AINumbers Fintech Intelligence Suite

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds context beyond annotations by stating it is browser-based, client-side only, with zero PII and zero network, reinforcing the safe, non-destructive behavior. However, it does not detail the export mechanism or return format.

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 (three sentences) and front-loaded: the first sentence captures the core purpose, followed by safety and implementation details. Every sentence adds value without redundancy.

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

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

Given the complexity (nested input object, output schema present), the description covers the main simulation features and safety aspects. It references the manifest input_schema and output schema, so completeness is high, though it could elaborate on the Policy Mandate format.

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 sole parameter 'inputs' has a generic schema description, but the tool description adds specific context by listing the kinds of inputs (spend caps, MCC allowlists, etc.), thus enhancing understanding 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 simulates agent payment policies for tokenized A2A corridors, with specific capabilities (spend caps, MCC allowlists, etc.), and exports a Policy Mandate. This distinguishes it from sibling tools like 'simulate_spend_policy' by specifying the context and 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 does not provide guidance on when to use this tool versus alternatives. It lacks explicit when-to-use, when-not-to-use, or references to sibling 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?

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds critical behavioral details beyond these: deterministic in-browser execution, zero PII, zero egress, and export of an AP2 artifact with execution_hash. No contradiction with annotations.

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

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

The description is reasonably concise and front-loaded with the tool's purpose. However, it includes specific artifact IDs and a URL that may be considered noise for general understanding, slightly reducing efficiency.

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

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

Given no output schema, the description explains the output (AP2 artifact with execution_hash) and lists consumed/produced artifacts. However, it lacks detail on the structure or content of the output artifact and does not clarify when this specific aggregation is needed versus other similar tools.

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

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

Schema coverage is 100%, and the schema already provides descriptions for all 4 parameters. The description does not add any additional meaning or context for the parameters beyond what is in the schema, so it meets the baseline of 3.

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 an aggregator for CBAM precursor emissions, specifying its role as an OpenChainGraph compute node with deterministic execution. However, it does not explicitly differentiate from sibling aggregate tools like aggregate_execution_receipts or aggregate_ownership_50pct, leaving some ambiguity about when to choose this tool over others.

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 names upstream and downstream artifacts (art-68, art-69, cry-04) and provides a URL, but it gives no explicit guidance on when to use or avoid this tool. There are no when-not or alternative recommendations, leaving the agent to infer usage from context.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable context: 'Runs deterministically in-browser; zero PII, zero egress', explicitly confirming privacy and execution model. No contradiction with annotations.

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

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

The description is dense with specifications (inputs, outputs, URL) but avoids fluff. Sentences are efficient for the domain's complexity. 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?

The description provides high-level role and constraints (in-browser, zero PII) but lacks output schema description (none exists) and usage guidance. Given 4 parameters with nested objects, additional detail on return values or parameter relationships would improve completeness.

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

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

Schema coverage is 100% with each parameter having a description. The tool description does not elaborate on parameters further; it only lists upstream/downstream artifacts. Baseline 3 is appropriate as schema handles semantics.

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

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

The description clearly states the tool as an 'Agent-Action Audit-Trail Aggregator' with specific technical details: deterministic in-browser execution, zero PII, exports AP2 artifact with execution_hash. It identifies a unique purpose, though it does not explicitly distinguish from sibling tools. The name and description are sufficiently specific.

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

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

No explicit guidance on when to use this tool or alternatives. The description focuses on technical behavior rather than usage context. No mention of prerequisites, trade-offs, or comparison with 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?

The description adds valuable behavioral context beyond the annotations: it runs 'deterministically in-browser', has 'zero PII, zero egress', and exports an artifact with 'execution_hash for chain provenance'. These details disclose data safety and determinism, which complement the readOnlyHint and idempotentHint annotations. No contradiction with annotations is present.

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 brief (two sentences plus a list of upstream/downstream and a URL). It front-loads the tool's identity and key properties. The list of artifacts adds context without redundancy. Some repetition ('Ownership 50%-Rule Aggregator' in both title and description) is minor. Overall efficient for the information conveyed.

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 an output schema, the description could clarify the output structure beyond an execution_hash. It also does not explain the '50% rule' concept or how policy_parameters are used. The deterministic and zero-egress properties cover safety, but for a tool with nested objects and no output schema, more details about the AP2 artifact fields would improve completeness.

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

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

The input schema has 100% description coverage, with each parameter described (compute mode, parent_hashes, parent_tool_ids, policy_parameters). The description does not add further detail beyond what the schema provides, such as expected formats or examples. It mentions the output artifact conceptually but does not enhance parameter understanding. Baseline 3 is appropriate.

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

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

The description clearly identifies the tool as an 'Ownership 50%-Rule Aggregator' and an OpenChainGraph compute node for compliance. It states the core function (aggregate ownership based on a 50% rule) and distinguishes it as a deterministic in-browser operation, but does not explicitly differentiate it from sibling aggregators like aggregate_cbam_precursor_emissions or aggregate_taxonomy_kpi_gar, which serve similar functional roles.

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 usage context by listing upstream artifacts (art-90-sanctions-screening-fit-diagnostic) and downstream consumers (art-92-screening-list-coverage-checker, cry-05-agent-action-audit-trail-aggregator), indicating its place in a processing pipeline. However, it offers no explicit guidance on when to choose this tool over alternatives or when not to use it, leaving the agent to infer suitability.

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

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

Annotations declare readOnly, idempotent, non-destructive. The description adds valuable context: deterministic in-browser execution, zero PII, zero egress, and exports an AP2 artifact with execution_hash. This enhances understanding of behavior beyond the annotations.

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

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

The description is concise but dense with jargon (OpenChainGraph, attestation_mandate, AP2 artifact). It is front-loaded with the title, but the technical overload may hinder clarity. Could be more accessible.

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

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

Despite 100% schema coverage and good annotations, the description lacks an explanation of what constitutes a reputation score, how aggregation works, or what policy_parameters represent. The output artifact is mentioned but no output schema exists. The URL provides external detail, but the description alone is incomplete for an agent to fully understand the tool's purpose and usage.

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

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

Schema coverage is 100%, so baseline is 3. The description does not add additional meaning to the parameters; it repeats the schema's description of policy_parameters. No extra interpretation or guidance is provided.

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 title and description indicate it aggregates reputation scores, but the description focuses on technical execution details (in-browser, zero egress, AP2 artifact) rather than clearly stating what the tool computes or when to use it. The core function is implied but not explicit.

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 vs alternative aggregate tools (e.g., aggregate_cbam_precursor_emissions) or any prerequisites. Sibling tools are not differentiated.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context beyond annotations: it 'runs deterministically in-browser', 'zero PII, zero egress', and exports an 'AP2 artifact with execution_hash for chain provenance'. This clarifies safety and execution characteristics, enhancing 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 (three sentences), front-loads the purpose, and each sentence adds distinct information: purpose and classification, execution environment and safety, and provenance links. No fluff or redundancy; it is well-structured for quick comprehension.

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

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

Despite the richness of annotations and schema, the description lacks key contextual details. It does not explain what the tool actually aggregates (e.g., what 'Taxonomy KPI' or 'GAR' means), nor does it describe the output structure beyond mentioning an 'AP2 artifact'. The complex 'policy_parameters' object is left entirely unexplained. For a tool with nested objects and no output schema, this is insufficient.

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

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

The input schema has 100% description coverage, so the baseline is 3. The description does not add any parameter-specific meaning beyond what the schema already provides. Parameters like 'compute', 'parent_hashes', 'parent_tool_ids', and 'policy_parameters' are adequately described in the schema but not elaborated further in the description.

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 'Taxonomy KPI & Green Asset Ratio Aggregator' and an 'OpenChainGraph compute node'. While it conveys the general purpose of aggregating taxonomy-related metrics, it does not explicitly differentiate from sibling tools like 'aggregate_cbam_precursor_emissions' or 'aggregate_execution_receipts', which have similar names but different outputs.

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 mentions it consumes from a specific upstream artifact ('art-73-taxonomy-alignment-scorer') and outputs to a downstream tool, implying usage in a chain. However, it lacks explicit guidance on when to use this tool versus alternatives, nor does it state prerequisites or exclusions. The context is implied but not actionable.

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

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

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds significant behavioral context: deterministic in-browser execution, zero PII, zero egress, and export of AP2 artifact with execution_hash. This provides safety and operational transparency beyond annotations.

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

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

The description is a single paragraph front-loaded with the tool's name and purpose. It efficiently covers key points without redundancy. The inclusion of a direct URL to the tool page is slightly extraneous but does not detract significantly.

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 complexity (4 parameters, nested objects, no output schema), the description explains the tool's role in the chain graph, its dependencies, and its output artifact. It hints at return behavior by mentioning the AP2 artifact and execution_hash, providing sufficient context for an agent to understand the tool's place in a workflow.

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

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

Schema description coverage is 100%, so baseline is 3. The free-text description does not elaborate on parameter meaning beyond what is in the schema. The schema already describes parameters like compute mode and parent_hashes adequately, so no additional semantics are provided.

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 an 'IHB Interest Allocation' compute node, clearly stating its role as an OpenChainGraph analytics node. It distinguishes itself from siblings by specifying upstream dependencies and the deterministic in-browser execution, but the allocation function itself is implied rather than detailed.

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 lists specific upstream artifacts that this tool consumes, implying it should be used after those tools are executed. However, it does not explicitly state when to use this tool versus alternatives, nor does it provide explicit exclusion criteria or alternative tools.

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

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

Annotations already indicate read-only and idempotent behavior. The description adds valuable context beyond annotations: it runs deterministically in-browser, zero PII, zero egress, and exports an artifact with execution_hash. This provides transparency on data handling and output, with no contradiction to annotations.

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

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

The description is a single paragraph of four sentences, front-loaded with the primary purpose. It is concise and contains no superfluous information. However, a more structured format (e.g., bullet points) could improve readability for an AI agent.

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

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

The description explains the tool's role in a pipeline and its deterministic behavior, but it does not describe the return value or the structure of the exported artifact. Given the absence of an output schema, the description should provide more detail on what the tool returns to be fully complete.

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

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

Schema description coverage is 100%, so the schema already fully describes all parameters. The description does not add any additional meaning or usage context for the parameters beyond what is in the schema. Baseline score of 3 applies.

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 an 'ASC 340-40 Commission Amortization' compute node, which is a specific verb-resource pair. It distinguishes itself from siblings by being a specialized compliance mandate for commission amortization under ASC 340-40, and the context of being part of a chaingraph with upstream artifacts sets it apart.

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 after reconciling commission statements ('Consumes upstream artifacts from: art-266-reconcile-commission-statement'), but it does not explicitly state when to use this tool versus alternatives. No exclusions or context about when not to use it are provided.

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

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

The description adds behavioral details beyond annotations: runs deterministically in-browser, zero PII/egress, exports AP2 artifact with execution hash for chain provenance. These details align with the read-only, idempotent, non-destructive hints from annotations and provide useful context.

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

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

The description is concise, with 4 sentences covering purpose, behavior, outputs, and link. It is front-loaded with the tool name. However, it could be more streamlined by removing the URL if not essential.

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 complexity (4 params, no output schema), the description covers execution environment, artifact export, and output feed. However, it fails to explain what the tool actually returns (e.g., format of the AP2 artifact) or the meaning of 'AP2' and 'chain provenance' for an agent unfamiliar with the domain.

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

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

All 4 parameters are described in the schema (100% coverage), so the description adds no extra semantic value. Baseline 3 is appropriate. The mention of 'policy_parameters' as decision function input offers minimal extra context.

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

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

The description states it is a 'Prediction Market Analyzer' and an 'OpenChainGraph compute node (event_market_pnl)', which clearly identifies the tool's purpose as analyzing prediction markets, specifically computing profit/loss. The verb 'analyze' is somewhat generic, but the resource is specific.

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

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

No explicit guidance on when to use this tool versus its siblings. The description mentions output feeds to a specific artifact but does not distinguish from related tools like 'find_prediction_arbitrage' or provide contexts for selection.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds value by specifying deterministic in-browser execution, zero PII, zero egress, and the export of an AP2 artifact with execution_hash for chain provenance, which provides helpful behavioral context beyond annotations.

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

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

The description is concise and front-loaded with key purpose and behaviors. However, it includes a URL that is not essential for tool usage and mixes declarative statements with operational details, slightly reducing clarity.

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

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

Given the tool's complexity (4 parameters, nested objects, no output schema), the description provides a reasonable overview of purpose and behavior. It mentions the output artifact and its downstream use, but additional details about the artifact structure or exact integrity mechanism would improve completeness.

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

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

Schema coverage is 100% with descriptions for all 4 parameters. The description does not add any additional meaning or context to the parameters, so the baseline of 3 is appropriate.

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

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

The description clearly states it anchors document integrity and eIDAS electronic timestamps, specifies it is an OpenChainGraph compute node for compliance mandates, and details its deterministic in-browser execution and artifact export. This distinguishes it from sibling tools like verify_timestamp_attestation by highlighting its role as a compute node producing an AP2 artifact.

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

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

The description implies usage is for document integrity anchoring and mentions the output feeds another tool, but lacks explicit guidance on when to use this tool versus alternatives or any exclusions. It does not state prerequisites or context.

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

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

Annotations already indicate readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable context: it is browser-based, client-side only, zero PII, and zero network, which goes beyond annotations to clarify execution environment and data handling.

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 relatively concise, with three sentences front-loading the purpose. However, it includes jargon like 'Cat-12' and 'AIN Bridge' that may be unclear, slightly reducing 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?

The description mentions the output type (Policy Mandate JSON) and client-side execution, but lacks details on output structure or usage of the output schema. Given the presence of an output schema, the description is moderately complete but could be more explicit.

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 'inputs' with a generic description. The tool description does not explain what specific input IDs or values are expected, relying on an external manifest. This fails to add 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 translates AML/BSA controls, TM rules, and customer risk policy into a structured Policy Mandate JSON for agentic payment systems. It identifies the specific verb 'Translate' and the resource, distinguishing it from siblings like 'validate_ap2_mandate_chain'.

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. It is described as an 'anchor agentic tool for Cat-12', but does not specify when not to use or provide context for selecting 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?

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable behavioral context beyond annotations: it runs 'deterministically in-browser; zero PII, zero egress', and explains the artifact export with 'execution_hash for chain provenance'. This informs the agent about execution model and data safety.

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 paragraph of five sentences, each adding unique information: purpose, execution model, artifact output, inputs, outputs, and a URL. No redundancy, front-loaded with key details.

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

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

Given four parameters (one nested) and no output schema, the description provides necessary context: execution environment, data privacy, chain provenance, specific artifact IDs for inputs and outputs, and a URL for further details. It does not explain the mathematical application of scenarios but the name and upstream artifacts imply the context. Nearly complete.

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

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

Schema description coverage is 100%, and the input schema already describes all four parameters in detail (e.g., compute, parent_hashes, parent_tool_ids, policy_parameters). The tool description does not add new semantic information about parameters; it repeats the linkage to upstream artifacts but does not clarify parameter usage 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's purpose: 'Climate Scenario Applicator (NGFS / Fit-for-55)' specifies the domain and scenario families. It explains it is a 'compute node' that runs deterministically, exports artifacts, and lists specific upstream and downstream artifacts, distinguishing it from sibling tools that are about auditing, scoring, or building.

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 explicitly state when to use this tool versus alternatives. It mentions upstream and downstream dependencies, implying it should be used after upstream artifacts are ready and before the downstream aggregator, but no explicit recommendations or exclusions are 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?

Annotations already indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds behavioral specifics: deterministic in-browser execution, zero PII, zero egress, and artifact export with execution_hash for chain provenance. This context enhances understanding beyond annotations. There is no contradiction; the export of an artifact is consistent with non-destructive, read-only behavior as it creates a new artifact without modifying upstream state.

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 paragraph with essential information front-loaded: tool identity, behavior, and context. It includes specific artifact IDs and a URL. It is not overly long, though it could be slightly more structured. Overall, it earns its place without unnecessary 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?

Given the annotations cover safety and idempotency, and the schema covers parameters, the description provides chain context (upstream/downstream) and execution environment. However, it lacks details about the output artifact structure (no output schema) and does not fully explain the 'compute' parameter beyond its enum options. This leaves some gaps for a tool with nested objects and complex usage.

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

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

Schema coverage is 100% with clear descriptions for all parameters. The description does not add significant semantic value beyond the schema; it mentions consuming upstream artifacts which relates to 'parent_hashes' and 'parent_tool_ids' but does not elaborate further. The description minimally supplements the schema, meeting the baseline expectation.

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

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

The description clearly states it's an 'Evidence Pack Assembler' for 'AIUC-1', an OpenChainGraph compute node. It specifies deterministic in-browser execution, zero PII/egress, and exports an AP2 artifact with execution_hash. It distinguishes itself from sibling tools like 'lint_aiuc1_control_evidence' by explicitly listing upstream and downstream tools, making its role in the chain unambiguous.

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

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

The description provides explicit context on when to use this tool: it consumes artifacts from 'art-303-aiuc1-control-evidence-linter' and 'cry-05-agent-action-audit-trail-aggregator' and outputs to 'art-305-aiuc1-evidence-freshness-lint'. This implicitly advises using it when those upstream artifacts are available. However, it does not directly state when not to use it or compare to alternatives like 'build_226j_response_evidence_pack'.

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

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

Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds transparency by stating it runs deterministically in-browser with zero PII and zero egress, and exports an artifact with execution_hash for provenance. This aligns with annotations and provides valuable behavioral detail.

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 (three sentences) and front-loads the purpose before adding behavioral traits. It could be slightly more structured, but it is efficient and contains no redundancy.

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

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

Given the four parameters and no output schema, the description provides the chain context and behavioral properties but does not explain what the output artifact contains (e.g., assembled license terms). This gap prevents a higher score.

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

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

Schema coverage is 100% with descriptions for all four parameters. The tool description does not add additional semantic value beyond what the schema provides. The baseline of 3 is appropriate.

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

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

The description clearly states it is an 'OpenChainGraph compute node' that 'assemble_license_terms' and exports an AP2 artifact. It distinguishes from siblings by specifying upstream and downstream artifact IDs, making its role in the pipeline unique.

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

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

The description provides context on when to use the tool (as part of a ChainGraph workflow for license terms) and mentions it consumes from and feeds into specific tools. It does not explicitly state when not to use it, but the pipeline context is sufficient.

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 provide readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds context about deterministic in-browser execution and zero PII/egress, which is helpful. However, description states 'Exports an AP2 artifact', potentially contradicting readOnlyHint=true (export could be a side effect). Flagging as contradiction.

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

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

The description is relatively long (multiple sentences) and includes a URL, but the first sentence is unclear jargon ('Mutual NDA Composer: OpenChainGraph compute node (compliance_mandate)'). It could be more concise and front-load 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?

No output schema, but description mentions output feeds into 'art-277-agreement-acceptance-binder', providing some context. However, it does not explain the AP2 artifact contents or how to use the output, leaving gaps for a tool with complex nested parameters and no output schema.

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

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

Schema coverage is 100% with descriptions for all 4 parameters. The tool description does not add additional parameter information beyond what the schema provides, so baseline 3 is appropriate.

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

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

The title 'Mutual NDA Composer' and description indicate it composes a mutual NDA, but the description focuses on technical execution details (in-browser, AP2 artifact) rather than explicitly stating what the tool outputs or its primary function. It is somewhat clear but lacks a direct statement of purpose.

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

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

No guidance on when to use this tool versus siblings like 'assemble_license_terms' or 'bind_agreement_acceptance'. The description mentions technical constraints but no usage context or 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?

Annotations declare idempotentHint=true, readOnlyHint=true, and destructiveHint=false. The description adds valuable behavioral context: it runs deterministically in-browser, exports an AP2 artifact with execution_hash for chain provenance, consumes upstream artifacts, and provides a URL. This goes beyond annotations without contradicting them.

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 at four sentences and front-loaded with the title and purpose. While it conveys key details, a couple of phrases (e.g., 'OpenChainGraph compute node (compliance_mandate)') could be tightened without losing 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?

The tool involves a nested object parameter (policy_parameters) and no output schema. The description covers runtime behavior, artifact export, and upstream dependency, but does not describe the output format (AP2 artifact structure) or the diagnostic result. Given the complexity, more detail on outputs would improve completeness.

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

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

Schema coverage is 100% (all 4 parameters have descriptions). The description mentions consuming a specific upstream artifact ('art-133-agent-payment-rail-trust-crosswalk') as an example, but does not add meaning beyond the schema's parameter descriptions. Baseline 3 is appropriate.

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

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

Title and description clearly identify the tool as a readiness diagnostic for agent directory publishing. It specifies it's an OpenChainGraph compute node with a compliance mandate. However, the description does not differentiate it from many sibling tools with similar 'assess_' prefixes, such as 'assess_ai_act_conformity' or 'assess_cra_vuln_reporting_readiness'.

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 among the many readiness diagnostics. No prerequisites, use cases, or exclusions are mentioned. The sibling list includes dozens of similar 'assess' and 'check' tools, but the description does not help an agent choose this one.

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 adds behavioral details beyond the annotations: 'Runs deterministically in-browser; zero PII, zero egress' clarifies execution environment and privacy properties. It also mentions export of an AP2 artifact with execution_hash for provenance. This complements the idempotentHint and readOnlyHint annotations without contradiction.

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

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

The description is a single paragraph that efficiently bundles purpose, regulatory deadline, behavioral traits, and output details. It is front-loaded with the tool's name and purpose, and each sentence adds value. Slightly dense but not overly verbose; could benefit from a more structured format but remains concise.

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

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

Given the tool's complexity (4 parameters, no required, no output schema), the description covers essential context: regulatory deadline, execution environment, zero PII/egress, output artifact type, and feeds. It does not detail the output schema (if any) but is sufficient for an agent to understand the tool's role and operational constraints.

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 provides full coverage (100%) with descriptions for all parameters. The description mentions policy_parameters as 'input parameters for this tool's decision function' but refers to the manifest for field names, adding little new meaning. The baseline of 3 is appropriate given schema coverage; the description does not significantly enhance 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 clearly states the tool's purpose: assessing EU AI Act conformity for credit-scoring. It specifies the regulatory context (EU AI Act Annex III Part 5(b)), mentions it's a compute node for model governance, and names output feeds. This distinguishes it from siblings like assess_iso42001_aims_conformance or run_ai_act_highrisk_fit by focusing on credit-scoring obligations.

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 contextual usage guidance (regulatory deadline, deterministic in-browser execution) but does not explicitly state when to use this tool versus alternatives or when not to use it. It implies use for credit-scoring conformity assessments under EU AI Act but lacks direct comparison to related tools.

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

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

Annotations already provide readOnlyHint, idempotentHint, destructiveHint. Description adds valuable context: deterministic execution, in-browser, zero PII/egress, and artifact export with execution_hash. No contradictions.

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?

Four sentences conveying key technical details without fluff. Front-loaded with title and compute node identity, but slightly dense with jargon (e.g., 'AP2 artifact', 'execution_hash') which may reduce clarity for some agents.

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?

Description covers technical details (determinism, privacy, artifact export) but lacks business purpose explanation and does not describe the output format beyond execution_hash. Without an output schema, more detail on return values would be helpful.

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

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

Schema coverage is 100% with descriptions for each parameter. The tool description does not add any additional parameter information beyond what the schema provides, so baseline of 3 is appropriate.

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

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

The title and name indicate it assesses circumvention diligence, but the description focuses on technical implementation (in-browser, zero PII, exports artifact) without clearly stating what circumvention diligence means or what the assessment produces. It lacks a specific verb+resource statement that distinguishes it from sibling assess tools.

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

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

No guidance on when to use this tool versus alternatives like assess_ai_act_conformity or assess_vida_readiness. The description mentions upstream and downstream artifacts but does not clarify use cases or exclusions.

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

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

The description adds valuable behavioral context beyond annotations: it runs deterministically in-browser, involves zero PII and zero egress, and exports an AP2 artifact with execution_hash for chain provenance. These details complement the readOnlyHint and idempotentHint annotations perfectly.

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 tool's title and nature. Every sentence provides useful information, though the URL is perhaps extraneous. The structure is efficient, earning a 4.

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 annotations, schema, and lack of output schema, the description covers key aspects: execution mode, safety, output details, and upstream dependency. It is fairly complete for a compute node tool, though explicit usage guidelines would improve it.

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

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

The input schema covers all four parameters with descriptions (100% coverage). The tool description does not add any additional meaning or usage guidance for the parameters, so it meets the baseline score of 3.

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 as assessing CRA Vulnerability Reporting Readiness (Art. 14) and that it is an OpenChainGraph compute node. It distinguishes from the sibling tool 'check_cra_annex1_completeness' by mentioning it consumes upstream artifacts from that specific checker.

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 context by stating it consumes upstream artifacts from 'art-139-cra-annex1-completeness-checker', suggesting it should be run after that tool. However, it does not explicitly state when to use it versus alternatives, or provide when-not-to-use 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?

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds meaningful context: 'Runs deterministically in-browser; zero PII, zero egress. Exports an AP2 artifact with execution_hash for chain provenance.' This explains execution environment, privacy guarantees, and output format, going beyond annotations. No contradiction detected.

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

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

The description is a single sentence plus a URL, conveying purpose, execution model, privacy, and artifact output without redundancy. Every sentence earns its place; no extraneous information.

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

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

Given the tool's complexity (4 parameters, no output schema), the description adequately explains the execution context, privacy, and that an artifact is exported with a hash for provenance. However, it lacks details on what the health assessment output contains, which slightly reduces 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 100% (4 parameters fully described). The description adds no additional meaning about parameters; it does not mention how parameters affect monitoring or output. Baseline 3 is appropriate per scoring rules.

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 monitors 'DeFi Lending Health and Liquidation', specifying both the verb (monitor/assess) and resource (DeFi lending). The mention of 'OpenChainGraph compute node (analytics_mandate)' and the URL further clarify its function, distinguishing it from siblings like 'assess_restaking_risk' or 'analyze_prediction_market'.

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 DeFi lending health monitoring and liquidation events, but does not explicitly state when to use this tool vs alternatives, nor does it provide exclusions, prerequisites, or context for when not to use it. It only describes execution characteristics.

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?

Beyond annotations (readOnly, idempotent), the description adds critical transparency: deterministic in-browser execution, zero PII/egress, artifact export with execution_hash, and chain provenance. These details confirm safety and operational 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 concise, front-loaded with the tool's identity, and adds useful context like the URL and artifact details. Every sentence contributes value, though the structure could be slightly more organized.

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 complexity (4 params, no output schema), the description adequately covers purpose, safety, output artifact, and downstream use. It lacks detail on conformance criteria but is sufficient for an AI agent to decide invocation.

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

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

Schema coverage is 100% with parameter descriptions. The description does not add extra parameter semantics beyond the schema, so baseline 3 is appropriate.

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

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

The description clearly identifies the tool as assessing ISO 42001 AIMS Clause Conformance, a compute node that runs in-browser and exports an AP2 artifact. It specifies the standard and clause type, distinguishing it from siblings like assess_ai_act_conformity.

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

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

No explicit guidance on when to use this tool versus alternatives. The description mentions it feeds into a specific validator but does not provide criteria for selection among many 'assess_' sibling tools.

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

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

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint false), the description adds useful behavioral details: runs deterministically in-browser, zero PII, zero egress, exports AP2 artifact with execution_hash for chain provenance. No contradiction with annotations.

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

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

The description is a single paragraph that front-loads the name and core purpose, then adds behavioral and workflow details. It is informative but slightly dense; could be more concise (e.g., 'Runs deterministically in-browser' is good but repeats from context). Still efficient for the information provided.

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 4 parameters (including nested objects) and no output schema, the description explains the artifact output and provenance but does not describe the output shape, the compute logic, or what the readiness assessment yields. Upstream/downstream links are helpful but incompleteness limits full understanding.

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% for 4 parameters; the description adds no parameter semantics beyond what the schema already provides. Baseline 3 is appropriate since the schema fully documents 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 identifies the tool as a 'MAR-Crypto Surveillance-Readiness Assessor' and an 'OpenChainGraph compute node' with a compliance mandate, indicating the specific verb (assess) and resource (MAR-Crypto Surveillance readiness). It distinguishes from siblings by naming a unique topic, though it does not explicitly differentiate from other assess tools.

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

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

The description mentions upstream and downstream artifacts ('Consumes upstream artifacts from: art-98-mica-casp-fit-diagnostic. Output feeds: cry-05-agent-action-audit-trail-aggregator') but does not provide explicit guidance on when to use this tool versus alternatives, no exclusions, and no context for selection among 200+ 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?

Annotations already declare read-only, idempotent, non-destructive. Description adds behavioral context: deterministic execution, no PII/egress, and artifact provenance with execution_hash. No contradictions. Adds value beyond annotations.

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

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

The description is a single concise sentence covering purpose, execution model, privacy, and artifact flow. No wasted words, but structure could be improved with bullet points.

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 4 parameters, no output schema, and sibling tools, the description covers core aspects (purpose, execution, provenance) but lacks usage guidance and parameter details. References a URL for more info.

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

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

Schema coverage is 100%, so baseline 3. Description provides context linking parameters to upstream/downstream artifacts but does not explain individual parameters (compute modes, parent_hashes, etc.) beyond 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 identifies the tool's function as assessing CASP authorization readiness under MiCA, specifying it as an OpenChainGraph compute node with deterministic in-browser execution, no PII, no egress, and artifact export. It distinguishes from siblings through its specific domain and artifact linkages.

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 sibling assessment tools (e.g., assess_ai_act_conformity). The description implies it's part of a chain graph for MiCA compliance but doesn't state scenarios for selection.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral context: runs deterministically in-browser, exports an AP2 artifact with execution_hash, consumes upstream artifacts, and operates with zero PII/egress. No contradictions with annotations.

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

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

The description is relatively concise and front-loads the core purpose. It includes a URL for access. However, it could be slightly tighter (e.g., 'Runs deterministically in-browser' and artifact details could be separate sentences). Still, each sentence provides unique 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 tool has 4 parameters (one nested) and no output schema, the description sufficiently explains the tool's role as a deterministic, non-destructive assessor that produces a provenance artifact. It details technical constraints and upstream dependencies. A mention of the output format would improve completeness, but overall it is adequate.

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 covers all 4 parameters with descriptions. The description adds context about consuming upstream artifacts (linking to parent_hashes/parent_tool_ids) but does not elaborate further. With 100% schema coverage, baseline is 3; this is adequate.

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

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

The description clearly states the tool performs a 'NAIC AI Systems Program Readiness Assessment' and specifies it is a compute node for compliance mandates. However, it does not differentiate this from numerous sibling tools that assess other regulatory programs (e.g., assess_ai_act_conformity, assess_iso42001_aims_conformance), leaving ambiguity about unique purpose.

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

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

No explicit guidance on when to use this tool versus alternatives. The description provides technical details (in-browser, zero PII) but does not specify the regulatory context (NAIC AI program) as a distinguishing factor or mention when not to use it.

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 indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds that it runs deterministically in-browser, zero PII, zero egress, and exports an AP2 artifact with execution_hash for chain provenance. This provides useful behavioral context beyond the annotations.

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

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

The description is concise (a few sentences) and front-loads the purpose. However, it includes a URL and a list of output feeds which could be considered clutter or better placed elsewhere. The structure is adequate but not optimal.

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

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

While parameters are documented, the description lacks explanation of what the readiness assessment produces. It mentions exporting an AP2 artifact but does not describe its contents or how to interpret results. The nested policy_parameters object is vaguely defined. With no output schema, more detail is needed.

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

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

All 4 parameters are described in the schema (100% coverage), so baseline is 3. The description mentions 'compute mode' and describes policy_parameters as inputs for the decision function, offering some extra context but not significantly more than 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 identifies the tool as a PSD3/PSR Readiness Checker and specifies it is an OpenChainGraph compute node for compliance mandates. The regulatory context and deadline are given, distinguishing it from other assess tools. However, the purpose could be stated more directly without jargon.

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 regulatory deadlines and notes that it runs in-browser with zero PII, but it does not guide when to use this tool over sibling tools like assess_ai_act_conformity or assess_mica_casp_readiness. No explicit when-to-use or when-not-to-use advice 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?

Annotations declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral details: runs deterministically in-browser, zero PII, zero egress, and exports an AP2 artifact with execution_hash. These go beyond annotations without contradicting them.

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 only three sentences but repeats the title in the first sentence, making it redundant. It is not overly long, but the repetition reduces efficiency. A more compact phrasing could improve score.

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 should explain the tool's return value. It merely mentions 'exports an AP2 artifact' without describing the artifact's contents or how to interpret the risk analysis. This is insufficient for an agent to understand the output.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds no parameter-specific information; the schema descriptions already cover the meanings. No additional value is provided by the description for 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 title and description clearly identify the tool as a 'Restaking Delegation and Slashing Risk Analyzer.' The description adds technical context (OpenChainGraph compute node, deterministic in-browser execution) but lacks explicit detail on what the analysis results look like. It distinguishes from sibling assess tools by the specific resource (restaking risk).

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. It does not mention prerequisites, when not to use, or comparisons to other assess tools. Agents receive no decision-making context.

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

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

Annotations already indicate readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable behavioral context: deterministic in-browser execution, zero PII, zero egress, exports AP2 artifact with execution_hash for provenance. This goes beyond annotations and informs the agent about safety and execution model.

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 paragraph of four sentences, each providing distinct information. It is concise but includes technical jargon. Could be slightly more front-loaded, but overall 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?

The description covers purpose, execution model, output (AP2 artifact), and upstream consumption. However, it does not explain the exact return value structure or when this node should be invoked in a workflow. Given the complexity of DSCSA compliance, more detail on prerequisites and downstream usage would improve completeness.

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

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

Schema description coverage is 100%, so the schema already documents parameters. The description adds implicit meaning by mentioning upstream artifact consumption, which relates to parent_hashes/parent_tool_ids. However, no explicit parameter details are provided 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 identifies the tool as a DSCSA Suspect/Illegitimate Product Quarantine Assessor, an OpenChainGraph compute node. It specifies the domain and the role, but does not explicitly differentiate from other assess_* siblings. The verb 'assess' and resource 'suspect product status' are clear.

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

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

The description implies usage in a chain (consumes upstream artifact) and provides a URL, but gives no explicit guidance on when to use this tool vs alternatives or when not to use it. There is no context about prerequisites or typical workflow placement.

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

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

Annotations already indicate idempotent, read-only, non-destructive behavior. The description adds valuable detail: deterministic in-browser execution, zero PII, zero egress, and artifact export with execution_hash for provenance. This exceeds annotation scope without contradiction.

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

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

Description is relatively concise, covering key aspects in a few sentences. It front-loads the purpose and includes a URL. Could be slightly tighter by removing the URL or condensing, but overall well-structured with minimal waste.

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

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

While annotations and schema cover safety and parameters, the description lacks context on what TRAIGA exposure assessment entails, the content of the AP2 artifact, error handling, or conditions for execution. The downstream reference helps but the domain context is minimal.

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

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

Schema coverage is 100% with descriptions for all four parameters. The tool description does not add any parameter-specific information beyond what's in the schema. Baseline score of 3 is appropriate as the description does not reduce understanding but also does not enhance 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 clearly states the tool as a 'TRAIGA Exposure Assessor' and explains it is a compute node that runs in-browser, deterministic, exports AP2 artifact with execution_hash for provenance. It also specifies the downstream output feeds, distinguishing it from other assess_* tools by its deterministic browser execution and specific compliance mandate.

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. It mentions feeding into a downstream pack builder but does not state prerequisites, exclusions, or compare to other assess tools. The agent would need to infer usage from the name and description.

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

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

The description adds valuable behavioral context beyond annotations: it states the tool runs deterministically in-browser, handles zero PII, and exports an AP2 artifact with execution_hash. Annotations already indicate readOnlyHint and idempotentHint, and the description does not contradict them, providing transparency about execution and output.

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 at four sentences, front-loading the core identity and then adding critical details. It is well-structured with no redundant information, though the URL and full artifact IDs could be considered slightly extraneous for a general 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?

Given the tool's complexity (a compute node with dependencies and no output schema), the description is incomplete. It does not explain what the tool actually assesses or computes, nor does it describe the output artifact format beyond execution_hash. The focus on technical plumbing over domain purpose 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?

The input schema has 100% description coverage, meaning each parameter is already described. The tool description does not add any additional semantics or usage context for the parameters, so the baseline score of 3 is appropriate per guidelines.

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 ViDA DRR Transaction Reporter within a ChainGraph compute node, but it does not explicitly state that it assesses reporting obligations, resulting in a slight mismatch with the tool name. It lacks clear differentiation from sibling assessment tools, focusing instead on technical implementation 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?

The description mentions upstream and downstream artifact IDs, hinting at its place in a pipeline, but it does not provide explicit guidance on when to use this tool versus alternatives or when not to use it. No exclusions or alternative tools are mentioned, leaving the agent to infer usage from the name alone.

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

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

The description adds valuable behavioral context beyond annotations: 'runs deterministically in-browser; zero PII, zero egress' and 'exports an AP2 artifact with execution_hash for chain provenance'. This aligns with the annotations (readOnlyHint, idempotentHint) and provides additional safety and provenance details. No contradiction.

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

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

The description is concise with multiple sentences, each providing distinct information. It front-loads the tool name and type. However, it includes a URL which is not essential for tool selection or invocation, slightly reducing conciseness. Overall, it is 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 should explain what the tool returns. It mentions 'exports an AP2 artifact with execution_hash for chain provenance', which provides some guidance, but lacks details on the artifact's structure or interpretation. It also omits prerequisites, error conditions, and how to handle missing upstream artifacts.

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

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

Schema description coverage is 100%, so the baseline is 3. The description does not add any parameter-level meaning beyond the schema. The schema itself documents the parameters adequately, so the description provides no extra value for 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 an 'Assessor' but does not clearly state the primary action. It mentions being a compute node for compliance mandate and exporting an AP2 artifact, but the core verb 'assess' is not elaborated. The purpose is implied rather than explicitly defined, making it vague compared to best practices.

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 only mentions consuming upstream artifacts from one specific tool, but no exclusions, prerequisites, or selection criteria are given. Sibling tools include many similar assess_* tools, increasing the need for usage 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable context: 'Runs deterministically in-browser; zero PII, zero egress,' confirming safety and non-destructive behavior. No contradiction with annotations; 'exports' likely refers to generating a response artifact.

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 paragraph of four sentences, efficiently conveying purpose, behavior, and downstream consumption. It is front-loaded with the title. Some minor density (IDs, URLs) could be streamlined, but no wasted 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?

Given the complexity (4 parameters, no output schema), the description covers the tool's behavior and output artifact but lacks details on return format and when to use versus similar attestation tools. The schema covers parameters, so the gap is manageable but present.

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%, with each parameter having a description. The tool description does not add additional meaning beyond the schema, fulfilling the baseline for high coverage. No extra parameter guidance is provided.

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 it's an 'MCP Server Self-Attestation Pack' and elaborates on its role as an OpenChainGraph compute node, running in-browser, producing an AP2 artifact with execution_hash. This is specific and distinguishes it from siblings like 'precheck_reserve_attestation', though it could be more direct in stating the tool's primary action (generate attestation).

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

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

No explicit guidance on when to use this tool versus alternatives. The description provides context (e.g., for infrastructure_mandate) and lists output feeds, but lacks when-not-to-use or alternative tool references. Sibling tools are many, and no differentiation 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?

Beyond annotations (read-only, idempotent, non-destructive), description adds key behavioral traits: runs deterministically in-browser, zero PII/egress, exports AP2 artifact with execution_hash, and consumes specific upstream artifacts. This enriches the agent's understanding of the tool's safety and provenance features.

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 relatively concise (4-5 sentences) and front-loaded with the tool's purpose. It efficiently communicates key constraints and behaviors. Slightly more verbose than necessary but still clear.

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

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

Given 4 parameters, no output schema, and many siblings, the description adequately covers the tool's purpose and constraints but lacks details on output structure or parameter interactions. The schema and annotations fill gaps, but some context (e.g., what the returned artifact looks like) is missing.

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 100% coverage with descriptions for all 4 parameters (compute, parent_hashes, parent_tool_ids, policy_parameters). Description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.

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

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

Title and description clearly state it is an attestation for a Settlement Orchestrator, specifying it is an OpenChainGraph compute node with deterministic in-browser execution, zero PII/egress, and exports an AP2 artifact with execution_hash for chain provenance. This distinguishes it from sibling tools like attest_mcp_server by focusing on settlement orchestration attestation.

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 implies usage context (e.g., consuming upstream artifacts from a specific lint tool), but does not explicitly state when to use this tool versus alternatives or provide when-not-to-use guidance. The mention of deterministic in-browser execution and zero PII/egress gives some context but lacks direct 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?

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds valuable behavioral traits: deterministic in-browser execution, zero PII, zero egress, and export of an AP2 artifact with execution_hash for chain provenance. These details align with and enrich the annotation hints, providing a clear safety and execution profile.

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 appropriately sized at about 5 sentences, front-loading the core purpose and then adding technical details. However, the URL at the end is not essential for an agent's decision to invoke the tool and could be considered extraneous. Overall, it is concise with minimal waste.

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 an output schema, the description should clarify what the tool returns (e.g., a conformance pass/fail, detailed report). It only mentions exporting an AP2 artifact with execution_hash, omitting the actual audit outcome or result structure. This gap leaves the agent without enough information to understand the tool's full behavior and expected output.

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

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

The input schema has 100% description coverage, with each parameter (compute, parent_hashes, parent_tool_ids, policy_parameters) adequately documented in the schema. The tool description does not add any additional meaning or context for the parameters beyond what the schema already provides, meeting the baseline expectation for high-coverage schemas.

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 title and first sentence clearly identify the tool as an 'ACP/UCP Product-Feed Conformance Auditor' with a specific verb (audits) and resource (product-feed conformance). The description further distinguishes it from sibling audit tools by detailing its role as an OpenChainGraph compute node, consuming from a specific upstream artifact and outputting to specific downstream tools, making its place in a pipeline 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 implies usage as part of an OpenChainGraph workflow by specifying upstream and downstream artifacts, but it lacks explicit guidance on when to use this tool versus alternative audit tools (e.g., audit_agent_key_rotation). No when-not-to-use conditions or comparisons to siblings are provided, leaving the agent to infer usage context.

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

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. The description adds valuable behavioral details: deterministic in-browser execution, zero PII/egress, and that it exports an AP2 artifact with execution_hash for chain provenance, which goes beyond annotations.

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

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

The description is a dense paragraph that includes a URL and a reference to a downstream artifact. While it's not overly long, it lacks front-loading of the core purpose and could be more 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?

Despite the annotations and schema, the description fails to explain what the auditor actually checks, what inputs it requires beyond the schema, and what the output artifact contains. For an auditor tool with no output schema, this is incomplete.

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

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

Schema coverage is 100% and each parameter has a clear description. The tool's description itself does not add any additional meaning about parameters, but baseline 3 is appropriate given high schema coverage.

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 title and first sentence state 'Agent Key Rotation Auditor', but the description does not explain what specific auditing checks are performed (e.g., compliance, rotation frequency). The focus is on execution properties rather than the tool's actual purpose.

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. Given numerous sibling 'audit_*' tools and other check/verify tools, explicit usage context is missing.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context: 'Renders the interactive AINumbers tool as a widget; inputs are applied via the AIN Bridge and the tool runs client-side (zero PII, zero network).' This goes beyond annotations and informs agents of execution environment and data handling.

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 (2-3 sentences) while conveying purpose, usage, and execution details. Every sentence adds value with no redundancy.

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

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

For a tool with one optional parameter, comprehensive annotations, and an existing output schema, the description covers the audit's scope, usage scenario, and execution context (client-side, zero network). It does not need to explain return values since an output schema exists.

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

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

Schema coverage is 100% with a single 'inputs' object parameter. The description adds minimal extra meaning beyond the schema, noting it is applied via AIN Bridge prefill. Given high schema coverage, baseline 3 is appropriate.

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

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

The description clearly states the tool audits MCP OAuth 2.1 authorization, specifying exactly which RFC checks it performs (RFC 9728 metadata, RFC 8707 audience binding, token-passthrough/confused-deputy risk). This clearly distinguishes it from sibling audit tools like audit_mcp_tool_scope_revocation or audit_agent_key_rotation.

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 states 'Use when a developer is securing an MCP server's authorization,' providing clear context. It does not explicitly state when not to use or mention alternatives, but the usage scenario is well-understood.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the description adds value by stating 'Runs deterministically in-browser; zero PII, zero egress' and 'Exports an AP2 artifact with execution_hash for chain provenance.' This discloses important behavioral traits about execution environment, data handling, and output format beyond what annotations provide.

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

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

The description is a single, concise paragraph that front-loads the tool's purpose. It includes a URL which may be extraneous for an AI agent but does not significantly detract. Every sentence contributes to understanding the tool's function and context, though the last sentence about the downstream validator could be integrated more efficiently.

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, the description should detail the return artifact more thoroughly. It mentions 'AP2 artifact with execution_hash' but does not specify the full structure or how the agent should use it. The nesting in policy_parameters and the compute parameter's enum behavior are partially covered by the schema, but deeper onboarding would benefit from more 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?

The input schema covers all 4 parameters with descriptions (100% coverage). The description adds no additional parameter-level detail, leaving interpretation to the schema. Baseline 3 is appropriate as the schema already does the heavy lifting, but the description does not enhance clarity around complex fields like policy_parameters' nested object.

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 this tool is an 'MCP Tool Scope & Revocation Auditor' that runs deterministically in-browser, indicating its function of auditing scope and revocation. It is specific enough to distinguish from sibling audit tools that focus on different aspects (e.g., OAuth, key rotation). However, the phrasing 'OpenChainGraph compute node (compliance_mandate)' could be clearer for an AI agent unfamiliar with the domain.

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 lacks explicit guidance on when to use this tool versus alternatives. It mentions 'Output feeds: art-151-agent-obo-mandate-validator' but does not state prerequisites, exclusions, or comparison to sibling tools. For a specialized auditor, this omission limits discoverability for the correct use case.

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 indicate read-only, idempotent, non-destructive. The description adds that it is client-side only, uses AIN Bridge, renders an interactive widget, and has zero PII and zero network, which aligns and enriches the behavioral profile.

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

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

Two efficient sentences that front-load the core action and output format. Every word earns its place; no filler 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 the tool's complexity (10 dimensions, weighting matrix), the description adequately covers inputs, processing, outputs, safety aspects (zero PII, client-side), and interactivity. The presence of an output schema further supports 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 100% with one parameter 'inputs'. The description adds value by explaining they are applied via AIN Bridge prefill and that the tool runs client-side, providing context 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 scores and compares BaaS providers across 10 specified dimensions, outputs a weighted comparison matrix and Markdown memo. This distinguishes it from sibling tools by its specific focus on BaaS provider evaluation.

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 implicitly tells when to use (when comparing BaaS providers) and provides context: browser-based, client-side, zero PII. However, it does not explicitly state when not to use or name alternatives, but the specificity is sufficient.

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 adds significant behavioral context beyond annotations: it runs deterministically in-browser, zero PII, zero egress, and exports an AP2 artifact with execution_hash. These details align with the read-only, idempotent, non-destructive annotations. It also notes consumption of upstream artifacts, providing workflow context. No contradictions with annotations.

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

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

The description is concise with three sentences, front-loading the purpose and key constraints. It includes a URL for reference. Every sentence adds value (purpose, behavioral traits, dependency). No redundant or vague phrasing. Could be slightly more structured but overall 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 4 parameters, no output schema, and high schema coverage, the description provides adequate high-level context (in-browser execution, zero PII, artifact export). However, it lacks detail on how parameters affect the binding process or the exact structure of the output artifact. The dependency is mentioned but not fully explained. The output is partially described but not 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?

The input schema has 100% coverage with parameter descriptions, so the description does not need to add much. It mentions consuming upstream artifacts from 'art-276-mutual-nda-composer', which implicitly relates to parent_hashes and parent_tool_ids, but does not explicitly link or add new semantic detail. The description adds minimal value beyond the schema, scoring baseline 3.

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 an 'Agreement Acceptance Binder' and an 'OpenChainGraph compute node (compliance_mandate)'. It specifies the action (binds agreement acceptance) and the resource (produces AP2 artifact with execution_hash). It distinguishes from siblings by naming a specific upstream artifact (art-276-mutual-nda-composer). However, the exact meaning of 'binding' could be more explicit.

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 vs alternatives. It does not mention conditions or exclusions. Sibling tools cover many agreement-related functions, but the description offers no comparison or selection hints. The only contextual clue is the upstream dependency, which is insufficient for a clear usage guideline.

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

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

Annotations already indicate readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable behavioral context: deterministic in-browser execution, zero PII, zero egress, exports AP2 artifacts with execution_hash for chain provenance, and consumes specific upstream artifacts. This goes beyond what annotations provide.

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

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

The description is concise at four sentences, front-loaded with the title and purpose. It avoids fluff and technical jargon, though it could be slightly more structured for readability.

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

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

Given the complexity (4 parameters, nested objects, no output schema), the description covers the purpose and execution environment but does not explain the output format beyond mentioning an AP2 artifact. It relies on domain knowledge for what a '226J Response Evidence Pack' is. Adequate but could be more complete, especially regarding the return value.

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

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

Schema coverage is 100% with detailed descriptions for each parameter. The tool description does not add new parameter-specific information; it only mentions the artifact and provenance. Since schema already covers the parameters, the description offers no additional semantic value.

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

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

Clearly states that this tool builds a '226J Response Evidence Pack' using OpenChainGraph compute node for compliance mandates. It specifies the deterministic in-browser execution and export of an AP2 artifact. However, it does not explicitly distinguish itself from sibling tools, though the unique domain and artifact name imply its specific use.

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 alternatives. It is implied that the tool is for building 226J evidence packs, but there are no explicit conditions for use, exclusions, or comparisons with sibling tools.

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

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

The description adds significant behavioral context beyond annotations: it runs deterministically in-browser, handles zero PII and zero egress, exports an AP2 artifact with execution_hash for chain provenance, and specifies the output destination. This complements the readOnlyHint, idempotentHint, and destructiveHint annotations well.

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

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

The description is exceptionally concise, using short sentences to convey the tool's purpose, constraints, output, and reference URL. Every sentence adds value with no redundancy or fluff.

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

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

The description is mostly complete for a tool with 4 optional parameters, no output schema, and rich annotations. It explains the output artifact and its purpose. It could provide more detail on the AP2 artifact format, but the downstream tool is referenced, so the gap is minor.

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

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

The input schema has 100% coverage with property descriptions, so the description does not need to elaborate on parameters. It neither adds nor detracts from parameter understanding, meeting the baseline for high schema coverage.

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 builds an adverse action notice, identifies it as an OpenChainGraph compute node for compliance, and distinguishes it from the sibling tool 'validate_adverse_action_notice' by specifying its output feeds that validation tool. The verb 'build' and resource 'adverse action notice' are specific.

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

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

The description provides no explicit guidance on when to use this tool versus alternatives. It does mention it is a compliance mandate and runs in-browser, but does not explain prerequisites or exclusions. No comparison to other tools 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?

Description adds behavioral context beyond annotations: deterministic in-browser execution, zero PII, zero egress, exports AP2 artifact with execution_hash. Aligns with readOnlyHint and idempotentHint annotations. No contradiction.

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

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

Description is structured with key information upfront (purpose, execution context, privacy, artifact export). Includes upstream/downstream references and URL. Slightly verbose but 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?

Covers execution context, privacy, artifact export, and chain provenance. Mentions upstream/downstream artifacts. However, with no output schema, the description does not fully explain the return value (AP2 artifact) beyond a brief mention, and policy_parameters remain a black box.

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

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

Schema coverage is 100% with detailed descriptions for all 4 parameters. Description adds no extra parameter information (only mentions compute mode in passing). Baseline 3 is appropriate.

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

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

Description clearly states it builds an 'agent-traffic acceptance policy' as an OpenChainGraph compute node. Verb 'build' and resource are specific. However, it does not explicitly differentiate from other builder tools in the sibling list, such as build_ai_conformity_pack or build_digest_manifest.

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

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

No guidance on when to use this tool versus alternatives. Description mentions it's for agent guardrail mandate and deterministic in-browser execution, but doesn't specify prerequisites, exclusions, or compare to other builders.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the description's extra details (deterministic browser execution, zero PII/egress) add some context but are not essential. No contradiction with annotations.

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

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

The description is a single dense paragraph with all key information. It could be structured with bullet points for readability, but it is not overly long and carries valuable details.

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

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

The description explains the tool's role in a chain and its inputs/outputs but does not describe the return format or expected behavior of the exported artifact. Given no output schema, more detail on return values would improve completeness.

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

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

Schema description coverage is 100%, so the schema already explains all 4 parameters. The description adds no new parameter-level details beyond what the schema provides, hence baseline 3.

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 builds AI Act conformity packs as part of a ChainGraph, specifying it runs deterministically in-browser, exports AP2 artifacts, and lists upstream and downstream connections. This distinguishes it from sibling build tools.

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

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

No explicit guidance on when to use this tool versus alternatives like build_chaingraph or build_digest_manifest. The description only lists dependencies and outputs, not selection 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral context: runs deterministically in-browser, zero PII, zero egress, exports AP2 artifact with execution_hash, and lists output chains. No contradictions with annotations.

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

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

The description is concise, front-loaded with the title and key characteristics (deterministic, zero PII, zero egress). Every sentence provides essential information without fluff.

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

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

Given the tool's complexity (4 params, no required, nested objects) and rich annotations, the description covers purpose, behavior, and output feeds. It lacks explicit detail on the return value structure beyond 'AP2 artifact', but the context of similar tools and the output schema absence is acceptable. Overall, fairly complete.

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

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

Schema coverage is 100% with parameter descriptions. The description does not add additional meaning beyond what is in the schema; it repeats the 'policy_parameters' description but does not clarify field names. Baseline 3 is appropriate as schema does the heavy lifting.

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: building an AI Decision Log Record under EU AI Act Article 12. It specifies it is a deterministic in-browser compute node that exports an AP2 artifact, distinguishing it from sibling build tools like 'build_ai_conformity_pack' or 'build_adverse_action_notice'.

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 compliance with EU AI Act and lists output feeds to other tools (e.g., validate_agent_audit_trail), but it does not explicitly state when to use this tool versus alternatives or when not to use it. There is no exclusionary guidance or mention of prerequisites.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context: runs deterministically in-browser, zero PII, zero egress, and exports an AP2 artifact with execution_hash for chain provenance. No contradictions exist.

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 relatively concise but includes internal references (e.g., art-332, URLs) that may not be useful for an agent. It front-loads the purpose but could be more streamlined.

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

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

The description omits details about the output format, the meaning of the nested policy_parameters object, and how to construct inputs. With no output schema and a complex parameter, the description is insufficient for an agent to fully understand invocation.

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

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

Schema coverage is 100%, so each parameter has a description in the schema. The tool's description does not add any further meaning to the parameters beyond what the schema already provides. A score of 3 is appropriate per guidelines.

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 'Amortization Schedule Builder' and states it is an 'OpenChainGraph compute node (compliance_mandate)', giving a clear verb and resource. However, it does not explicitly distinguish from sibling tools like compute_reg_z_appendix_j_apr, which may overlap in function.

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, nor are there any prerequisites or exclusions mentioned. The description lacks contextual clues for tool selection.

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

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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds the DAG-building and parent_hash wiring context but does not disclose significant behavioral traits beyond what annotations imply. No contradictions.

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

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

The description is a single, front-loaded paragraph of four sentences. Every sentence serves a purpose—identifying the sibling, describing output, explaining parameters, and providing usage guidance. No redundancy or waste.

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

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

The description explains what is returned (ordered executable DAG with parent_hash wiring) and outlines the agent loop. Without an output schema, it adequately covers the tool's operation, though a bit more detail on return structure could help.

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

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

Schema coverage is 100% with each parameter described, but the description adds meaningful differentiation: target_tool_id builds a chain for a specific node, tool_ids for an explicit list, and neither lists nodes. This adds value 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 it builds an executable DAG over ChainGraph tools with explicit parent_hash wiring. It distinguishes itself from the sibling 'build_workflow_links' by being 'hash-aware', fulfilling the requirement for a specific verb+resource and sibling differentiation.

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 explains when to use each parameter (target_tool_id, tool_ids, or neither to list nodes) and outlines the agent loop. While it doesn't explicitly exclude alternatives, the context is clear enough for usage decisions.

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 adds meaningful behavioral context beyond annotations: zero PII, zero egress, deterministic in-browser execution, chain provenance via execution_hash, and upstream dependency on art-306. Annotations already declare readOnlyHint, idempotentHint, and destructiveHint (all non-destructive). No contradictions.

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 four sentences with minimal redundancy. It front-loads the core purpose and then details constraints. The embedded URL adds slightly to length but is relevant for human reference. Acceptably concise, though could tighten further.

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

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

The description explains what it produces (AP2 artifact with execution_hash) and its consumption relationship, but lacks details on output schema or return values (no output schema exists). Given parameters include nested objects and chain provenance, the description covers operational context but omits result structure and agent action guidance.

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 coverage is 100% with descriptions for all 4 parameters. The description does not add extra semantics beyond listing the parameters. Per guidelines, high coverage sets baseline at 3, and no additional value is provided.

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 builds a claim dispute bundle as an OpenChainGraph compute node with compliance mandate. It specifies deterministic in-browser execution, zero PII/egress, and AP2 artifact export. This differentiates it from sibling build tools (e.g., build_chaingraph) by naming a specific upstream artifact (art-306-agent-insurability-evidence-scorer) and runtime context.

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. It does not mention prerequisites, exclusions, or decision criteria. The agent must infer usage from the name and context, which is insufficient for a tool with many 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?

Beyond annotations (readOnlyHint, idempotent), the description adds that it runs deterministically in-browser, zero PII, zero egress, and exports an execution_hash, providing valuable behavioral context.

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

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

The description is brief at two sentences plus a link, front-loading purpose and key traits; the link is somewhat extraneous but does not significantly detract.

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 tool complexity (4 parameters, nested objects, no output schema), the description fails to explain parameter usage (e.g., parent_hashes for chaining, policy_parameters) and expected outputs, leaving 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 input schema has 100% description coverage, so the description adds no additional parameter meaning beyond what schema already provides; baseline score applies.

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 builds a conversion receipt for OpenChainGraph, defines it as a compute node producing an AP2 artifact, and specifies it feeds into a verifier tool, distinguishing it from sibling builders.

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

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

The description implies use for creating a receipt to be verified later, but does not explicitly state when to use this tool versus alternatives like other builders, nor provides exclusion 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?

Beyond annotations (readOnlyHint, idempotentHint), the description adds that it runs deterministically in-browser with zero PII and zero egress, and exports an AP2 artifact. These details strengthen behavioral understanding. No contradictions with annotations.

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

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

The description is a single, dense paragraph that front-loads the key purpose. It includes essential information without redundancy. Some jargon (AP2, execution_hash) may reduce clarity, but overall it's concise.

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

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

Given the tool has 4 parameters (including nested objects) and no output schema, the description omits details about parameter usage and return values. However, annotations and schema descriptions partially compensate. The description is adequate but not fully complete 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?

All 4 parameters have descriptions in the schema (100% coverage). The description does not add extra meaning or usage hints beyond what the schema provides. Baseline of 3 is appropriate.

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

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

The description clearly states the tool builds a Digest Manifest, an OpenChainGraph compute node that exports an AP2 artifact with execution_hash for chain provenance. The verb 'builds' is implied from the title and first phrase. It distinguishes from siblings like build_chaingraph or build_conversion_receipt, though not explicitly.

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

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

No guidance on when to use this tool versus alternatives. It mentions the output feeds a specific downstream tool (art-191-conversion-receipt-builder), but no conditions, prerequisites, or exclusions. The agent is left to infer 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?

Adds behavioral details beyond annotations: entry sorting, duplicate-last-leaf, same leaf scheme as referenced spec, and worker content isolation. No contradiction with readOnlyHint=true or idempotentHint=true.

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 dense paragraph is front-loaded with main purpose and includes all key behavioral points. Could be slightly more structured but is concise and informative.

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?

No output schema, but description mentions return of manifest object + merkle_root. Covers all input parameters, preprocessing requirements, and hash logic, making it complete 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 coverage is 100%, but description adds meaning by explaining parameter roles (caller hashes files, entries include content_type) and hashing behavior (sorted by path, duplicate-last-leaf).

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 builds a Merkle-rooted disclosure manifest from caller-supplied digests, distinct from sibling 'build_digest_manifest' by specifying data-room context and Merkle rooting.

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 caller's preprocessing responsibility (hashing files) and notes that worker never sees contents. Mentions client-side signing as a separate step, providing clear usage context, though lacks explicit 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?

Annotations already provide readOnlyHint=true and idempotentHint=true. The description adds behavioral details: deterministic in-browser execution, zero PII/egress, and artifact export with execution_hash. This provides context beyond annotations, though it does not describe the full output structure.

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 key information front-loaded (purpose, deterministic, no PII/egress). The included URL provides additional reference but does not bloat the description unnecessarily.

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

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

Given the tool's complexity (builder with chain provenance), no output schema, and well-covered parameters, the description provides sufficient context: deterministic behavior, zero PII/egress, upstream artifact consumption, and artifact export. Missing output structure details are mitigated by annotations and schema.

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

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

Schema coverage is 100%, so parameters are fully described in the schema. The description adds no new semantic information about parameters beyond the schema. Baseline score of 3 is appropriate.

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

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

The description clearly states the tool is a builder for e-invoice transmission receipts, an OpenChainGraph compute node that runs deterministically in-browser with zero PII and zero egress. It specifies the output artifact type and execution_hash for provenance. This distinguishes it from sibling builders like build_chaingraph.

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 used after consuming upstream artifacts from a specific router, but it doesn't explicitly state when to use this tool versus alternatives (e.g., route_einvoice_jurisdiction_mandate). No exclusions or when-not-to-use 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?

Annotations already indicate read-only and idempotent. The description adds valuable context: runs deterministically in-browser, zero PII egress, exports AP2 artifact with execution_hash. No contradictions.

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 paragraph that efficiently front-loads the purpose and adds technical details. Every sentence is informative, though slight restructuring could improve readability.

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

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

For a tool with 4 parameters (one nested object) and no output schema, the description covers purpose, execution environment, security, artifact type, and dependencies. It lacks detail on expected values for policy_parameters, but overall is fairly complete.

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

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

Input schema covers all 4 parameters with descriptions (100% coverage). The tool description does not add any additional parameter meaning beyond the schema, so baseline score of 3 is appropriate.

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

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

The title and description explicitly state 'FRIA & Post-Market Monitoring Plan Builder'. It specifies the verb 'build' and the resource, and distinguishes from siblings by naming the specific compliance mandate and upstream/downstream artifact IDs.

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 creating FRIA monitoring plans but does not provide explicit when-to-use or when-not-to-use guidance. It mentions zero PII and zero egress, which hints at safety, but no alternatives or exclusions are 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?

Annotations already declare readOnlyHint and idempotentHint, so the description adds context about client-side execution, zero PII, and zero network. However, it does not disclose potential side effects or authorization needs beyond what annotations provide.

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

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

The description is two sentences, front-loading the purpose and adding technical constraints efficiently. Every sentence adds value without unnecessary elaboration.

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 an output schema and annotations cover safety, the description is mostly complete. However, it could briefly mention what the output represents (e.g., the mandate document or validation result) for full clarity.

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 sole parameter 'inputs' is described in the schema with clear meaning (map of IDs to values). The description adds 'AIN Bridge prefill' context but does not significantly deepen understanding beyond the schema, which already has 100% coverage.

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 that the tool builds or validates a Google AP2 Checkout/Payment Mandate VDC and distinguishes it from the AINumbers Policy Mandate. However, it does not differentiate from the sibling tool 'ap2_aml_mandate_builder', which may cause confusion.

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 only says it targets the external AP2 spec, not the AINumbers Policy Mandate, implying a specific use case but offering no explicit guidance on when to use this tool versus alternatives or when not to use it.

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

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

Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds crucial behavioral details: deterministic execution, in-browser only, zero PII, zero egress, and exports an artifact with execution_hash. This goes beyond annotations and helps the agent understand safety and constraints.

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

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

The description is a single paragraph that front-loads the core purpose and key traits. It includes relevant chaining context but is not unnecessarily verbose. Minor redundancy exists with artifact lists, but overall it is well-structured and concise for the tool's complexity.

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 nested objects, 4 parameters, and no output schema, the description provides sufficient context: it explains the tool's role, environment, constraints, inputs (upstream artifacts), and outputs (AP2 artifact with execution_hash). While some details about the token scope itself are absent, the description is fairly complete for an experienced 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?

The input schema has 100% description coverage for all four parameters. The description does not add additional semantics beyond what the schema already provides. Baseline score of 3 is appropriate given high schema coverage.

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 'Mastercard Agentic Token Scope Builder' and an 'OpenChainGraph compute node (compliance_control)'. It distinguishes itself from sibling tools by specifying its deterministic in-browser execution, zero PII, and chaining provenance. The unique purpose is well-defined.

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 lists upstream and downstream artifacts, providing context for when this tool is used in a pipeline. However, it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusion criteria or when-not scenarios. Usage guidance is implied but not explicit.

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 adds behavioral details beyond annotations (deterministic, in-browser, zero PII/egress, execution_hash). However, it contradicts the readOnlyHint annotation by claiming it 'exports' an artifact, implying a side effect. This inconsistency 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 a single paragraph of around 100 words, efficiently presenting key information (purpose, behavior, chain context, URL). It is front-loaded with the title and core function, and each sentence adds value. Minor improvement could be structure breaks.

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 complexity (4 parameters, nested objects, no output schema), the description provides chain provenance and behavior context but lacks detail on what 'No-Russia Clause Pack' specifically contains and the policy_parameters structure. Output artifact fields are partially mentioned.

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%, with each parameter already documented. The tool description adds no additional meaning about the parameters, so baseline 3 is appropriate.

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

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

The description clearly states the purpose: it builds a No-Russia Clause Pack as a compute node, exports an AP2 artifact, and runs in-browser. It distinguishes from sibling tools by specifying upstream/downstream artifact IDs and a URL, but does not explicitly contrast with other build_* tools.

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

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

The description implies usage context by mentioning upstream (art-95) and downstream (cry-04) artifacts, suggesting it fits in a chain. However, it lacks explicit instructions on when to use this tool vs alternatives or when not to use it.

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?

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds deterministic in-browser execution, zero PII/egress, and output as AP2 artifact with execution_hash. This provides valuable behavioral context without contradiction.

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

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

The description is very concise at ~80 words across 4 sentences. Every sentence adds value, starting with the core purpose and front-loading key behavioral traits.

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

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

Given the tool's complexity (4 params, nested objects, no output schema), the description covers purpose, behavior, and output format well. However, it could elaborate on how the PLD Disclosure Pack is used or linked to other chaingraph artifacts.

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

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

Schema coverage is 100% with descriptions for all 4 parameters. The tool description adds no additional parameter meaning beyond what the schema already provides, resulting in baseline 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 the tool builds a PLD Disclosure Pack as an OpenChainGraph compute node for compliance mandates. It specifies deterministic in-browser execution, zero PII/egress, and exports an AP2 artifact, distinguishing it from sibling builders.

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 compliance-related PLD pack building but lacks explicit when-to-use guidance or comparisons with sibling tools like build_226j_response_evidence_pack or build_ai_conformity_pack.

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