changeoracle

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

No annotations are provided, so the description must convey behavioral traits. The verb 'Verify' implies a non-destructive read operation, but this is never explicitly stated. It also does not mention any side effects, required permissions, rate limits, or what happens if validation fails. The description only lists what is verified, offering minimal transparency.

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

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

The description is a single short sentence, front-loaded with the key action and targets. However, it is so terse that it borders on under-specification rather than effective conciseness. While there is no fluff, the brevity sacrifices necessary 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?

Tool complexity is moderate with one parameter and no output schema. The description names three verification areas but does not explain return values, success/failure criteria, or typical usage context. Since no output schema exists, the description should provide more behavioral context, which it fails to do, making it incomplete.

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

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

The input schema has one required parameter 'change_id' with a string type, but the description provides no explanation of what 'change_id' represents, its format, or how to obtain it. With 0% schema description coverage, the description fails to compensate, leaving the sole parameter semantically undefined.

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 action ('Verify') and resources (approval chain, SoD compliance, prerequisites), making its purpose clear. However, it does not differentiate from sibling tool 'sod_check', which likely overlaps in the SoD area, so it falls short of the highest distinction.

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 like 'sod_check' or other siblings. It does not specify any exclusions, prerequisites, or typical scenarios for choosing this tool, leaving usage entirely implied.

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

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

No annotations are provided, so the description carries the full burden. It only says 'Automated risk assessment' without disclosing whether the operation is read-only, what side effects exist, or what the response looks like. No behavioral details are revealed.

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 wasted words. It efficiently conveys the core action, though it is under-specified in other dimensions.

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

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

With no annotations, no output schema, and only a single parameter, the description leaves many gaps: it doesn't explain the tool's return value, side effects, or usage context. The description is too minimal to be considered 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 schema has one parameter (change_id) with 0% description coverage. The description doesn't explain the parameter or how it relates to the mentioned 'type, scope, and controls.' It adds minimal value beyond the schema's field name.

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

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

The description states the tool performs an 'Automated risk assessment' and mentions factors like type, scope, and controls, but it doesn't clearly specify the resource (change) or the output of the assessment. It's not a tautology but is somewhat vague and doesn't differentiate from sibling 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?

There is no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The description only implies usage based on the tool's name and generic function, providing no explicit 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 no annotations provided, the description does not disclose whether this is a read-only operation, what the response format is, or any dependencies. It implies a dashboard view but doesn't explicitly state it won't modify data or require permissions, leaving significant behavioral ambiguity.

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

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

The description is a single, concise line that packs meaningful content into few words. It is front-loaded with 'Dashboard' and lists metrics without redundancy, earning every word.

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 description names four metrics, it omits details on how these are represented (e.g., counts, percentages, date ranges) and doesn't provide an output schema. For a no-param tool it's adequate but leaves room for interpretation, so it's neither fully specified nor inadequate.

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 schema fully covers parameter semantics. The description doesn't need to elaborate, and the empty schema is trivially complete, meeting the baseline for no-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 identifies the tool as a dashboard presenting four specific metrics (volume, risk distribution, test/rollback coverage, emergency ratio), which gives a clear sense of its function. It differentiates from sibling tools like list_changes and health_check by focusing on aggregated statistics, though it lacks an explicit verb like 'returns' or 'displays'.

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 compared to alternatives such as list_changes or change_risk_assess. The description only outlines content without specifying appropriate 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It does not state whether the tool performs a read, what output it returns, or any side effects, providing essentially no transparency beyond the name.

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 underspecified, consisting of only two words. While conciseness is valuable, this lacks even a full sentence and fails to provide a meaningful structure that aids understanding.

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?

Even though the tool is simple with no parameters, the description does not explain what the health check returns or how the agent should interpret the result. With no output schema, the description should fill this gap but remains incomplete.

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

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

The tool has zero parameters, which according to the rubric warrants a baseline score of 4. The empty input schema is fully described by the schema itself, so no further parameter documentation is needed.

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

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

The description 'Server status.' is a noun phrase that essentially restates the tool name 'health_check' without providing a clear verb or resource. It is vague and does not distinguish this tool from its siblings, though the sibling tools are change-related, making the general domain 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?

No guidance is provided about when to use this tool versus the alternatives. There is no mention of appropriate contexts, prerequisites, or exclusions, leaving the agent to infer usage solely from the tool's name.

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 zero annotations provided, the description carries the full burden of behavioral disclosure. It only states that it lists changes with optional filters, offering no information about return format, pagination, filtering details, ordering, or read-only guarantees. This leaves substantial behavioral ambiguity for an agent.

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

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

The description is a single, direct sentence with no redundancy. It efficiently states the core action and the availability of filters, making it appropriately sized and 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?

The tool has 4 parameters, no output schema, and no annotations, yet the description is only four words. It does not describe the response shape, parameter combos, or edge cases, leaving an agent without enough information to reliably invoke the tool beyond a simple unqualified call.

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. 'Optional filters' vaguely indicates the parameters act as filters, but it fails to explain the meaning of search, status, risk_level, or change_type. The enums in the schema provide some hints, but the description adds no specific parameter-level 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 uses the specific verb 'List' with the resource 'changes' and notes 'optional filters,' clearly identifying the tool as a retrieval operation for change records. This distinguishes it from sibling tools like register_change (create), change_risk_assess (assess), and change_stats (analytics), which have different purposes.

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 phrase 'optional filters' implies a search/listing use case, but the description provides no explicit guidance on when to use this tool versus siblings like change_stats or test_evidence, and no exclusions or alternatives. Usage context is only implied.

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

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

With no annotations provided, the description must fully disclose behavioral traits. It states the analysis scope but does not mention whether it is read-only, what data it accesses, or what the output format is. This lack of detail is insufficient for an agent to anticipate side effects or return values.

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 highly concise, consisting of a single phrase that conveys the core purpose. While efficient, it borders on under-specification, lacking a full sentence or additional context, but it does not waste 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?

Given the absence of annotations and an output schema, the description should provide more context about what the tool returns and how to interpret results. It only offers a high-level label with no details on scope, data sources, or output structure, 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?

The tool has zero parameters, as indicated by the empty schema. With no parameters to describe, the baseline is 4, and the description does not need to provide parameter semantics. It correctly contains no parameter-related information.

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

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

The description clearly identifies the tool's function: analyzing patch lag against scheduled deadlines. It distinguishes itself from sibling tools like change_stats or health_check by focusing specifically on patch compliance and overdue patches.

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 patch compliance analysis but does not explicitly state when to use it versus alternatives. No exclusions or alternative tool references are provided, leaving room for the agent to infer the appropriate 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 no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions 'full DORA traceability', hinting at data collection but not explaining side effects, permissions, idempotency, success/failure behavior, or return format. This is insufficient for a mutation tool.

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

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

The description is a single concise sentence with no wasted words, but it sacrifices necessary detail for brevity. It lacks structure to accommodate the tool's complexity, making it too under-specified to be considered well-crafted.

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 20 parameters, no output schema, and no annotations, the description is massively incomplete. It does not explain required fields, what the tool returns, or how it fits into the DORA traceability workflow, leaving dangerous gaps for an AI agent.

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 mentions no parameters. With 20 parameters including enums for change_type and risk_level, the description adds zero meaning to help the agent correctly populate fields 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 uses a specific action verb 'register' with a clear object 'ICT change request' and meaningful qualifier 'full DORA traceability'. This clearly distinguishes it from sibling tools like 'list_changes' or 'change_risk_assess', making the tool's function unambiguous.

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

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

The description provides no guidance on when to use this tool versus alternatives such as approval_check or rollback_plan. It lacks any mention of prerequisites, exclusions, or typical workflows, leaving usage entirely to inference from the name.

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

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

With no annotations, the description must disclose behavioral traits. It only says 'validate' without specifying whether this modifies anything, requires prerequisites, or what the output format is. This is insufficient for an agent to understand side effects or expectations.

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

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

The description is a single, direct sentence with no superfluous words, earning a high conciseness score. However, it is so brief that it sacrifices necessary detail for other dimensions.

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?

This tool has 5 parameters, no annotations, and no output schema. The one-sentence description fails to explain operational context, input semantics, or expected results, making it incomplete for real-world use.

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 5 parameters with zero description coverage. The description adds no parameter semantics, leaving the agent to guess the meaning of boolean fields like rollback_tested and backup_confirmed or the integer estimated_rollback_minutes.

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 validates rollback plan readiness for a change, which is a specific, actionable purpose. It distinguishes from siblings like approval_check or change_risk_assess, though it doesn't explicitly name alternatives.

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

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

No guidance is provided on when to use this tool versus other validation tools, nor any prerequisites or exclusions. The description only states the function, leaving usage context entirely implicit.

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

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

With no annotations provided, the description carries the full burden. 'Detect' implies a read-only inspection, and 'across all changes' clarifies scope, but it does not disclose return formats, permissions, or any side effects. This is minimally adequate for a simple zero-parameter tool.

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

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

The description is a single, front-loaded sentence with no unnecessary words. It is concise and structured effectively, placing the action verb first.

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

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

For a tool with no parameters, no annotations, and no output schema, this description covers the core action and scope adequately. It could mention what the output looks like, but given the simplicity, it is 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 input schema has zero parameters, so there is nothing to explain. The baseline for zero parameters is 4, and the description appropriately ignores parameter details since none exist.

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 the specific verb 'Detect' with a clear resource ('Segregation of Duties violations') and scope ('across all changes'), unambiguously distinguishing it from siblings like approval_check or change_risk_assess.

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 over alternatives, nor any exclusions. While the purpose is clear, there is no explicit discussion of use cases or context that would help an agent choose this 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It says only 'record or view' without explaining side effects, whether recording overwrites existing data, what 'view' returns, or any permissions needed. The dual-mode behavior is acknowledged but not detailed.

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, grammatically complete sentence with no redundancy, which is concise. However, for a tool with 8 parameters, this brevity borders on under-specification rather than effective conciseness. It does not structure information for the agent (e.g., by grouping parameters or outcomes).

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 (8 parameters, no annotations, no output schema), the description is drastically incomplete. It does not explain parameter meanings, the distinction between recording and viewing, or expected outputs. An agent cannot reliably invoke this tool based on the provided information.

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 mentions none of the 8 parameters. The schema contains enums for 'result' and 'test_type', but without explanation of how they map to behavior, the agent cannot correctly select or fill parameters. The description fails entirely to compensate for the schema's lack of semantic 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 uses a clear verb ('record or view') and identifies the resource ('test execution evidence for a change'). This resource is distinct from sibling tools like approval_check and register_change, which focus on other aspects. However, the dual verb 'record or view' introduces ambiguity about whether the primary action is mutation, retrieval, or both.

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

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

No guidance is given about when to use this tool versus alternatives. The description does not mention prerequisites, exclusions, or relationships to sibling tools. An agent would have to infer usage from the name and context, which is insufficient for a tool in a complex change-management workflow.

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