governanceoracle

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

No annotations are present, so the description must carry full behavioral transparency. It fails to disclose that the tool can add new actions (via the 'add' parameter) or describe other behaviors like required permissions or side effects. The description is too vague about what 'track' entails.

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 of 8 words, which is very concise. However, it is too brief to be informative; a more detailed description would better serve the agent. It is not front-loaded with critical information like the ability to add actions.

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 6 parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain core functionality (e.g., whether this tool creates, reads, or updates actions), nor does it clarify the meaning of key parameters like 'finding_id' or the effect of the 'add' flag.

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 only 17% (only the 'add' parameter is documented). The description does not provide any additional meaning for the remaining five parameters. While 'owner', 'title', and 'due_date' are somewhat self-explanatory, 'finding_id' and 'priority' lack clarifying 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 specific verb ('Track') and identifies the resource ('remediation actions') with relevant aspects (deadlines, ownership). It distinguishes from sibling tools like 'board_report' or 'kpi_dashboard', which focus on reporting rather than action tracking.

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 'exception_register' or 'framework_review'. The description lacks context for prerequisites, when not to use it, or how it relates to other remediation-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?

The description hints that the tool returns a read-only bundle (checklist, stats), but it does not explicitly state that it is non-destructive or whether any side effects exist. No annotations are available to supplement this.

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 is concise and front-loaded. It could be slightly more structured (e.g., separating content from purpose), but it efficiently conveys the core 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 the lack of parameters, output schema, and annotations, the description provides basic content information but omits usage context, frequency of updates, or what distinguishes this from similar tools like framework_review.

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 zero parameters and 100% schema coverage, the description does not need to add parameter information. The baseline of 4 is appropriate as the description adds no parameter details, but none are 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 tool's resource as 'Annual framework review evidence bundle' and lists its contents (checklist, stats, Art. 6(5) compliance). However, it lacks an explicit action verb (e.g., 'retrieve' or 'generate'), making the tool's operation slightly ambiguous.

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

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

No guidance is provided on when to use this tool versus its siblings. There is no mention of alternatives or exclusions, leaving the agent 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?

With no annotations, the description bears full responsibility. It lists output components but omits behavioral traits like side effects (e.g., this is a read-only report, no data modification), required permissions, or aggregation behavior. The description is functional but not transparent about non-obvious behavior.

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 action and outcome. Every word contributes meaning, with no redundancy or extraneous details.

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 lacking output schema, the description enumerates key deliverable components (executive summary, findings, risk, overdue items), providing a clear idea of what the tool returns. The single parameter is straightforward. Could mention that the report aggregates data from other sources, but overall sufficient for usage.

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% with a description for the 'period' parameter, so the description adds minimal extra meaning beyond what is already in the schema. It does not elaborate on format constraints or default behavior, so baseline 3 is appropriate.

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

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

The description explicitly specifies the tool's action ('Generate') and the resource ('Management Body review pack') with clear components (executive summary, open findings, risk posture, overdue items). It distinguishes this from sibling tools like 'board_report_llm' and 'list_findings' by focusing on a consolidated pack format.

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 generating board-ready reports, but does not explicitly compare to the similar sibling 'board_report_llm' or state when to avoid this tool. No exclusion criteria or prerequisites are provided, so guidance is slightly incomplete.

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 provided, so description carries full responsibility. It mentions 'AI-powered' and 'local LLM' but does not disclose potential side effects, latency, costs, or whether it's read-only. Insufficient behavioral 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?

Two concise sentences with front-loaded key information. Every word adds value; 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 no annotations and no output schema, the description should provide a more complete picture. It fails to explain what 'current findings' refers to, how the LLM is invoked, or any usage constraints. Missing important context for an LLM-powered tool.

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

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

Schema coverage is 100%, so the schema already documents both parameters. The description adds no extra meaning beyond what's already in the parameter descriptions, 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?

Clearly states it generates an AI-powered narrative summary using Gemma 4 LLM, in German or English. However, it does not explicitly distinguish itself from sibling 'board_report' tool, leaving 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 like 'board_report'. No conditions, prerequisites, or exclusions 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?

With no annotations provided, the description bears full burden. It only states it is a dashboard, failing to disclose behavioral traits such as read-only nature, authentication needs, or whether it performs mutations. The acronym 'DORA' is unexplained.

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. It is front-loaded and efficient, though could benefit from a brief expansion on content.

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 no parameters and simple schema, the tool lacks an output schema and the description is too terse. It does not explain what data the dashboard returns (e.g., metrics, charts), making it incomplete for agent decision-making.

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

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

There are no parameters, and the description adds context ('across all DORA control domains') beyond the empty input schema. Baseline for zero parameters is 4, as per guidelines, since no additional parameter details are 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 clearly identifies it as a control effectiveness dashboard across DORA control domains, which specifies the resource and scope. However, it does not explicitly differentiate from siblings like 'kpi_dashboard' or 'health_check', leaving room for 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. The description provides no context for selection, 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?

With no annotations, the description must carry the burden of behavioral disclosure. It mentions expiry tracking but fails to explain what happens on expiry, permissions needed, or how the view and add modes differ. No details on side effects or constraints.

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, which is concise but lacks sufficient detail to be truly helpful. It avoids fluff but is under-specified.

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 8 parameters with no required fields, low schema coverage, no output schema, and no usage examples, the description is grossly inadequate. It does not explain how to perform a 'view' versus 'add', or what the response will be.

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

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

Schema description coverage is only 13%, with only the 'add' parameter documented. The description adds marginal value by hinting at the view/add modes but does not explain other parameters like title, finding_id, or dates. The agent must infer meaning from parameter 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 states the tool is for viewing or adding risk acceptances/exceptions with expiry tracking, using specific verbs and resource. It distinguishes from siblings like register_finding, which deals with general findings.

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 register_finding or action_tracker. The agent is left without context on when to 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. The description indicates it is a review/assessment, suggesting read-only behavior, but it does not disclose authentication needs, side effects, or what 'effectiveness assessment' entails.

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 wasted words. The description is appropriately sized 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?

For a parameterless tool, the description is adequate but lacks details on return values (no output schema) and behavioral context. It assumes domain knowledge (DORA areas) and does not explain what the assessment outputs.

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, so schema coverage is 100%. The description adds meaning by specifying the tool's purpose and scope (ICT Risk Management Framework, DORA area), compensating for the lack of parameters.

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 it performs an annual review and effectiveness assessment of the ICT Risk Management Framework per DORA area. The verb and resource are specific, but the sibling tool 'annual_review' could overlap; the DORA focus helps differentiate.

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 like 'annual_review' or 'board_report'. The description implies it's for DORA-related reviews but does not provide usage 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?

The description is minimal ('Server status.') and does not disclose behavioral traits beyond the obvious read-only intent. With no annotations, it fails to mention return format, side effects, or authentication needs, leaving significant transparency gaps.

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: three words. Every word is necessary, and it is well front-loaded, achieving maximum efficiency.

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 (no parameters, no output schema), the description is complete enough to convey the basic purpose. Minor improvement could mention return type, but overall it fulfills requirements for a trivial health check.

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

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

There are no parameters, so the input schema is fully covered (100%). The description need not add parameter information, and it correctly omits it.

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 name 'health_check' combined with the description 'Server status.' clearly indicates a check of server health or status. It is not a tautology and distinguishes from siblings like 'control_status' which may imply control actions.

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

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

No guidance is provided on when to use this tool versus alternatives. It lacks any context about prerequisites or exclusions, leaving the agent to infer use cases without support.

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 provided, so the description must cover behavioral traits. It only lists the KPI names, omitting details like data freshness, side effects, or access restrictions. The read-only nature is implied but not 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?

The description is a single, concise sentence with no wasted words, front-loaded with the tool's purpose. However, it lacks structural elements like bullet points that could improve readability.

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 and no output schema, the description is minimally adequate. It does not explain the return format or how the KPIs are presented, but given the simplicity, it meets basic expectations.

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

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

No parameters exist in the input schema, and schema coverage is 100%. Baseline for zero parameters is 4; no further description 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 clearly states it provides 'ICT Risk KPIs' listing specific metrics (open findings, overdue rate, remediation rate, exception count), distinguishing it from sibling tools like register_finding or list_findings which deal with individual findings.

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 list_findings or health_check. Given multiple sibling tools, explicit context on usage scenarios would help.

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, and the description does not disclose behavioral traits like idempotency, read-only nature, pagination, or performance implications. The description is too 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 very short (one sentence), but this is acceptable for a simple list tool. However, it could still be more informative while remaining 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?

Given the four optional parameters, no output schema, and lack of annotations, the description is incomplete. An agent would not know what to expect in the response or how to properly use filters.

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 adds no meaning beyond the parameter names. It does not explain semantics (e.g., how 'owner' is matched) or provide examples.

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 (list) and resource (findings) and mentions optional filters. It effectively distinguishes from sibling tools like 'register_finding' which presumably creates findings.

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, no context on when not to use it, and no mention of prerequisites or typical scenarios.

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 provided, so the description must disclose behaviors. It only says 'register', failing to mention if it creates a new entry, updates an existing one, requires permissions, or any 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 sentence, which is concise but overly minimal. It lacks structure and important details, making it barely adequate.

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 13 parameters, no output schema, and no annotations, the description fails to provide necessary context. The agent cannot infer behavior, parameter usage, or expected outcomes from this minimal text.

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 only 8% (only 'source' has a brief description). The tool description adds no additional meaning to any of the 13 parameters, leaving the agent with bare enum values and no guidance on how to fill them.

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 registers an audit finding, risk, or control gap. It uses a specific verb ('register') and resource types, and distinguishes from sibling tools like 'list_findings' which lists findings.

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 (e.g., 'list_findings' for viewing, 'control_status' for checking status). No contexts or exclusions provided.

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