driftoracle

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

With no annotations, the description carries the full burden of behavioral transparency. It only states 'View/set' without disclosing side effects, persistence, reversibility, permissions, or whether setting thresholds overwrites existing values. This is insufficient for a mutation-capable 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 extremely concise with no wasted words, and the key action is front-loaded. However, it may be too terse for the tool's parameter count, though that is more a completeness concern than a conciseness issue.

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, no output schema, and 3 parameters, the description is not complete enough for an agent to invoke correctly. It omits how 'set' toggles behavior, whether parameters are required together, and what return or side effects to expect.

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 low at 33%, and the description does little to compensate. It vaguely references 'thresholds' but does not explain the 'set' boolean or the two max_age_days parameters, leaving their semantics largely to the schema.

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

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

The description 'View/set drift detection thresholds' uses a specific verb and resource, clearly communicating both read and write capabilities. It distinguishes itself from sibling tools like detect_drift and drift_status by focusing on configuration of thresholds.

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, exclusions, or scenarios where configuring thresholds is appropriate versus using the various drift detection/history 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?

With no annotations provided, the description must disclose behavioral traits, but it only says 'live check.' It doesn't indicate whether the operation is read-only, whether it makes external network calls, what side effects may occur, or how results are returned. The agent cannot infer safety or side effects from 'live check' alone.

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 brief, consisting of a fragment. While concise, it under-specifies the tool's purpose and behavior; brevity at the expense of necessary information is not good 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?

Given the presence of multiple sibling drift tools and the absence of an output schema, the description is insufficiently complete. It fails to convey what the tool returns, how it differs from related tools, or any usage constraints. Even for a simple tool, the description leaves too much to inference.

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 includes a single optional entity_id parameter with only 'Optional' as its description, and the tool description provides no additional context about its purpose. Since schema coverage is 100%, the baseline is 3, but the description adds no value to 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 identifies the tool as a live check for cloud provider status changes, which clearly relates to drift detection. However, it doesn't specify the exact scope (e.g., infrastructure configuration, availability) or distinguish it from sibling drift detection tools like detect_control_drift or detect_enterprise_drift.

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 offers no guidance on when to use this tool over alternatives. It doesn't mention prerequisites, frequency, or complementary tools, leaving the agent without decision criteria. Given the many sibling drift tools, this is a significant gap.

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?

There are no annotations, so the description must disclose behavioral traits. It only states a condition ('degraded from GREEN to YELLOW/RED') and does not mention whether the tool is read-only, what output it returns, or any side effects. This is insufficient for a tool despite the implied 'detect' in 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 a single short sentence, which is concise, but it is under-specified rather than effectively structured. It omits essential details about the tool's function and parameters, so the brevity reduces 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?

For a tool with one parameter, no annotations, and no output schema, the description is incomplete. It does not explain the return value, the meaning of entity_id, or how this relates to other drift tools. The description provides only a minimal definition of drift, leaving major 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?

The schema has one parameter (entity_id) with no description, and schema description coverage is 0%. The description does not mention entity_id at all, so the agent has no guidance on what this parameter represents or whether it is optional. The description fails to compensate for the sparse schema.

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

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

The description is a noun phrase with no verb, stating what the tool identifies ('Controls that degraded from GREEN to YELLOW/RED') rather than what it does. It adds some specificity about the drift criteria, but fails to clearly state an action, making it vague and not properly differentiated from sibling tools like detect_cloud_drift.

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 offers no guidance on when to use this tool versus alternatives such as detect_cloud_drift or detect_enterprise_drift. No context or exclusions are provided, leaving the agent to infer usage.

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 discloses 'Auto-logs drift events' as a side effect, but omits details about permissions, reversibility, or return behavior. This is a limited disclosure of behavioral traits.

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 primary action. The long list of dimensions is necessary and directly relevant, making the description efficient without verbosity.

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?

Without an output schema or annotations, the description omits return value details, the meaning of entity_id, and the consequences of auto-logging. It provides the core purpose but leaves significant gaps, especially for the unspecified entity_id and operational 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?

Schema description coverage is 50% with entity_id undocumented. The description aligns with the categories parameter by naming the six dimensions, but does not help clarify entity_id or its usage. It adds some semantic value for categories but fails to compensate for the other parameter.

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

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

The description clearly states 'Detect compliance drift across 6 enterprise dimensions' and enumerates the specific frameworks, which gives a specific verb+resource+scope. It distinguishes itself from sibling tools like detect_cloud_drift or detect_regulatory_drift by naming the exact enterprise dimensions.

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 detecting drift in the listed compliance frameworks, but does not explicitly state when to use it versus alternatives or when not to use it. No mention of sibling tools 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?

Since no annotations are provided, the description bears full responsibility for behavioral disclosure. However, it only lists the items being found and says nothing about whether the tool is read-only, what it returns, if it has side effects, or if any permissions are required.

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 under-specified. It is not structured to convey necessary context about usage or parameters. While it avoids verbosity, it lacks completeness and could benefit from additional sentences.

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

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

With no output schema and minimal parameter documentation, the description needs to supply more context. It only hints at purpose and lacks prerequisites, return behavior, and differentiation from the many sibling drift detection tools, making it insufficient for an agent to confidently invoke the tool.

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

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

The only parameter, entity_id, is completely unexplained. The schema provides just a string type, and the description does not mention it at all (schema coverage 0%). The agent cannot infer what entity_id refers to or how it filters the results.

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 'Find' and names three distinct resources ('stale assessments', 'expired evidence', 'degraded controls'), which clearly indicates the tool's focus on evidence drift. The mention of 'evidence' distinguishes it from sibling drift detection tools like detect_control_drift or detect_cloud_drift.

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 only states what it finds, but does not mention prerequisites, exclusions, or scenarios where another drift detection tool might be more appropriate.

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?

There are no annotations, so the description must disclose behavioral traits. It only lists data sources and implies a read-only scan, but does not state side effects, permissions, rate limits, or whether any state changes occur. The lack of output format and entity_id behavior further reduces 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 two concise sentences, each adding value: the first states the primary purpose, the second lists specific data sources. No unnecessary words or 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 output schema and no annotations, the description leaves out critical context: what the tool returns, how the optional entity_id impacts results, and how this differs from other drift scans. The limited info is insufficient for an agent to fully understand the tool's behavior.

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

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

The only parameter, entity_id, is described in the schema as 'Optional' with no additional context. The tool description does not mention this parameter at all, failing to explain how it affects the scan or when to provide 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 description uses a specific verb 'Scan' and clearly identifies the resource: regulation changes affecting DORA. It also lists the specific data sources (RegWatch, LawOracle, EU feeds), which distinguishes it from sibling drift-detection tools like detect_cloud_drift and detect_control_drift.

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 explicit guidance on when to use this tool versus alternatives such as full_drift_scan or detect_control_drift. It does not mention exclusions or conditions, leaving the agent without clear decision 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?

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It does not state whether the operation is read-only, whether it triggers scans, or any side effects. The description only states a domain fact, leaving the agent uncertain about the tool's 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 very short, which is concise, but it is a fragment rather than a complete sentence. It sacrifices necessary semantics—such as the operation type and parameters—to the point of under-specification. Brevity is present but at the expense of 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?

With no output schema, no annotations, and incomplete parameter descriptions, the description should provide more context about return values and usage. It only covers the basic domain ('drift events') and leaves the agent without enough information to invoke the tool effectively.

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 mention either parameter (limit, entity_id). The schema provides only a minimal 'Optional' description for entity_id and no description for limit. With schema coverage at 50%, the description should compensate, but it adds no parameter meaning at all.

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 resource ('history of all drift events') but lacks an explicit verb like 'List' or 'Retrieve.' It does not distinguish itself from sibling tools such as drift_status or full_drift_scan, which also relate to drift state. The phrase is clear about the data domain but not the 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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention whether it is for auditing past events, nor does it suggest any context for using limit or entity_id. No exclusions or alternative tool references are present.

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. It does not disclose whether the operation is read-only, any side effects, authentication needs, or output format. The only behavior implied is returning current open drift events, but this lacks enough detail for safe autonomous invocation.

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 efficiently conveys the core purpose without any filler. Every word contributes to meaning.

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

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

For a simple tool with one optional parameter and no output schema, the description adequately informs the agent of the return nature (current open events). However, it could be more complete by explicitly noting that this is a read-only status check and perhaps contrasting with drift_history, but the minimalism is acceptable for the complexity level.

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%; the parameter description 'Optional — empty for all' already clarifies that omitting entity_id returns all entities. The tool description adds the context 'per entity', which reinforces the filter intent but does not introduce new semantics beyond the schema.

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

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

The description 'Current open drift events per entity' clearly states a specific resource (open drift events) and scope (per entity), distinguishing it from siblings like drift_history (historical) and full_drift_scan (scanning). The verb is implied but the intent is unmistakable.

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

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

Usage context is implied by the term 'current open drift events'—it's for checking present status rather than scanning or history—but there is no explicit guidance on when to choose this over drift_history or detect_* tools. No alternatives or exclusions are mentioned.

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 disclosing behavior. It details what detections are included and that the enterprise dimension scans specific frameworks via 'MEGA MCP oracles', adding useful behavioral context. However, it does not state whether the operation is read-only, potential performance implications, or any side effects, leaving gaps for a non-annotated 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 two sentences long and front-loads the core function in the first sentence. The second sentence adds specific detail about the enterprise dimension's scope, which is valuable. No wasted 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?

There is no output schema, so the description should explain what the tool returns, but it does not. It also omits any guidance on the optional entity_id parameter, and does not mention potential limitations or environmental dependencies beyond the oracle reference. Given the tool's moderate complexity, the description is incomplete for accurate invocation.

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

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

The input schema has one parameter, entity_id, with 0% schema description coverage. The tool description does not mention entity_id at all, so it provides no meaning beyond the parameter name/type. With low schema coverage, the description should compensate, but it fails entirely.

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: 'Run ALL 5 drift detections in one call' and enumerates them (regulatory + evidence + cloud + control + ENTERPRISE). This distinguishes it from the individual sibling detect_* tools and gives a specific verb ('Run') + resource ('ALL 5 drift detections').

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 'in one call' conveys when to use this tool—when a comprehensive drift scan is needed, as opposed to individual detection tools. It does not explicitly mention alternatives or exclusions, but the context clearly implies the batch vs. individual choice. This qualifies as clear context without 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 disclosing behavioral traits. 'Server status.' reveals nothing about side effects, read-only nature, authentication requirements, return format, or error handling. It is completely opaque.

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 terse, but this is under-specification rather than effective conciseness. It does not convey enough information to be useful, so the brevity fails to earn 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?

Without an output schema, the description must explain what the tool returns. 'Server status.' does not describe the response structure, possible status values, or any operational details, making the tool incomplete for an agent to use correctly.

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

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

The tool has zero parameters, so the baseline is 4. The description adds no parameter information, but with no parameters to document, no additional semantics 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 'Server status.' is a vague restatement of the tool name, essentially paraphrasing 'health_check' without providing a specific verb or resource. It does not distinguish this tool from siblings like 'ping', which could also check server availability.

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 offers no guidance on when to use this tool versus alternatives. There is no mention of appropriate contexts, exclusions, or complementary tools, leaving the agent without decision 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 are provided, so the description must carry the full burden. It states the action (mark) but does not disclose effects, reversibility, permissions required, or what happens after marking. It adds minimal context beyond the verb, lacking any explanation of side effects or follow-up actions.

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 and front-loaded with the core action. However, it is under-specified for a tool with three parameters and no annotations. It is not a tautology like 'Process', but it sacrifices necessary 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?

This is a mutating tool (marking an article) with no annotations, no output schema, and 0% parameter coverage. The description fails to explain the meaning of 'article', 'entity_id', or the consequences of marking. It is highly incomplete for the complexity, especially given numerous related sibling tools with which it could be confused.

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 three string parameters (reason, article, entity_id) with 0% schema description coverage. The description does not mention or explain any of these parameters. The agent must rely solely on param names, which are insufficient for understanding relationships or required format. No parameter semantics are added.

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 ('mark') and resource ('an article') and specifies the outcome state ('as DRIFT'). The word 'Manually' distinguishes it from the automatic detection sibling tools, but it does not fully differentiate from resolve_drift or trigger_remediation. Overall, it is specific but lacks explicit sibling contrast.

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 like detect_* or resolve_drift. The word 'Manually' implies a use case for overriding automated detection, but no explicit when/when-not is provided. The tool description does not mention prerequisites or contexts.

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 are absent, so the description carries full burden for disclosing behavior. It does not state whether the tool is read-only, what it returns, whether it invokes external processes, or any side effects. The tool behavior is completely opaque.

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 brief, but this is under-specification rather than conciseness. The single sentence does not provide enough information to be useful, and the structure is just a label, not an explanatory description.

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 no output schema and no annotations, so the description is the only source of context. It fails to explain what the obligation map contains, how to interpret DORA-DFT-01..04, or what the expected return value is. It is completely inadequate for an agent to understand the tool.

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

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

The input schema has zero parameters, so the baseline per the rubric is 4. The description adds no parameter information, but none is needed since there are no parameters to document.

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 'Drift detection obligations (DORA-DFT-01..04)' is a noun phrase with no action verb. It does not clearly state what the tool does (e.g., list, map, retrieve, configure). It vaguely names the content but does not distinguish from sibling tools like detect_*_drift or drift_history.

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 detect_cloud_drift, drift_status, or configure_thresholds. There is no mention of context, 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 carries full responsibility for behavioral disclosure. 'Connectivity test.' offers no details on what the tool returns (e.g., success/failure, latency), timeout behavior, or side effects. It adds little beyond the tool name and is essentially a tautology.

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 and front-loaded, with no wasted words. 'Connectivity test.' efficiently states the purpose. However, its brevity borders on under-specification, but for a zero-parameter tool it is appropriately sized.

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 output schema and no annotations, the description is the sole information source. It fails to explain expected results, error conditions, or what 'connectivity' refers to in the context of the sibling tools. This is insufficient for an AI agent to fully understand the tool's behavior.

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

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

The tool has zero parameters and the schema confirms this, so the baseline score of 4 is appropriate. The description does not need to explain non-existent parameters, and the schema already covers the empty parameter structure.

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 as a connectivity test. It uses a specific verb 'test' and resource 'connectivity', distinguishing it from sibling tools focused on drift detection and health checks. However, it could more explicitly contrast with the overlapping 'health_check' tool.

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

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

The description provides no guidance on when to use this tool versus alternatives. There is no mention of scenarios, prerequisites, or why one would choose ping over health_check or drift scans. This is a clear omission.

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 responsibility for behavioral disclosure. It does not state whether the action is reversible, idempotent, requires special permissions, or affects downstream processes like drift history or health checks.

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 or repetition. It is front-loaded with the action and subject, making it immediately scannable.

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 interacts with drift events, but the description omits key context such as what 'resolved' means, whether the resolution is persistent, how it relates to detection or thresholds, and what happens to the drift_id after resolution. With no output schema or annotations, this leaves significant gaps for an 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?

With schema description coverage at 0%, the description must compensate for the undocumented parameters 'drift_id' and 'resolved_by'. The phrase 'Mark drift event as resolved' implies drift_id identifies the event, but it does not clarify the role or required format of 'resolved_by'.

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 'Mark drift event as resolved' uses a specific verb ('mark') and resource ('drift event') with a clear resulting state ('resolved'). It distinguishes itself from sibling tools like detect_drift variants and even 'mark_drift' by specifying the resolved outcome.

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 'mark_drift' or 'trigger_remediation'. There is no mention of prerequisites, sequencing, or when resolving is appropriate versus other actions.

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 carries the full burden of behavioral disclosure. It lists actions but omits side effects, permissions, reversibility, or the scope of 'all data,' which is concerning for a mutation-capable 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 filler, front-loading the core purpose. However, it is cryptic and misses critical context, so while concise, it is not fully self-sufficient.

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 annotations, output schema, and schema descriptions, the description must provide substantial context. It lists several workflow steps but fails to explain return values, failure modes, or the scope of 'all data,' leaving the agent underinformed for a complex remediation tool.

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

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

The single parameter entity_id is not mentioned in the description, and schema coverage is 0%. The parameter name is self-explanatory to some degree, but the description adds no value regarding expected values, optionality, or how it affects the remediation workflow.

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 as a self-healing remediation action, listing concrete steps (sync all data, run escalation, collect evidence, auto-resolve drift). It distinguishes itself from sibling 'resolve_drift' by emphasizing automation, though it doesn't explicitly name that alternative.

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 on when to use this tool versus alternatives like resolve_drift or mark_drift. The 'self-healing' label implies automated use, but there are no explicit conditions, prerequisites, or exclusions.

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