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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds a vague hint of multi-instance scope ('fanned out across instances') but doesn't disclose additional behaviors like output aggregation or performance implications. It doesn't contradict annotations, and the annotation coverage reduces the burden, so a middling score is appropriate.

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

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

The description is extremely concise (one phrase), but it's cryptic and lacks structure. It doesn't front-load a clear purpose; instead, it uses jargon ('partner-network sweep') that obscures meaning. Conciseness is present but at the expense of clarity, making it only minimally acceptable.

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

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

Given the tool's complexity (multi-instance, aging direction, top-partner filtering) and the availability of an output schema, the description should explain the aggregation behavior and scope. It fails to describe what 'fanned out' means operationally, how instances are selected, or what the response contains. The schema and annotations help, but the description leaves critical gaps 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?

Schema coverage is 100% — all four parameters (as_of, direction, instances, top_partners) have detailed descriptions. The description adds no extra meaning about parameters, so the baseline of 3 applies; it neither enriches nor harms parameter understanding.

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

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

The description uses cryptic language like 'fanned out across instances' and 'the partner-network sweep' without specifying that it's a read-only AR/AP aging query across multiple instances. It doesn't clearly state the resource or action, making it hard to distinguish from sibling tools like receivable_payable_aging or accounting_health_summary.

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

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

No guidance is provided on when to use this tool versus alternatives (e.g., single-instance aging tools or other cross-instance queries). The description gives no context for selecting it based on use case, prerequisites, or exclusions.

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

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds no extra behavioral context, such as the meaning of 'open' or that it only returns counts without detail, and it says nothing about the optional 'instance' parameter's effect on results.

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

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

The description is a single sentence that conveys the core purpose without padding. It is appropriately terse and front-loaded, though it could benefit from a bit more structure or a second sentence for context.

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

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

Given the presence of an output schema, the return format may be documented there, but the description remains incomplete in core areas: it does not explain the 'instance' parameter, does not clarify the tool's single-instance scope versus siblings, and offers no usage guidance. The description is too minimal to be fully self-sufficient.

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 one optional parameter 'instance' with no description, and the schema description coverage is 0%. The tool description also fails to explain what 'instance' refers to or how it affects the output, leaving the agent without essential information for correct invocation.

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

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

The description clearly states the tool provides receivable/payable item counts and draft invoice backlog, identifying its resource and action. However, it does not explicitly distinguish it from sibling tools like 'receivable_payable_aging' or 'accounting_health_across_instances', which likely cover related but different scopes.

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 no guidance on when to use this tool versus alternatives. It does not mention that it is likely for a single instance versus across instances, nor does it note any prerequisites or exclusions. The user is left to infer usage from the name alone.

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

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

The description says 'Read-only', which is consistent with the annotations (readOnlyHint=true, destructiveHint=false, idempotentHint=true). It adds behavioral context by stating the operation 'fans out across instances' and produces 'combined grand totals', which is beyond what annotations provide. However, it does not disclose other behavioral aspects like potential latency, failure semantics, or how 'instances' is interpreted by default.

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

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

The description is a single concise sentence with no filler words. It front-loads the key qualifier 'Read-only' and immediately conveys the core behavior. It is appropriately sized for the information it delivers, though it sacrifices detail for brevity.

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

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

For a tool with cross-instance fan-out, five parameters, and no parameter descriptions, the one-line description is insufficient. It does not mention how instances are specified, what measures or group_by mean, or how domains are applied. An output schema exists, but the description alone leaves too many operational gaps for an agent to use the tool confidently.

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 explain any of the five parameters (model, domain, group_by, measures, instances). The only hint is the phrase 'across instances', but it does not clarify parameter formats, defaults, or relationships. With no parameter documentation in either schema or description, the agent is left to guess 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?

The description clearly indicates the tool performs an aggregation operation ('aggregate') that is 'fanned out across instances' with 'combined grand totals', distinguishing it from single-instance aggregation tools like aggregate_records and from cross-instance search tools like search_across_instances. However, it is phrased as a noun phrase rather than an explicit verb+resource construction, which slightly reduces clarity.

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 is for cross-instance aggregation scenarios ('across instances', 'combined grand totals'), but it does not explicitly state when to use this tool instead of alternatives or when not to use it. Sibling tool names provide context, but the description itself offers no direct comparison or exclusion.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds a bit of behavioral context by mentioning the version-specific read_group methods, but does not disclose other traits like error behavior or performance implications.

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

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

The description is a single sentence that front-loads the purpose. It is concise, but could be slightly more structured to separate the purpose from the implementation 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 9 parameters and no inline parameter explanations, the description is insufficient for an agent to use the tool correctly. The presence of an output schema partially compensates for return value documentation, but parameter semantics are critically lacking.

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% for 9 parameters. The description only hints at group_by and measures (via 'sum/count'), but does not explain key parameters like lazy, domain, order, or instance. This lack of detail hinders correct parameter usage.

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 aggregates Odoo records server-side using Postgres groupby/sum/count. It specifies the underlying methods (formatted_read_group for Odoo 19+, read_group for earlier versions), which distinguishes it from sibling tools like search_records or read_record that return raw records.

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

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

The description implies the tool is for aggregation tasks, but does not explicitly state when to use it versus alternatives. It lacks guidance on prerequisites, when not to use, or comparison with siblings like aggregate_across_instances.

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, and destructiveHint=false, so the description adds value by specifying the classification output (no_action, needs_review, needs_script) and fix suggestions. 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?

Single clear sentence with no wasted words. Front-loaded with the verb and resource, immediate understanding of functionality.

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 an output schema present and annotations covering safety, the description is largely complete. However, missing parameter semantics slightly reduces completeness for a tool with 3 parameters and zero schema descriptions.

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 0% and description provides no additional meaning for any of the 3 parameters (log_text, source_version, target_version). The agent must rely solely on parameter names, which are self-explanatory but insufficient for precise invocation.

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

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

Description clearly states the tool classifies Odoo install/update log errors into a specific migration worklist with categories and fix suggestions. It uniquely identifies the tool's function and resource, distinguishing it from siblings like upgrade_risk_report.

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

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

No explicit guidance on when to use this tool versus alternatives or when not to use it. The description implies usage for Odoo log analysis but lacks explicit context or exclusions.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety expectations. The description adds 'validated,' implying some checking of conditions, but does not explain other behavioral aspects like whether it returns a string or list, or any constraints. Since annotations cover the key safety traits, the description adds minimal extra behavioral clarity.

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

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

The description is a single, compact sentence with no filler. It efficiently conveys the core action and input. Every word contributes meaning, making it appropriately concise.

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

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

The tool has three parameters, one required, and an output schema, yet the description does not explain any of the parameters beyond a vague reference to conditions. It lacks details on how the logical operator or fields metadata influence the output. Even with annotations and an output schema, the description is incomplete for a tool that constructs complex domains.

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 explaining parameters. It only mentions 'structured conditions,' which vaguely maps to the 'conditions' parameter, but completely omits the 'fields_metadata' and 'logical_operator' parameters. Without any elaboration on how these parameters affect domain construction, parameter semantics are severely under-explained.

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's purpose: 'Build a validated Odoo domain from structured conditions.' The verb 'build' and resource 'Odoo domain' are specific, and the mention of 'validated' adds a unique aspect. It distinguishes from sibling tools like search_records, which perform queries, whereas this constructs a domain filter.

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 no guidance on when to use this tool versus alternatives. It does not mention prerequisites, when it is appropriate to build a domain, or suggest any alternative tools. The single sentence is purely declarative without usage context.

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

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, providing a clear safety profile. The description adds minimal behavioral context beyond stating the purpose; it does not discuss performance, caching, or side effects.

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

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

The description is a single concise sentence that is front-loaded with the verb and resource. It is efficient and avoids unnecessary words.

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

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

With 3 parameters, an output schema, and clear annotations, the description provides adequate context. It covers the primary purpose but could mention the output structure or typical use cases briefly.

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 input schema already documents all parameters. The description does not add meaning beyond the schema; it merely restates the tool's purpose.

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

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

The description clearly states the verb 'Report' and the resource 'expected modules, models, and safe discovery calls for a business pack'. It distinguishes this tool from siblings like health checks or search tools by its specific reporting scope.

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

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

No guidance is provided on when to use this tool versus alternatives, when not to use it, or any prerequisites. The description simply states what it does without contextual usage advice.

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

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

The description directly contradicts the annotation readOnlyHint: true. Cancelling a task is a mutating action, not read-only. The description adds no behavioral context beyond the basic action, and it does not explain side effects like whether cancellation is irreversible or what happens to the task's status. This is a serious inconsistency 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 a single concise sentence with no unnecessary words. It is front-loaded with the core action and resource. There is no redundancy or filler.

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

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

Given the tool's simplicity (one parameter) and the existence of an output schema, the description could be minimal, but it omits critical usage context and contradicts the annotations. It fails to provide guidance on when to cancel tasks or what the expected outcome is, making it incomplete for an agent to use reliably.

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

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

The description provides no information about the task_id parameter beyond its name. Schema description coverage is 0%, so the description must compensate, but it does not explain how to obtain a task_id or what format is expected. The single parameter is self-explanatory by name, but the description adds zero semantic value.

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's function: cancel a pending or running background task. It uses a specific verb ('cancel') and a specific resource ('background task'), and it distinguishes itself from sibling tools like submit_async_task, get_async_task, and list_async_tasks by being the cancellation 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 gives no guidance on when to use this tool versus alternatives. It does not mention checking task status first (e.g., via get_async_task), nor does it state that tasks should be cancelled only when they are no longer needed. There is no discussion of prerequisites or exclusions.

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

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

Annotations already indicate write and destructive behaviors; the description adds the approval flow context beyond annotations, but does not fully disclose side effects, error conditions, or the exact effect when the environment variable is not set. It offers some transparency but not exhaustive.

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, both front-loaded. The first sentence states the core purpose, the second introduces the approval mode. No extraneous information. 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?

Given the tool's complexity (10 parameters, destructive annotation, approval flow), the description covers the dual-mode usage but lacks details on parameter semantics, error handling, and exactly what the tool returns (though output schema exists). It is minimally complete but leaves significant gaps.

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

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

With 0% schema description coverage and 10 parameters, the description provides no additional meaning for any parameter. The agent must rely on parameter names alone, which is insufficient for correct usage. The description should have elaborated on key parameters like model, record_id, approval, etc.

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

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

The description clearly states the action ('Post a chatter message') and the target resource ('mail.thread record'). This is a specific verb+resource combination that distinguishes it from all sibling tools, none of which perform chatter posting.

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 context on the two modes (with approval token vs. direct bypass) but does not explicitly state when not to use this tool or name alternative tools. It gives a practical condition (environment variable) but lacks comprehensive guidance on alternatives or prerequisites.

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

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds value by listing specific quality check categories, but does not disclose behavior like performance impact or error handling. Given the strong annotation coverage, the description provides adequate additional context.

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

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

A single, front-loaded sentence that efficiently communicates the tool's purpose and scope. No unnecessary words, and it includes the key verb 'run', resource 'Odoo model', and constraints 'read-only' and specific check types.

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?

Despite having an output schema, the description fails to explain how to use the five parameters effectively or what to expect from the checks. For a tool with no schema parameter descriptions, this is insufficient for an agent to craft correct invocations.

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

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

Schema description coverage is 0%, so the description must compensate. It mentions 'one Odoo model' but does not explain parameters like 'checks' (what string values?), 'instance', 'key_fields', or 'sample_limit'. Users lack guidance on configuring these parameters beyond their 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 clearly states the tool runs read-only data-quality checks on one Odoo model, listing specific check types (duplicates, missing values, etc.). It distinguishes itself from sibling tools like 'aggregate_records' or 'diagnose_access' by focusing on data quality and read-only 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?

No explicit guidance on when to use this tool versus alternatives, nor any prerequisites or exclusions. While the purpose implies usage for data quality checks, a mention of when not to use it (e.g., for write operations) would improve clarity.

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 non-destructiveness; the description confirms the diagnostic nature but adds no further behavioral details (e.g., output volume, execution cost).

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 single-sentence description is concise, front-loaded with the verb and resource, and contains no redundant information.

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

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

For a 9-parameter tool with full schema and an output schema, the brief description is mostly adequate, though it could briefly mention the nature of the diagnostic output (e.g., 'returns ACL analysis').

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 description does not need to explain parameters; it adds no extra meaning beyond what the schema already provides, meeting the baseline.

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

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

The description clearly states the verb 'diagnose' and the resource 'ACL and record-rule visibility for an Odoo model', making the tool's specific purpose distinct from sibling diagnostic tools.

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

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

No guidance is provided on when to use this tool versus alternatives like diagnose_odoo_call or when to avoid it; the description lacks context for decision-making.

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, and destructiveHint=false. The description adds 'without executing it', reinforcing safety but providing no additional behavioral details beyond what annotations 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?

The description is a single, concise sentence that immediately conveys the tool's purpose. No unnecessary words or information.

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

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

Given the tool has 10 parameters and an output schema, the description is brief but sufficient to understand the core functionality. However, it could briefly mention that the tool analyzes potential issues without side effects, which would improve completeness.

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

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

Schema description coverage is 100%, so baseline is 3. The tool description adds no extra meaning beyond the parameter descriptions in the schema (e.g., it doesn't explain how 'metadata' or 'transport' affect diagnosis).

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

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

The description explicitly states 'Diagnose an Odoo model call without executing it', clearly defining the action (diagnose), the resource (Odoo model call), and the key constraint (no execution). This distinguishes it from sibling tools like 'execute_method' which performs actual execution.

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

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

The description implies usage for diagnosis, but does not provide explicit guidance on when to use this tool versus alternatives (e.g., 'execute_method', 'preview_write'). There is no mention of use cases or exclusions.

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

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

Annotations already indicate destructiveHint=true, but the description adds no details about what gets destroyed, permissions required, or failure behavior, failing to add value 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 single-sentence description is concise but overly brief, sacrificing essential information for brevity.

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

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

Given the tool's complexity (nested object, confirm parameter, output schema exists), the description is too minimal to adequately guide an agent, missing return value expectations and parameter specifics.

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

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

With 0% schema description coverage, the description provides no guidance on the 'approval' object or 'confirm' boolean, leaving the agent without necessary parameter 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?

The description 'Execute a previously previewed and confirmed standard write' uses a specific verb (execute) and resource (approved write), clearly distinguishing it from sibling tools like 'preview_write' and 'validate_write'.

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

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

The description implies the tool should be used after preview and confirmation, but it does not explicitly state when not to use it or provide alternatives among siblings like 'validate_write'.

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 flag destructiveHint: true and readOnlyHint: false, indicating the tool can modify data. The description adds no behavioral context beyond the annotations—no mention of side effects, permissions required, or safety considerations. Given the annotations, the description should at least reinforce the destructive nature or clarify when destruction might occur.

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

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

The description is a single short sentence, which is concise but not optimally structured. It could be expanded with key information (use case, restrictions) without becoming verbose. Front-loads the core action but omits important guidance.

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?

Despite having an output schema, the description fails to explain return values, error behaviors, or side effects. For a destructive, open-world tool with 5 parameters and many siblings, this is insufficient. The description should at least mention safety warnings or when to prefer this over similar tools.

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

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

The input schema has 100% description coverage, with each parameter (model, method, args, kwargs, instance) already described. The tool description adds no additional meaning beyond what the schema provides. Per the rubric, baseline is 3 since schema coverage is high.

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 'Execute a custom method on an Odoo model' clearly identifies the action (execute) and the resource (custom method on Odoo model). It distinguishes from siblings like 'execute_approved_write' (specific to writes) and 'diagnose_odoo_call' (testing). However, it could be more precise about what constitutes a 'custom method' versus blocked methods (create/write/unlink), which are noted only in the parameter schema.

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

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

No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, comparable tools (e.g., 'execute_approved_write' for safe writes, 'read_record' for reading), or scenarios where this tool is inappropriate. The blocked methods are only stated in a parameter description, not in the tool description.

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, and destructiveHint=false. The description adds no behavioral details beyond what annotations provide, so baseline score applies.

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

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

Single sentence is too brief for a tool with 6 parameters and an output schema; it lacks necessary details and qualifies as under-specification rather than conciseness.

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?

Despite having an output schema and multiple parameters, the description omits how the classification works, how parameters affect results, and what the output contains. Incomplete for the tool's 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?

Schema description coverage is 0%, and the description does not explain any parameter purpose, format, or interaction. Parameters like 'available_fields' and 'business_context' are left entirely undefined, severely hindering correct invocation.

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 uses a specific verb 'classify' and resource 'Odoo requirements into fit/gap implementation buckets', clearly distinguishing it from sibling tools like 'read_record' or 'aggregate_records' which do not perform classification.

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?

Description provides no guidance on when to use this tool, prerequisites, or alternatives. It only states what it does, leaving the agent to infer usage context.

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

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

Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds that it is a preview without network access, which reinforces the safe, non-destructive nature. However, it does not disclose any additional behaviors like potential formatting or limitations.

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

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

The description is a single, well-front-loaded sentence with all critical information at the beginning. No extraneous words or repetition.

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

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

The tool has 7 parameters and an output schema, but the description ignores both. It does not explain what constitutes a 'JSON-2 request preview' or what the returned payload looks like, leaving the agent underinformed.

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

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

Despite 0% schema description coverage, the description adds zero information about the 7 parameters. Terms like 'model', 'method', 'base_url' are left unexplained, so the agent must infer from names alone.

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 specifies the verb 'Build' and the object 'JSON-2 request preview', and adds the key qualifier 'without network access', distinguishing it from sibling tools like 'diagnose_odoo_call' which likely involve actual network calls.

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 no guidance on when to use this tool versus alternatives (e.g., diagnose_odoo_call or execute_method). It lacks any mention of use cases, prerequisites, or exclusions.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds the behavioral context of polling a background task's status and result, but it does not disclose any additional traits such as behavior when the task is not found, retry logic, or output specifics. Since annotations carry the safety burden, the description provides minimal but adequate transparency 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 a single concise sentence that is front-loaded with the action 'Poll' and clearly states the resource. It contains no unnecessary words and is easy to parse.

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 simple structure (one parameter), the presence of an output schema, and annotations covering safety, the description is largely complete. It accurately conveys the tool's purpose and operation. It lacks explicit workflow context (e.g., referencing submit_async_task), but for a simple polling tool, the description is sufficiently comprehensive for an agent to understand and invoke it.

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 mention parameters at all. The only parameter, task_id, is self-explanatory from its name and type, but the description does not compensate for the lack of schema descriptions by explaining how to obtain or use the task_id, leaving the agent to infer its meaning from context.

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 "Poll a background task's status and result" uses the specific verb 'Poll' and clearly identifies the resource (background task's status and result). It distinguishes from sibling tools like submit_async_task, cancel_async_task, and list_async_tasks by indicating a targeted retrieval of a single task's status and result.

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

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

The description implies usage for checking the status of an asynchronous background task, but it does not explicitly state when to use this tool versus alternatives such as list_async_tasks, nor does it mention exclusions. It provides no direct guidance on the workflow (e.g., after submitting a task) or when to prefer another 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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the description adds no extra behavioral context beyond what annotations provide.

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

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

Single sentence with no unnecessary words, though it could be more structured or front-loaded with key information.

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

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

Given 5 parameters and an output schema, the description is too minimal; it fails to explain how parameters affect results or what the output contains.

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 0% and the description does not explain any of the 5 parameters, such as 'model', 'instance', 'relevance', 'max_fields', or 'field_names', leaving the agent uninformed.

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

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

Description clearly states the tool retrieves field metadata for a specific Odoo model, distinguishing it from sibling tools like list_models or search_records.

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

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

No guidance on when to use this tool versus alternatives, such as reading a record's fields or exploring model relationships.

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, and idempotentHint=true. The description adds minimal behavioral context beyond 'bounded', leaving the precise scope unclear. 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?

A single, concise sentence front-loads the core action. No extraneous text, and every word is meaningful.

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?

While the output schema exists (reducing need to describe returns), the term 'bounded profile' is vague. The description could clarify what is included (e.g., version, user info). Adequate but not excellent.

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?

All three parameters have descriptions in the input schema, achieving 100% coverage. The tool description does not add extra meaning beyond what the schema already provides.

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

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

The description uses a specific verb ('Read') and resource ('bounded profile of the connected Odoo environment'), clearly distinguishing this tool from sibling tools like 'get_model_fields' or 'list_instances'.

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

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

No guidance is provided on when to use this tool versus alternatives such as 'health_check' or 'list_models'. An agent receives no context about prerequisites or preference conditions.

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 indicate readOnlyHint, idempotentHint, and non-destructive. The description adds 'non-secret runtime safety posture', clarifying scope but not revealing additional behavioral traits beyond 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?

Single sentence, concise, no redundant words. Every part contributes to clarity.

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

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

Given zero parameters, rich annotations, and an output schema, the description is sufficient. It omits output details but output schema compensates. No gaps.

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

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

No parameters exist, so schema coverage is 100%. The description does not need to add parameter meaning. Baseline 4 is appropriate for zero-param tools.

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

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

The description clearly states the tool reports the server's non-secret runtime safety posture, a specific verb+resource. It distinguishes from health-related siblings like accounting_health_across_instances which focus on different domains.

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

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

No explicit guidance on when to use this tool versus alternatives. The purpose is implied but no when-not or sibling differentiation is provided, leaving the agent to infer usage context.

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

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

With annotations readOnlyHint=true, idempotentHint=true, and destructiveHint=false, the description adds context by specifying the operation is 'local' and builds a BM25 index, suggesting side effects are confined to the local session. This clarifies that while it's a read operation, it sets up a searchable structure. It does not contradict any annotation and adds useful nuance about scope, though it could mention memory/performance implications.

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

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

The description is a single, front-loaded sentence of 13 words, free of fluff. Every word earns its place, immediately conveying the action and outcome. It is perfectly sized for quick consumption.

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

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

The tool has 6 parameters (moderate complexity) and an output schema exists. The description covers the overall purpose but omits any detail about parameters, return value structure, or edge cases like what happens with replace=true. Given the annotations already declare safety, this is adequate for a basic understanding but leaves gaps in knowing how to set up the index correctly, making it minimally complete.

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

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

Schema description coverage is 0% and the description makes no mention of any parameters. All six parameters (limit, model, domain, fields, replace, instance) are left unexplained. Since the schema provides no defaults or descriptions, the description needed to compensate but entirely fails to clarify what these parameters do or how they interact. This leaves the agent guessing on parameter usage.

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 'fetch' and 'build' with concrete resources: 'a bounded slice of records' and 'a local BM25 knowledge index'. This clearly distinguishes it from sibling tools like search_knowledge and knowledge_stats, as it focuses on indexing rather than querying. It tells exactly what the tool does.

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

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

There is no guidance on when to use this tool instead of alternatives. It does not mention exclusions, prerequisites, or compare to similar tools like search_knowledge or list_instances. The description only states the action without contextual 'when' or 'when not to use', so it fails to help an agent decide between this and related 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?

Description adds context beyond annotations by specifying what is inspected (relationships and required field metadata). Annotations already show readOnlyHint true, destructive false, idempotent true, so the description complements well.

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

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

Single sentence with no wasted words. Purpose is front-loaded and clear.

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

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

Given 6 parameters and no schema descriptions, the description is insufficient. It does not explain parameter usage or return value (though output schema exists). Leaves agent with significant gaps.

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

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

Schema description coverage is 0% and the description does not explain any of the 6 parameters (model, fields_metadata, include_readonly, etc.). The agent must infer meaning solely from parameter names and types.

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

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

Description clearly states the tool inspects model relationships and required field metadata, distinguishing it from siblings like get_model_fields which only gets fields. However, it could be more explicit that it is read-only.

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

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

No guidance on when to use this tool vs alternatives like get_model_fields or search_records. The description does not mention appropriate contexts or exclusions.

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

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

Annotations declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, which already cover safety. The description adds that it reports 'local' knowledge index, which is useful context, but does not elaborate on what exactly is included (e.g., budget specifics, whether it aggregates across instances). No contradiction.

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

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

The description is a single concise sentence that states exactly what the tool does. No fluff, perfectly 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?

Complexity is low with 0 parameters and a clear purpose. The output schema exists, so return values are presumably documented there. The description covers the main function (sizes and budget) but could mention whether it's instance-specific or aggregated, though 'local' hints at instance-level. Overall complete 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?

The tool has 0 parameters, so schema coverage is 100% trivially. The description adds no parameter details because none exist. Baseline for 0 params is 4, and the description is adequate.

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 reports local knowledge index sizes and document budget, which is specific and distinguishes it from siblings like index_knowledge and search_knowledge. It lacks a verb like 'get' but the purpose is clear.

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

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

The description implies usage for checking knowledge index stats, but does not explicitly state when to use this tool versus alternatives (e.g., index_knowledge or search_knowledge). No exclusions or contextual triggers are provided.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is established. The description adds the newest-first ordering, which is useful, but it does not disclose other behaviors like result limits, pagination, or what 'recent' means. This goes slightly beyond annotations but is minimal.

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

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

The description is a single, concise sentence that states the action, resource, and ordering. It is front-loaded and contains no redundant information.

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

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

For a zero-parameter list tool with an output schema and good annotations, the description is adequate. The only slight gap is the vague term 'recent' without a defined limit, but the overall simplicity and existing structured data make it sufficiently complete.

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

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

The tool has zero parameters, so the baseline is 4. The description does not need to add parameter meaning, and since there are no params, no additional info is required.

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 action (list), the resource (background tasks), and the ordering (newest-first). It distinguishes from siblings like get_async_task (fetch specific) and cancel_async_task (cancel), so the purpose is 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?

No guidance is provided on when to use this tool versus alternatives such as get_async_task or cancel_async_task. The description simply states what it does without context for selection or exclusions.

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

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

Adds behavioral context beyond annotations: states the tool requires no credentials. Annotations already cover read-only and idempotent safety, so description is helpful but not critical.

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

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

Single, front-loaded sentence with no redundant words. Every part is meaningful.

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?

Tool is simple (0 parameters, output schema exists). Description is sufficient: it names the resource and a key constraint (no credentials). Annotations cover safety.

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?

No parameters exist; schema coverage is 100%. Description effectively conveys the tool's scope without needing parameter details.

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

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

Clearly states the verb 'List', the resource 'configured Odoo instance names', and a key qualifier 'without credentials'. Distinguishes from siblings like 'search_across_instances'.

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

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

No explicit guidance on when to use this tool versus alternatives. The qualifier 'without credentials' implies a condition but does not compare with sibling 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, etc. The description adds no behavioral details beyond the listing action, e.g., pagination limits or result ordering, which are relevant but omitted.

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

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

A single sentence with no extraneous words. However, it sacrifices useful detail for brevity; still earns a high score for conciseness.

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 adequate for a simple list operation, especially with annotations covering safety and an output schema. But missing details on instance and limit parameters limit completeness.

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

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

Schema description coverage is 0%. The description only vaguely hints at 'name filtering' for the query parameter, ignoring limit (default 100, implying pagination) and instance (scope). No parameter meanings are clarified.

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

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

The description clearly states the verb 'List' and resource 'Odoo models', and mentions optional name filtering. However, it does not explicitly differentiate from sibling tools like search_records or read_record, leaving some ambiguity.

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

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

No guidance on when to use this tool versus alternatives, such as get_model_fields for specific model details or search_records for records. No exclusions or when-not-to-use instructions.

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 indicate readOnlyHint=true and idempotentHint=true; description adds specific purpose but no additional behavioral traits (e.g., rate limits, data freshness). Consistent 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?

Single sentence with example, no wasted words, front-loaded with the action and resource.

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 one parameter and an output schema, the description sufficiently explains the tool's purpose and input without needing additional 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?

With 0% schema description coverage, the description compensates by explaining the 'name' parameter expects an old or new model name, illustrated by an example.

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

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

Description clearly states the verb 'look up' and the resource 'Odoo model rename/removal history', with an example distinguishing it from sibling tools like search_records or read_record.

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

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

No explicit guidance on when to use or not use this tool versus alternatives; the example provides context but lacks when-not-to-use criteria.

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

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

The description matches annotations (readOnly, idempotent) and adds the 'preview without executing' context. No contradiction; behavior is clearly stated.

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

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

A single, front-loaded sentence with no filler. Every word serves a purpose.

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

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

Despite having an output schema, the description omits critical input parameter details (e.g., how to specify records, the difference between values and values_list). The agent needs more guidance to use the 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?

With 0% schema description coverage, the description provides no parameter details. The agent cannot determine what 'values', 'values_list', 'record_ids', etc., mean, severely limiting correct invocation.

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 previews create/write/unlink operations without execution. It uses specific verbs and resources, and distinguishes from siblings like 'execute_approved_write' or 'validate_write'.

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 use for dry-running operations without committing. It could explicitly say when not to use (e.g., when execution is needed), but the context from sibling names helps.

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. The description adds the behavioral trait of 'size-capped base64 content', warning about potential truncation. This adds value beyond annotations, but only marginally.

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

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

The description is a single concise sentence with no wasted words. However, it omits necessary parameter details, so it sacrifices completeness for brevity.

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

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

Given the tool has 3 parameters (one unexplained), the description is incomplete. It does not explain the optional parameters 'instance' and 'include_data'. Although an output schema exists, the missing parameter documentation is a significant 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 coverage is 0% and the description does not explain any parameter semantics. It does not clarify the meaning of 'instance' or 'include_data'. Only 'attachment_id' is inferable from context.

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

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

The description clearly states the verb 'Read', the resource 'ir.attachment', and specifies what is read: 'metadata and size-capped base64 content'. This distinguishes it from sibling tools like 'read_record' or 'search_records'.

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

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

No explicit guidance on when to use this tool vs alternatives. There is no mention of prerequisites or when-not-to-use. The purpose is clear but usage context is not provided.

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

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. Description adds 'Read' which matches, but does not provide extra behavioral context (e.g., returns full record if fields omitted, or behavior when record not found). With annotations present, a score of 3 is appropriate.

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

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

Single sentence, no redundant words. Front-loaded with verb and resource. Could add more detail 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?

Output schema exists, so return value is documented. However, with 4 parameters and 0% schema coverage, the description is insufficient to fully guide usage. Sibling tools list is large, and description does not help differentiate.

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 0%, so description must compensate. It mentions 'model' and 'record_id' implicitly, but does not explain the 'fields' and 'instance' parameters. No additional meaning beyond 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?

Description clearly states verb 'read' and resource 'single Odoo record', with key parameters 'model and ID'. It distinguishes from sibling tools like search_records (which return multiple) and aggregate_records. However, it could explicitly differentiate from read_attachment.

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

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

No guidance on when to use this tool versus alternatives like search_records, get_model_fields, or execute_method. No context about prerequisites or limitations.

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 indicate readOnly, openWorld, idempotent, non-destructive, so the description doesn't contradict them. The description provides a good high-level behavior ('bucketed by days overdue') that complements annotations. However, it doesn't elaborate on side effects (though readOnly implies none) or specific data aggregation behavior, but given the annotations, this is adequate.

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 one sentence, concise and to the point. It communicates the core function without fluff. It could maybe expand on the output, but for a report tool, this is appropriately short.

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 minimal but an output schema is present, so return values don't need explanation. However, it doesn't mention the meaning of 'open-item lines' or the purpose of the 'limit' parameter, which could be ambiguous. The tool complexity is moderate (5 params, all documented), so more context would help. Given the output schema exists, it's acceptable but could be slightly more complete.

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

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

All parameters have descriptive schema descriptions: as_of (ISO date), limit (max lines), instance (optional Odoo instance), direction (receivable/payable), top_partners (max partners, capped). The description adds context by saying the report is 'bucketed by days overdue', which helps understand what 'as_of' and 'direction' mean. Since schema coverage is 100%, the parameter semantics are already well-covered, but the description reinforces the purpose.

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 produces an 'Aged receivable/payable report' with a specific structure (bucketed by days overdue). It effectively conveys the core purpose and distinguishes it from general reporting tools. However, it doesn't explicitly differentiate from sibling tools like `accounting_health_summary` or `business_pack_report`, which might also involve financial reports.

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

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

The description implies usage for generating aging reports but provides no guidance on when to choose this over alternatives or prerequisites (e.g., configured Odoo connection, instance). Given sibling tools like `accounting_health_summary`, explicit when-to-use guidance is missing. The schema mentions 'instance' and 'direction', but the description doesn't clarify typical use cases.

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

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

Annotations already indicate readOnlyHint, idempotentHint, and non-destructive. The description adds the behavioral trait of avoiding code import, which is valuable context beyond annotations. Additional details about scanning behavior could improve transparency, but the description supplements annotations well.

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 action and constraint. Every word earns its place with no redundancy.

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

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

Given the low complexity (3 optional parameters, output schema exists, annotations cover safety), the description is adequate but lacks details on return values or parameter constraints. It provides the essential purpose but could be more helpful with usage examples or output 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?

The description does not explain any of the three parameters (max_files, addons_paths, max_file_bytes). Schema description coverage is 0%, so the description bears the responsibility but fails to clarify their purpose or usage. Parameter names are self-explanatory to some extent, but the description adds no 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?

The description clearly states the tool scans local Odoo addon source, with the key constraint 'without importing addon code', which distinguishes it from import operations. The verb 'scan' and resource 'local Odoo addon source' are specific.

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

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

The description provides implied usage by stating it scans without importing, but does not explicitly state when to use this tool versus alternatives. It lacks guidance on when not to use it or how it compares to sibling tools like diagnose_odoo_call or read_record.

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, openWorldHint, idempotentHint, and destructiveHint false. The description adds value by stating that the tool builds and caches the catalog, implying that it is a read operation that may return cached data, and that it is bounded. This context enriches the understanding beyond 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, front-loaded sentence with no unnecessary words. Every word contributes to the purpose, making it highly concise and efficient.

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

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

Given that an output schema exists and annotations cover safety, the description is mostly complete. However, it does not explain the caching behavior in detail or mention the bounded nature explicitly, which could be helpful for an agent to understand the tool's scope. Still, it is sufficient for a tool with well-documented parameters and 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 the schema documents all parameters fully. The description does not add any additional meaning or constraints beyond what the schema provides, meeting the baseline expectation.

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

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

The description clearly states the action ('Build and cache') and the resource ('bounded Odoo model schema catalog'), which is specific and informative. It distinguishes from sibling tools like 'list_models' or 'get_model_fields' by emphasizing caching and boundedness, but does not explicitly contrast with them.

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

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

The description gives no guidance on when to use this tool versus alternatives such as 'list_models', 'get_model_fields', or 'search_records'. No usage context, prerequisites, or exclusions are provided.

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

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds useful behavioral grounding with 'fanned out... merged and attributed', which explains the cross-instance orchestration and result attribution. It does not go into detail about attribution semantics or edge cases, but it complements the annotations well.

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?

This is a single, well-structured sentence that front-loads the key idea ('Read-only') and packs in scope and behavior without waste. It is concise while still being information-dense.

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