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

Read-only nature is indicated by '[READ]', but no annotations exist. Description does not mention side effects, rate limits, data freshness, or output structure. Additional context like 'Op counts' being aggregated is helpful but leaves gaps for an AI 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?

Description is very short (two lines plus args list) and front-loaded with purpose. Every sentence is useful, though it could be expanded slightly for completeness without becoming verbose.

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

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

For a tool with 3 optional parameters, no annotations, and no output schema, the description explains core function and parameters but omits return format, examples, or edge cases. It is adequate for a simple monitoring tool but lacks full context.

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?

Input schema has no descriptions (0% coverage). The description adds meaning: 'since / until: ISO timestamps bounding the period' and 'bucket: "hour" or "day"', which clarifies the parameters' types and allowed values 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?

Description clearly states verb '[READ]' and resource 'Op counts bucketed by hour/day'. It specifies the purpose as 'monitoring-continuity evidence', differentiating it from sibling tools like query_audit_events that likely provide raw event details.

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?

Implicitly suggests use for monitoring via 'monitoring-continuity evidence' but lacks explicit when-to-use vs alternatives, when-not-to-use, or any exclusion criteria. No comparison to siblings is 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, the description must disclose behavioral traits. The '[READ]' prefix indicates read-only safety, and the parameter documentation clarifies filtering behavior. However, it lacks details on data freshness, pagination, or response size, which are important for an agent to understand the tool's limitations.

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

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

The description is concise with three distinct parts: a summary line, compliance context, and parameter list. It is front-loaded with the core purpose. Minor redundancy in repeating compliance standards could be slightly trimmed, but overall it's efficient.

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

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

Given the absence of an output schema, the description provides a high-level indication of return structure ('the who/what/when/why/approval artifact') but does not specify exact fields or formatting. Important details like pagination, sorting, or error cases are missing, leaving some ambiguity 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 description coverage is 0%, so the description must compensate. It explains all three parameters: 'since / until: ISO timestamps' and 'high_only: True/False' with default. This adds sufficient semantic meaning beyond the raw schema, though the exact ISO 8601 format is implied rather than explicit.

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 retrieves a report of 'high-risk write ops with approver + rationale', explicitly linking it to compliance standards (SOC 2, PCI, HIPAA). It distinguishes itself from sibling tools like 'query_audit_events' and 'activity_timeline' by focusing on approval trails for high-risk operations.

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 clear context that this tool is for compliance reporting (SOC 2, PCI, HIPAA), but does not explicitly state when not to use it or mention alternatives among siblings. The compliance references imply usage scenarios, meeting the 'clear context, no exclusions' threshold.

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 full burden and explicitly states 'WRITES NOTHING and starts no daemon', detailing the exact behavior. This fully discloses the side-effect-free nature.

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 front-loads the key insight '[READ]' and purpose, then explains behavior and parameters. While efficient, the Args section could be more concise, but overall each sentence adds value.

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 4 parameters, no output schema, and no annotations, the description covers purpose, behavior, and parameter semantics well. It could specify the exact output format (e.g., a string) but mentions 'master-password env note'. Adequate for the tool's complexity.

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

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

Schema description coverage is 0%, but the description includes an Args section that explains each parameter with defaults, examples, and accepted values (e.g., framework list, cron format). This adds significant meaning 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?

Description clearly states it composes and validates a cron line and command for periodic sealed-bundle generation, with the tag '[READ]' and explicit note that it writes nothing. This distinguishes it from execution-oriented siblings like generate_evidence_bundle and sign_bundle.

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

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

Description emphasizes that the tool only composes and validates, and does not execute or schedule, implying use when a ready-to-paste schedule hint is needed. It does not explicitly name alternatives, but the context of sibling tools and the read-only nature provides clear guidance.

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

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

With no annotations, the description fully discloses behavioral traits: populationSize is the full count, sample is capped, truncated and scanTruncated flags indicate limits. It explains what happens when limits are hit, which is critical for agent decision-making.

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

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

The description is concise and well-structured: a summary line followed by bulleted argument explanations. Every sentence adds value; no fluff. It is front-loaded with the core purpose.

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

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

Given no output schema, the description adequately explains return fields (populationSize, sample, truncated, scanTruncated). It covers key constraints and edge cases. However, it could mention the output format or provide a brief example for completeness.

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

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

Schema coverage is 0%, so the description compensates fully. It explains each parameter: framework with examples, control_id with placeholder, since/until as ISO timestamps, sample_size as integer. This adds essential meaning beyond the bare 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 clearly states the tool reads evidence rows for a single control, along with population size and reproducible query. It specifies the verb (READ) and distinct resource, differentiating from sibling tools that operate on multiple controls or summaries.

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 fetching evidence for a single control but does not explicitly state when to use it versus alternatives like coverage_summary or gap_analysis. No when-not-to-use or alternative guidance is 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?

The description labels the tool as [READ] indicating it is a read operation, and lists framework options. However, it fails to describe the output format or what 'coverage' entails, lacking detail on behavioral aspects beyond the basic read nature.

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

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

The description is concise and includes a structured 'Args' section. It front-loads the purpose with [READ] and avoids extraneous content, but the brevity leaves some gaps.

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, the description should explain what the tool returns (e.g., coverage metrics per control). It does not, leaving the agent uncertain about the output structure. For a read tool with 3 parameters, this is a notable omission.

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 coverage, the description compensates by defining framework values (hipaa, pci_dss, soc2, gdpr) and explaining since/until as ISO timestamps bounding the period. It adds meaning beyond the schema, though it could note that since/until are optional.

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 per-control coverage for a framework over a period, with the question 'are we covered?' clarifying its intent. However, it does not explicitly differentiate from sibling tools like gap_analysis or control_evidence.

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 explains what the tool does, without any context on when it is appropriate or when to choose other 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 carries the full burden of behavioral disclosure. It indicates the tool is read-only via '[READ]' and describes the content type. However, it lacks details on performance, permission requirements, aggregation, or pagination, leaving gaps in 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 concise, with a clear header and parameter explanations. The sentence about 'denials prove governance' adds minor fluff but does not detract significantly. Overall, it is well-structured and efficient.

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

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

Given no output schema, the description does not explain the return format or structure. The mention of 'enforcement + anomaly evidence' is vague. In the context of 17 sibling tools, more differentiation and completeness regarding output would be beneficial for an agent to select 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?

Schema description coverage is 0%, so the description must compensate. It explains that 'since' and 'until' are ISO timestamps bounding the period, which adds meaningful context. Although more detail on optionality could be provided, this is sufficient for understanding the 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 the tool's purpose: reading denied/error/budget-exceeded operations, providing enforcement and anomaly evidence. The prefix '[READ]' explicitly marks it as read-only. This distinguishes it from sibling tools like approval_report or query_audit_events which focus on approvals or general audit events.

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 does not provide explicit guidance on when to use this tool versus alternatives. It only implies use for verifying enforcement via denials. No mention of prerequisites, when not to use, or comparisons with siblings like query_audit_events or coverage_summary.

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 responsibility of disclosing behavior. It openly marks the operation as WRITE with medium risk, describes file output (including the .oscal.json naming), and outlines key limitations of the OSCAL format (unresolved control IDs, no 'partially satisfied' state). It does not address overwrite behavior or permissions, but the disclosed details are substantial and actionable.

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 well-structured with a clear one-line summary followed by a focused OSCAL caveat and a compact Args block. Every sentence provides necessary information; the OSCAL note is relevant because it explains a critical edge case and points to an alternative.

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 no annotations and no output schema, the description covers the essential aspects: input formats, output behavior, file naming, and key limitations. It could mention what the function returns (if anything) or overwrite semantics, but the current content is sufficient for an agent to select and invoke the tool correctly in most contexts.

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 fully compensates by explaining every parameter: bundle_path (path to bundle .json), fmt (enumerated allowed values), and out_path (default behavior alongside the bundle). This adds meaning that the bare schema lacks and enables correct invocation.

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

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

The description clearly states the tool renders a bundle to markdown, CSV, JSON, or OSCAL formats, with a specific verb ('Render') and resource ('bundle'). It also distinguishes itself from the sibling tool oscal_assessment_results by noting that this tool writes a file while the sibling provides inline output.

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

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

The description gives clear context for when to use this tool (to render a bundle to a file) and explicitly directs users to read oscal_assessment_results first when inline output and limitations are needed. It does not exhaustively enumerate exclusions but provides sufficient guidance for choosing between the primary alternatives.

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 states the tool is read-only and includes a caveat about evidence strength, but fails to discuss auth requirements, rate limits, or any side effects. The output format is only vaguely described, lacking details on pagination or structure, which is insufficient for a tool with zero annotations.

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

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

The description is concise and front-loaded with the purpose and read indicator. Every sentence adds value: the overall function, the evidence caveat, and clear parameter explanations. No redundant or irrelevant 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?

The tool has three parameters and no output schema. The description adequately explains the purpose and parameters, but does not detail the exact structure of the returned data (e.g., list of items with fields). Given the complexity of gap analysis, a bit more information about the output format would enhance completeness, but the current level is minimally viable.

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 0% parameter description coverage, so the description must compensate. It explains that 'framework' accepts values like hipaa, pci_dss, soc2, gdpr, and that 'since'/'until' are ISO timestamps bounding the period. This adds significant meaning. However, it does not specify the exact ISO format (e.g., ISO 8601) or provide examples, preventing a perfect score.

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 is a read operation that identifies controls with no or weak evidence, providing reasons and remediations. It distinguishes itself from sibling tools focused on audit sources, events, or bundles by specifying the gap analysis function. However, it does not explicitly differentiate from similar tools like 'coverage_summary' or 'control_evidence', so it's slightly less precise than the high standard.

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 does not provide any guidance on when to use this tool versus its siblings. It mentions a caveat about audit trails vs design evidence, but this is a behavioral note, not a usage directive. There is no explicit 'when to use' or 'when not to use' information, nor any mention of alternative tools for specific 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?

Without annotations, the description fully handles behavioral disclosure: it declares a WRITE operation (risk=medium), details side effects (reads audit DBs, writes to ~/.compliance-aiops/bundles/), and explicitly states it touches no external system. This is comprehensive for a tool with no annotations.

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

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

The description is efficiently structured: first paragraph conveys purpose and key behaviors, second paragraph details parameters. Every sentence adds value, with no wasted words. It is front-loaded with the most critical information.

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

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

Given 6 parameters, no output schema, and no annotations, the description covers purpose, side effects, parameter details, and safety. It lacks return value details, but that is somewhat expected without an output schema. Overall, it is sufficient for agent invocation.

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

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

Schema description coverage is 0%, but the description comprehensively explains each parameter, including framework's allowed values, period_start/period_end as ISO timestamps, out_path default, sign behavior, and period's role as a convenience override. This adds significant meaning 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 clearly states the tool assembles and hash-chain-seals an evidence bundle for a framework, with specific verb-resource combo and scope. It distinguishes from siblings like verify_bundle and sign_bundle by emphasizing it writes a local artifact and doesn't touch external systems.

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 a happy-path usage scenario ('One-call happy path') but does not explicitly state when to use this tool versus alternatives like verify_bundle or sign_bundle. Exclusion criteria or prerequisites are absent.

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 bears full responsibility. It marks the operation as '[READ]' and describes the action, but lacks details on failure cases, permissions, or side effects. For a zero-parameter read operation, this is adequate but not exemplary.

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: the first delivers the core functionality, the second provides usage guidance. Every sentence adds value; no redundant or vague language.

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

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

Given the tool's simplicity (no parameters, no output schema), the description is complete: it specifies what is listed, the file location pattern, the information returned, and a usage hint. It does not mention prerequisites or error conditions, but these are minor omissions for a non-destructive listing 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 tool has zero parameters, and the empty schema has 100% coverage. The description correctly adds no parameter info, meeting the baseline of 4 for tools with no 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 uses a specific verb ('List') and resource ('sibling audit DBs'), clearly distinguishes from sibling tools by focusing on enumeration of available audit sources, and explains what info is returned (readability + row counts). It also provides a usage hint, making its purpose 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 explicitly states 'Call this first', indicating it is a preparatory step before other audit tools like query_audit_events. While it doesn't explicitly list when not to use it or name alternatives, the directive is clear and sufficient for the tool's simple nature.

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?

Without annotations, the description carries the full burden. It mentions '[READ]' but does not disclose rate limits, pagination behavior, authentication requirements, or any potential side effects. The tool is a simple list but behavioral details are lacking.

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, clear sentence with a '[READ]' tag front-loads the action. Every word earns its place; 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?

With no output schema and no annotations, the description is minimal. It explains what is listed but does not define 'chain head' or metadata fields. Given the sibling tools, more context would help an agent decide when to use it, but it is adequate for a simple list operation.

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 schema coverage is 100%, so no parameter clarification is needed. The description adds value by specifying what is returned (chain head and metadata), which complements the empty 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 clearly states the tool lists previously generated bundles with chain head and metadata, using a '[READ]' prefix to indicate read-only action. It uniquely identifies the resource and distinguishes from creating, verifying, or exporting bundles.

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 verify_bundle or generate_evidence_bundle. The description does not explain when not to use it or suggest any prerequisites.

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

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

The description includes '[READ]' indicating read-only behavior, which is helpful given no annotations. It does not disclose caching, rate limits, or data freshness, but for a simple list tool, this is adequate.

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

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

Single sentence, no wasted words. It is front-loaded with the READ tag and clearly conveys the tool's purpose.

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

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

Considering no parameters or output schema, the description is sufficiently complete. It specifies the output includes control counts, which is the key information an agent needs.

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

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

No parameters exist, so the description does not need to add parameter meaning. Schema coverage is trivially 100%, and baseline is 4 per rubric.

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

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

The description clearly states the tool lists supported compliance frameworks (HIPAA, PCI-DSS, SOC 2, GDPR) and control counts, using a specific verb and resource. It distinguishes from sibling tools like list_audit_sources which list audit sources instead.

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 when-to-use or alternatives are provided. However, the tool is simple with no parameters, so usage is straightforward. Some guidance comparing to coverage_summary or gap_analysis would improve this.

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 burden and delivers: returns inline, includes summary and limitations, deterministic UUIDs, and three specific OSCAL limitation workarounds (import-ap point, unresolved control ids, partial satisfaction handling). This is substantial behavioral disclosure beyond the input schema.

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

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

Description is front-loaded with [READ] and the core purpose, then uses each sentence to disclose consequential behavior. The length is justified by the lack of annotations and the need to explain uncommon OSCAL limitation handling.

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

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

With no output schema and no annotations, the description covers return format, summary/limitations, determinism, param origin, and edge-case behavior. Nothing critical appears missing for selecting and invoking this 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 0% but the single parameter is described in Args: 'Path to a bundle .json (from list_bundles)'. This adds type/provenance beyond the raw string schema, though it does not elaborate further.

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?

Opens with '[READ] A sealed bundle as an OSCAL 1.2.3 Assessment Results document', naming a specific verb (read/convert) and resource. It distinguishes itself from export_bundle by noting writing a file is export_bundle's job.

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?

Explicitly names export_bundle as the sibling for file writing and points to list_bundles for obtaining bundle_path. This gives clear when-to-use/when-not-to-use 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?

Without annotations, the description carries the full burden. It labels the tool as read-only, explains the return format including 'truncated' flag, and warns against characterizing from truncated results. Missing auth/rate limit info, but otherwise transparent.

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: a one-line summary, a bulleted arg list, and a return description with warning. No redundant sentences, well-structured for quick scanning.

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 10 parameters, no enums, and no output schema, the description covers all necessary aspects: purpose, all parameter semantics, return format, and a critical behavioral caveat (truncation). Complete for effective 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?

With 0% schema coverage, the description provides detailed explanations for all 10 parameters (e.g., 'source', 'approved', 'selector') that the input schema lacks. Adds meaning and usage context beyond type and default.

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

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

The description clearly indicates a cross-tool audit event query with '[READ]' and 'the workhorse'. It distinguishes itself from sibling tools like 'undo_apply' and 'activity_timeline' by being a general query tool, though it could be more explicit about its scope.

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

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

No explicit guidance on when to use this tool versus alternatives such as 'activity_timeline' or verification tools. The description only warns about truncated results, which is a behavioral note, not a usage comparison.

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?

Discloses risk level and reads encrypted store. No annotations provided, so description carries full burden; could detail output/return but sufficient.

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?

Concise with structured tags and clear sections. Front-loaded with risk level and action.

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?

Adequate for a single-parameter tool with no output schema. Covers purpose, prerequisite, risk, and parameter type.

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?

Only one parameter 'bundle_path' with description 'Path to a bundle .json' adds format context beyond schema title. Schema coverage 0% but description compensates minimally.

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

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

Description clearly states the action 'Attach an HMAC signature over a bundle's seal' with specific verb and resource, distinguishing it from siblings like verify_bundle.

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?

Describes prerequisite (signing key in encrypted store) and implies when to use. Lacks explicit when-not but provides context for medium risk.

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?

Despite no annotations, the description fully discloses behavioral traits: it is a write operation ([WRITE][risk=medium]), dispatches inverse tool, dry_run previews without execution, and token single-use. This is comprehensive for a tool without annotations.

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

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

Well-structured with a header, description, and Args list. Slightly verbose with redundant '[WRITE][risk=medium]' but overall concise and front-loaded with key information.

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

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

Covers essential behavior: inverse tool dispatch, dry_run, token single-use. Lacks explicit mention of return values or error handling, but no output schema exists. Adequate for the tool's moderate complexity.

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

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

Adds significant meaning beyond schema: explains undo_id source (from undo_list or _undo_id), target passed through to inverse tool, and dry_run purpose. Schema has 0% description coverage, so the description compensates fully.

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

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

The description clearly states the tool's purpose: 'Apply a recorded undo by dispatching its inverse tool.' This distinguishes it from sibling tools like undo_list, which lists undos, making the purpose 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?

Provides specific guidance: use dry_run to preview, token can only be applied once. However, it lacks explicit comparison to alternatives or when not to use the tool, though context signals imply its unique role among siblings.

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 fully carries the burden. Explains truncation measurement, meaning of 'effectVerified', and notes that 'target' is unused but accepted for uniformity.

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?

Front-loaded purpose, each sentence adds value. Slightly verbose in places but still efficient and well-structured.

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, includes return format example. Covers parameters, behavior, truncation, and effectVerified caveat comprehensively.

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

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

Schema coverage is 0%, so description compensates well. Explains 'limit' (max rows, default 50, cap 500) and 'target' (unused). Could be more detailed about data types.

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

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

Starts with '[READ] List recorded, not-yet-applied undo tokens (most recent first)', immediately clarifying it's a read-only listing tool. Differentiates from sibling 'undo_apply' which actually applies the undo.

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?

Explicitly instructs to use 'undoId' with 'undo_apply'. Warns about 'effectVerified' field and advises checking live state. Could be improved by stating when not to use 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 full burden. It declares read-only behavior and verification scope, but does not disclose side effects, requirements (e.g., file access), or what happens on verification failure.

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: two lines for purpose and one line per parameter. No filler or redundancy. Every word earns its place.

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

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

Given a simple 1-parameter tool with no output schema, the description covers the essential purpose and parameter context. Missing details on return value or verification outcome, but not critical for selection.

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, bundle_path, has 0% schema description coverage. The description adds meaning by specifying the expected format ('Path to a bundle .json produced by generate_evidence_bundle'), which aids correct invocation.

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

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

The description clearly states it is a read operation that verifies a sealed evidence bundle, listing specific aspects: chain integrity, seal head, signature. This differentiates it from sibling tools like generate_evidence_bundle (creates) and sign_bundle (signs).

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 '[READ]' prefix hints at read-only usage, but no explicit when-to-use or when-not-to-use guidance is provided. Sibling tools like verify_source_chain may be alternatives, but no comparison is given.

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 explicitly marks the tool as read-only ([READ]) and mentions that row-id gaps may indicate deleted audit rows, providing behavioral insight. However, with no annotations, it does not disclose potential side effects, authorization requirements, or performance implications.

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

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

The description is concise, with a clear summary line and an Args section. It front-loads the main purpose and provides essential usage guidance without unnecessary detail.

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

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

Given the tool's simplicity (3 parameters, no output schema), the description explains the purpose, output (chainHead, gap detection), and usage pattern. It does not cover error conditions or permissions, but for an audit verification tool, the provided information is sufficient for basic 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 description adds context to the 'source' parameter by linking it to list_audit_sources, and explains 'since/until' as ISO timestamps bounding the range. This adds value beyond the schema (which only defines types), but lacks format examples or boundary details like inclusive/exclusive.

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 verifies the source chain by returning chain head and detecting row-id gaps. The [READ] prefix indicates it's a read operation. It distinguishes from siblings like verify_bundle by focusing on source chain rather than bundle, but does not explicitly differentiate from query_audit_events.

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 advises recording the chainHead and re-running later to detect changes, implying periodic use. However, it does not explicitly specify when to use this tool versus alternatives like query_audit_events or verify_bundle, nor does it mention prerequisites or restrictions.

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