalize. It doesn't enumerate exclusions versus update/delete, but for a create tool this is sufficient 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?

Annotations already declare destructiveHint=true and readOnlyHint=false, so the description need not restate that. It adds non-obvious behavioral facts: deletion requires a separate switch and always returns a staged operation first. This goes beyond annotations and meaningfully sets expectations.

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 concise sentences with the core purpose first, followed by two high-value caveats. Every sentence earns its place; there is no filler or repetition of schema/annotations.

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 destructive tool with two simple parameters and no output schema, the description provides essential behavior: staged operation first, archive exception, and switch requirement. The main gap is parameter semantics, but the operational guidance is strong enough to make the tool safely invocable.

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%, and the description does not define the `resource` or `id` parameters. 'Delete a record' hints that resource is the record type and id is its identifier, but this is too vague to clarify valid resource types or how the id is used. The description adds minimal value beyond 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 states a specific action ('Delete') and resource ('a record'), making the tool's purpose clear. It also distinguishes the tool from create/update operations and explicitly references the archive alternative, differentiating it from a sibling behavior.

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 explicitly instructs the agent to check productive_describe_resource for an `archive` action before using delete, giving clear when-to-use-vs-alternative guidance. It also notes the requirement for a special switch beyond ordinary writes, which is a practical precondition for invocation.

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?

Beyond the readOnlyHint annotation, the description discloses a critical behavioral quirk: custom-field values are keyed by numeric id, not display name, and using a name as a key is silently accepted with 200 but stored nowhere. This is exactly the kind of non-obvious behavior that prevents an agent from making a subtle mistake.

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 purpose and return fields, then adds the essential behavior warning. Every sentence 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 read-only listing tool with one optional parameter, the description is complete: it names the resource, lists the output components, and flags the keying gotcha. The absence of an output schema is mitigated by the explicit statement of what is returned, and the readOnlyHint annotation covers safety expectations.

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

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

The input schema has 100% description coverage and already explains appliesTo in detail, including the 'employees' example and the instruction to call without an argument first. The tool description itself adds no additional parameter semantics beyond the schema, so 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 uses a specific verb ('List'), names the resource ('organization's custom fields'), and specifies what is returned: id, object, and options. It clearly distinguishes this from siblings like productive_describe_resource, which would describe a resource's schema rather than enumerate custom fields.

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 its usage context clearly: call it to list custom fields and understand how values are keyed. The input schema adds explicit guidance to call without an argument first and then pick from appliesToValues, which is practical usage direction. It does not explicitly name alternative tools or state when not to use it, so it stops short of 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 already declare readOnlyHint=true, so the safety profile is covered. The description adds valuable behavioral context: output is derived from Productive's own OpenAPI document and includes specific contract elements, plus a warning about write no-ops that goes beyond the annotation.

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 dense but efficient: one sentence enumerates the full contract contents, and a second short sentence delivers a high-impact usage warning. Every phrase contributes meaning, with no filler or repetition of the 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?

For a simple one-parameter read-only introspection tool, the description fully specifies what output the agent should expect and when to call it. The lack of an output schema is compensated by the detailed enumeration of returned contract components.

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 schema already documents the single 'resource' parameter with examples. The description adds no additional syntax, validation, or format details for the parameter, so it stays at the baseline where the schema does the heavy lifting.

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 precise verb-object relationship: it provides 'the exact contract for one resource' and enumerates the concrete contents such as filter fields, operators, sort keys, and writable attributes. This clearly distinguishes it from siblings like productive_get, productive_list, and productive_describe_custom_fields.

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

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

The description explicitly tells the agent to 'Read this before writing' and contrasts a successful write with 'a 200 that changed nothing,' giving a clear trigger for use. It does not explicitly name alternative tools or when not to use it, but the intended context 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?

The readOnlyHint annotation already establishes safety, and the description adds meaningful behavior: optional eager-loading of related records in the same call. It does not explain raw mode or default include behavior, but the core read semantics are transparent and align with 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, well-structured sentence that front-loads the core purpose and then adds the key optional behavior. There is no redundant or filler language.

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 and no parameter descriptions, the description is too sparse to fully support correct invocation. The agent still has to guess what 'resource' values are valid, what 'raw' does, and what the response shape looks like. The relationship-include guidance is helpful but not enough.

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 all four parameters. It explains the purpose of 'id' and loosely hints at 'include', but it never clarifies 'resource' or 'raw', which are both undocumented in the schema and the description. This is a significant 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 uses a specific verb ('Read') and clear object ('one record by id'), which distinguishes it from sibling tools like productive_list and productive_create. The added phrase about pulling related records also separates it from naive relationship-stub traversal.

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 conveys when to use the tool: when you need a single record by id and optionally want related records in one call rather than following stubs. It does not explicitly exclude alternatives like productive_list for multiple records, so it stops short of full when-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?

The description adds significant behavioral detail beyond the readOnlyHint annotation: results are flattened out of JSON:API, attributes are hoisted, included records are inlined, and responses include total and nextPage so the agent understands pagination is partial. It also clarifies that report resources return aggregated rows rather than records. This goes well beyond the minimal safety signal.

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

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

The description is concise at three sentences and front-loads the core purpose. Each sentence provides meaningful information, though the phrase 'Also how the 26 report endpoints are read' is slightly awkward and could be streamlined. Overall it is efficient without 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?

With no output schema, the description explains the return shape well: flattened records, inlined relationships, total, and nextPage. It also covers the special report behavior and aggregated rows. For a complex 7-parameter listing tool with 132 possible resources, this is sufficiently complete to guide correct invocation.

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

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

Schema description coverage is 86%, so the input schema already documents most parameters well. The description adds a little context around group for report endpoints, but it mostly summarizes capabilities like filtering and paging rather than meaningfully extending the schema's parameter documentation. Baseline 3 is appropriate because the schema carries the parameter-semantic 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 clearly states the tool lists any Productive resource with filtering, sorting, includes, and paging. It also explicitly handles the special behavior of the 26 report endpoints, distinguishing this from siblings like productive_get and productive_search_capabilities. The verb 'List' and resource scope are 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 gives clear guidance on when to use this tool, including the specific instruction to use resource 'reports/time_reports' with group for aggregated report rows. It provides the main usage context but does not explicitly enumerate exclusions or alternatives such as 'use productive_get for a single record.' The context is clear enough that an agent can choose correctly in most cases.

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

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

Annotations only provide readOnlyHint=false, so the description carries the behavioral burden. It discloses two non-obvious behaviors: bulk_* actions operate on every record the filter matches, and they refuse to run without an explicit filter. The schema also surfaces that Productive answers 200 and silently ignores unknown attributes, adding important behavioral context beyond the annotation.

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 sentences with no filler. It front-loads the core purpose, then immediately covers the most dangerous edge cases (bulk scope and filter requirement), and ends with a useful discovery pointer. Every sentence 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 complex 5-parameter tool with nested filter objects and no output schema, the description and schema together cover the essential invocation details: valid action classes, bulk semantics, filter requirements, field validation, and discovery via productive_describe_resource. The only notable gap is the lack of any mention of what the response looks like or error behavior beyond the silent-attribute-ignore note, which is a minor omission for an action-triggering 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 description coverage is roughly 80%, and the schema already provides rich semantics for filters, attributes, and id. The description adds the bulk-vs-single distinction and the explicit-filter requirement, which complements the filters parameter. Given this high schema coverage, the baseline of 3 is appropriate; the description does not need to re-document 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 names a specific verb ('Run') and a clear resource class ('one of Productive's named verbs'), then lists concrete examples: archive, restore, close, open, approve, reject, copy, finalize, send, reposition. It also distinguishes single-record actions from bulk_* actions, so the tool's purpose is unmistakable and well differentiated from the sibling CRUD 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 clearly states that bulk_* actions require an explicit filter and calls out productive_describe_resource as the way to discover which actions a resource supports. It does not, however, give explicit when-not-to-use guidance against siblings like productive_update or productive_delete, so it falls short of 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?

With readOnlyHint=true already in annotations, the description adds useful behavioral context: it returns matching tools, workflow guides, and resources along with the operations they support. It also discloses the important quirk that resource names may not match user expectations. No contradiction with 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?

Three sentences, front-loaded with the core purpose, and every sentence adds value: what it finds, where to start, and what it returns. The naming examples are illustrative without being verbose.

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

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

For a read-only search tool with only two parameters and no output schema, the description covers purpose, scoping context, and return categories well. It does not detail result shape or empty-result behavior, but those are not critical for selecting and invoking 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?

The description reinforces that 'query' is a subject to search for, but the schema already covers that with examples. The 'limit' parameter is not described in the description, and with only 50% schema description coverage, the description does not fully compensate. The parameter is simple enough that the gap is moderate rather than severe.

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 ('Find') and resource ('resource, tool or guide for a subject') and clearly distinguishes this as the starting point for discovery. It explains the tool's role relative to siblings by highlighting Productive's naming conventions, so an agent knows this is a search/capability lookup, not a data operation.

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?

'Start here' explicitly tells the agent when to use this tool, and the mention of Productive's non-obvious naming ('a budget is a deal') explains why guessing would waste calls. It does not name alternative sibling tools or state when not to use it, but the contextual guidance is clear enough.

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 only readOnlyHint=false in annotations, the description carries the full burden of behavioral disclosure. It clearly reveals that hours are converted to minutes, the service is derived from the task when absent, and the person is resolved from the authenticated caller despite a shared server token. This is specific and valuable transparency.

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

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

Three sentences, each earning its place: the first states the action, the second explains the critical unit conversion, and the third clarifies lookup defaults and authentication behavior. It is dense without being bloated, and the essential action 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 an 8-parameter tool with no output schema, the description covers the core call flow well: what to log, how units are handled, which IDs can be omitted, and how resolution works. It does not describe the return value or what happens when conflicting inputs like hours and minutes are both supplied, but these are minor gaps given how much is already explained.

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 88%, so the schema already documents most parameters. The description adds real value by explaining the hours-to-minutes conversion, the distinction between service and task, and the fallback resolution behavior for serviceId and personId. It does not explain every edge case, such as providing both hours and minutes, but it meaningfully supplements 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 opens with a specific verb and resource: 'Log a time entry.' It goes beyond the title by explaining the key behavior that makes this tool distinct from generic create/list tools: it avoids manual lookups and handles conversions, making the intent unmistakable.

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 practical context: service can be omitted and is resolved from the task, person can be omitted and is resolved from the caller. This tells an agent when it can avoid passing certain parameters, though it does not explicitly name alternatives or state when not to use the tool.

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

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

With only readOnlyHint=false provided by annotations, the description carries a meaningful behavioral burden and does well: it discloses PATCH semantics, confirms omitted fields are retained, and warns that certain resources return a staged operation instead of writing. It does not cover permissions or reversibility, but it adds real behavioral facts beyond 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 short and front-loaded with the key PATCH behavior. The first sentence duplicates the title, which costs a little, but every other sentence carries useful operational meaning without padding.

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 PATCH semantics and the staged-operation caveat, but it does not explain what a staged operation should be followed by, especially given the sibling productive_commit_operation. There is also no output schema and the description does not say what a normal update returns, and relationships remain undocumented. This leaves the agent needing to infer important follow-up behavior.

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 low at 25%, and the description does add value for the attributes parameter by explaining that omitted attributes keep their values. However, it gives no semantic guidance for resource, id, or relationships, and the custom_fields nesting behavior lives only in the schema, not the description.

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 on a record and immediately clarifies PATCH semantics, which distinguishes it from read-only siblings like productive_get and productive_list. It is slightly repetitive with the title but unambiguous about the operation's purpose.

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

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

The description gives useful context: partial updates preserve omitted attributes, so no full resend is needed, and financial/admin resources return staged operations instead of writing. However, it does not explicitly say when to choose this over productive_create, productive_delete, or productive_run_action, so usage versus alternatives is mostly implied.

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