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, so the description adds value by explaining that it is browser-based, client-side only, and involves simulation with zero network calls, reinforcing the non-destructive, read-only nature.

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

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

Two sentences effectively front-load the main purpose and then provide technical context. Every phrase is informative, though the second sentence is dense with details like 'AIN Bridge' and 'AINumbers tool' that might require familiarity.

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 output schema, the description adequately covers inputs, processing, output (Policy Mandate), and security characteristics (zero PII, zero network). It doesn't explain error handling or edge cases, but overall is sufficient for a sandbox tool.

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

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

The single parameter 'inputs' is an object with 100% schema coverage, and the description adds semantic meaning by enumerating what can be set (spend caps, MCC allowlists, etc.), which goes beyond the schema definition.

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, listing specific configurable elements (spend caps, MCC allowlists, etc.) and distinguishing it from sibling tools like ap2_aml_mandate_builder by emphasizing simulation and client-side execution.

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 like build_google_ap2_mandate or lint_mcp_tool_definition. It mentions browser-based and zero PII but lacks comparative 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 provide readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral details: deterministic browser execution, zero PII/egress, and export of AP2 artifact with execution_hash for chain provenance. These go beyond the annotations and provide important context for safe usage.

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 two sentences. The first sentence front-loads the tool's purpose and key traits. The second sentence provides chain context and a URL. While efficient, the URL and artifact IDs could be seen as cluttered, but overall it is well-structured and not overly verbose.

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

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

Given the tool has 4 parameters, nested objects, no output schema, and 78 sibling tools, the description provides basic context (deterministic, chain provenance, upstream/downstream). However, it lacks detail on the aggregation logic, the return artifact structure (beyond 'AP2 artifact with execution_hash'), and how policy_parameters are used. The description is adequate but not 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 baseline is 3. The description does not add significant parameter information beyond what the schema already provides. It mentions 'Input parameters for this tool's decision function' but does not elaborate on specific parameters like 'compute' modes or the structure of policy_parameters.

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

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

The description clearly states it aggregates CBAM precursor emissions as a compliance mandate. It specifies the tool's role as an OpenChainGraph compute node. However, it does not explicitly distinguish itself from sibling aggregate tools like aggregate_execution_receipts, though the upstream/downstream artifact references provide some 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 mentions upstream and downstream artifacts ('Consumes from art-68...', 'Output feeds: art-69...') which implies a sequential workflow, but does not explicitly state when to use this tool versus alternatives or provide any when-not conditions. There is no guidance on prerequisites or 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?

Annotations already declare readOnlyHint, idempotentHint, etc. The description adds that execution is deterministic, in-browser, with zero PII/egress, and mentions cryptographic mandate. However, it states 'Exports an AP2 artifact,' which might imply mutation, but annotations indicate read-only; this ambiguity slightly reduces clarity.

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 tool's purpose and efficiently provides context on environment, inputs, outputs, and link. It is concise 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?

The description covers the tool's role in the chain and lists dependencies, but lacks explicit description of the output artifact's structure or content, especially since there is no output schema. For a tool with nested parameters and no output schema, additional 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?

The input schema has 100% coverage with descriptions for all 4 parameters, including nested objects and enums. The description does not add parameter-level meaning beyond the schema, 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 is an 'Agent-Action Audit-Trail Aggregator' for OpenChainGraph, specifying it aggregates execution receipts deterministically in-browser with zero PII/egress. It lists upstream and downstream artifacts, distinguishing it from sibling tools that perform different aggregation or validation functions.

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 by listing specific upstream artifacts this tool consumes and downstream tools it feeds, implying it is part of a pipeline. However, it lacks explicit guidance on when to use this tool vs. alternatives (e.g., other aggregators) 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 indicate read-only, idempotent, non-destructive behavior. The description adds context: runs deterministically in-browser, zero PII/egress, exports with execution_hash for provenance, and lists specific artifact dependencies.

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

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

The description is a single, well-structured paragraph that front-loads the purpose and then lists key characteristics. It is concise without being overly brief.

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 a nested object) and no output schema, the description covers execution mode and artifact flow but lacks explanation of the Ownership 50%-Rule itself or output format. Adequate but not comprehensive.

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. The tool description adds minimal parameter-specific context beyond mentioning upstream artifacts. 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 it is an Ownership 50%-Rule Aggregator, an OpenChainGraph compute node for compliance mandates. It mentions specific upstream and downstream artifacts, distinguishing it from sibling tools.

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

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

The description implies usage as part of a compliance pipeline by referencing upstream and downstream artifacts, but does not explicitly explain when to use this tool versus alternatives or provide when-not 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?

The description goes beyond annotations by detailing deterministic in-browser execution, zero PII, zero egress, and export of AP2 artifacts with execution_hash. Annotations already indicate safe read-only/idempotent behavior; the description adds valuable context about compute modes and chain provenance.

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 conveys the tool's role, behavior, and dependencies. It could arguably drop the URL, but the information is relevant. No redundancy or fluff; each sentence adds context.

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 reasonable context: compute modes, chaining via parent_hashes, and dependencies. However, it could be more complete by explaining what the aggregation entails (e.g., which fields from the upstream artifact are used) and what the output artifact contains beyond an execution hash.

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 parameters have descriptions in the input schema (100% coverage), so the description does not need to add much. However, the description only mentions upstream artifact IDs, not the parameters themselves. It adds minimal semantic value beyond the schema, but the schema coverage justifies a 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 aggregates Taxonomy KPI and Green Asset Ratio, specifying it's an OpenChainGraph compute node. The name and title reinforce this. However, it does not explicitly differentiate from sibling aggregate tools (e.g., aggregate_cbam_precursor_emissions), leaving some ambiguity about when to use this specific aggregator.

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 upstream and downstream artifact IDs (art-73 and cry-05) but does not offer explicit guidance on when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or conditions that would help an AI agent choose this tool over similar 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds significant context: 'Runs deterministically in-browser; zero PII, zero egress' and 'Exports an AP2 artifact with execution_hash for chain provenance'. This goes beyond annotations by explaining execution environment and data handling, with 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 moderately concise, consisting of five sentences that convey the tool's identity, execution characteristics, privacy features, output format, and related artifacts. It is front-loaded with the title and key attributes. Each sentence adds value, though the URL could be seen as optional. Overall well-structured without being verbose.

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

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

Given no output schema, the description mentions exporting an 'AP2 artifact with execution_hash' and identifies downstream consumers ('art-122-timestamp-attestation-verifier'). It also notes determinism and zero PII/egress. With annotations covering safety and idempotence, this provides sufficient context for using the tool in a pipeline. Some details about the artifact structure are missing but not critical.

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 elaborate on parameters beyond what is in the schema, but it provides overall context about the tool being a compute node and exporting artifacts. This adds some background but not parameter-specific detail.

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 'Document Integrity & eIDAS Electronic Timestamp Anchor' and an 'OpenChainGraph compute node (compliance_mandate)'. It specifies that it runs deterministically in-browser, exports an AP2 artifact with execution_hash for chain provenance. The purpose is clear, though it does not explicitly distinguish from sibling tools like verify_timestamp_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?

The description implies usage in compliance scenarios via 'compliance_mandate' and indicates the output feeds into 'art-122-timestamp-attestation-verifier'. However, it lacks explicit guidance on when to use this tool versus alternatives or when not to use it. No prerequisites or exclusions are stated.

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, indicating a safe read operation. The description adds key behavioral context: 'Browser-based, client-side only. Zero PII. Zero network.' This confirms no data leaves the browser and no server calls are made, which is valuable beyond the annotations. 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 multiple sentences with some redundancy (e.g., 'zero PII' mentioned twice). While it covers purpose, technical details, and a link, the first sentence 'Anchor agentic tool for Cat-12' is vague and not front-loaded. Overall, it is adequate but not tightly structured; every sentence contributes, but rephrasing could improve 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 simplicity (one parameter, no output schema) and strong annotations, the description provides sufficient context: it explains the translation process, client-side execution, and a link for interactive use. Lacking output schema, it still hints at the output being a structured JSON. The description is complete for an agent to understand what the tool does and how it behaves, though details on output format could strengthen 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?

Schema coverage is 100% with a description for the 'inputs' parameter stating it is a map of element IDs to values. The description adds that inputs are 'applied via the AIN Bridge prefill', providing minimal extra context. Since the schema already explains the parameter well, the description adds limited value, justifying a 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: translating AML/BSA program controls, TM rules, and customer risk policy into a structured Policy Mandate JSON. The verb 'translate' and resource 'controls into JSON' are specific. However, it does not explicitly differentiate from siblings like 'build_google_ap2_mandate', though the mention of 'AP2 AML' provides some distinction. A score of 4 reflects clear purpose without 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 does not provide explicit guidance on when to use this tool versus alternatives. It calls the tool an 'anchor agentic tool for Cat-12' which vaguely implies primary usage but lacks direct comparison with siblings like 'agentic_mandate_sandbox' or 'build_google_ap2_mandate'. No when-not-to-use or prerequisites are stated.

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, non-destructive, and idempotent behavior. The description adds substantial value: it confirms deterministic in-browser execution, zero PII, zero egress, and explains the output artifact and provenance hash. This goes beyond the annotations and provides rich behavioral insight.

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 contributing essential information. It is front-loaded with the title and purpose, and covers execution model, output, inputs, and a reference link. It is concise without being overly terse, though it could benefit from slightly more structured formatting.

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 parameters are fully described in the schema and no output schema exists, the description provides a good high-level understanding. It explains what the tool does, its execution environment, its dependencies, and its place in the data pipeline. It lacks details on the artifact format but still offers sufficient context for an agent to decide.

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 does not add parameter-level details beyond what is in the schema, though it hints that parent_hashes should come from the named upstream artifacts. Overall, the description does not significantly enhance parameter understanding over 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 applies NGFS/Fit-for-55 climate scenarios, and specifies it is an OpenChainGraph compute node. It distinguishes itself from siblings by naming specific upstream and downstream artifacts and its deterministic in-browser execution.

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 this tool by detailing its dependencies (upstream artifacts) and downstream consumers, but does not explicitly state when not to use it or mention alternatives. The guidance is clear enough for an agent to infer usage in the climate scenario application pipeline.

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 valuable behavioral context: deterministic in-browser execution, zero PII or egress, and artifact export with execution_hash. This helps the agent understand safety 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 concise at three sentences, front-loading the purpose and adding behavioral traits and an upstream dependency. It avoids fluff but could be better structured, e.g., separating behavioral notes from input 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 what the tool does and its behavioral context, but lacks information about the output format (AP2 artifact structure) and the meaning of 'readiness diagnostic'. Given no output schema, this is a gap. It does address input dependency well.

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

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

With 100% schema description coverage, the baseline is 3. The description does not add parameter-specific meaning beyond what the schema provides, though it mentions the upstream artifact consumption which relates to the parent_hashes parameter indirectly.

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 a diagnostic for agent directory publish readiness, including its role as an OpenChainGraph compute node. It provides specific details like consuming upstream artifacts and exporting an AP2 artifact, but does not explicitly differentiate from sibling tools like run_agentic_readiness_diagnostic.

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, nor does it mention prerequisites or scenarios to avoid. This leaves the agent without context for tool selection among many similar assess_* and run_* 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 declare readOnlyHint=true and idempotentHint=true. Description adds value by stating deterministic in-browser execution, zero PII/egress, and artifact export. No contradiction; aligns with non-destructive nature.

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

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

Four sentences, front-loaded with purpose. Includes URL and output feeds which add context but are not essential. Efficient overall, no 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?

Complex tool with nested objects and no output schema. Description mentions output feeds and artifact but does not explain what the conformity assessment returns (e.g., pass/fail, risk score). Incomplete for a tool that produces a result.

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% description coverage, so baseline is 3. Description provides context about compute node and artifact export but does not add specific parameter details beyond schema, especially for 'policy_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?

Description explicitly states the tool assesses AI Act conformity for credit-scoring, with specific regulatory deadline and Annex reference. Verb 'assess' and resource 'Credit-Scoring Conformity Pack' clearly define purpose, distinguishing it from siblings like 'build_ai_conformity_pack' or 'check_ai_act_art50_marking'.

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?

Context implies usage for credit-scoring conformity assessment, but no explicit guidance on when to use versus alternatives like 'build_ai_conformity_pack' or 'classify_ai_system_governance'. No 'when-not-to-use' or prerequisite conditions mentioned.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable behavioral details: deterministic execution in-browser, zero PII, zero egress, and export of AP2 artifact with execution_hash for provenance. 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 concise, front-loading key information (title, type, determinism, privacy, artifact export, dependencies, URL). 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 (4 params, no output schema, chain context), the description provides a good overall picture: deterministic behavior, privacy, what it consumes and produces, and its place in the graph. Minor gap: the exact meaning of 'circumvention diligence' is assumed but not elaborated.

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 fully documents parameters. The description adds minimal context about compute mode and policy_parameters, but does not significantly enhance 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 title and description clearly identify the tool as an OpenChainGraph compute node for circumvention diligence. It specifies the deterministic, in-browser execution and the artifact export. However, it does not explicitly differentiate itself from the many sibling tools beyond the unique 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 lists upstream and downstream dependencies, providing context for when the tool fits in a pipeline. However, it lacks explicit guidance on when to use this tool instead of alternatives or 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?

Beyond the annotations (readOnly, idempotent, non-destructive), the description adds key behavioral traits: it runs deterministically in-browser, processes zero PII, has zero egress, and exports an AP2 artifact with an execution hash. This provides valuable context that annotations alone do not cover.

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, consisting of two sentences and a URL. Every sentence adds unique value: first sentence names the tool and its nature, second covers key behaviors. No redundant or filler content, earning maximum efficiency.

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

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

Given no output schema, the description hints at the output (AP2 artifact with execution_hash) but does not explain what 'readiness' assessment returns or how to interpret results. The tool has a nested 'policy_parameters' object not detailed in description. Adequate but could be more complete.

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

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

The input schema has 100% description coverage for all 4 properties, so baseline is 3. The description does not add new parameter-level details but contextualizes 'parent_hashes' and 'parent_tool_ids' by noting upstream artifacts from a specific tool. No additional syntax or format guidance 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 assessing CRA Vulnerability Reporting Readiness under Article 14 and specifies it is an OpenChainGraph compute node. However, it does not explicitly differentiate it from sibling tools like 'check_cra_annex1_completeness' or other assessment tools, but the specific CRA context narrows its purpose sufficiently.

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 upstream artifacts from 'art-139-cra-annex1-completeness-checker', implying a prerequisite but does not state when to use this tool versus alternatives. No explicit guidance on exclusions or scenarios where another tool would be more appropriate is provided.

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

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

The description adds valuable behavioral context beyond the annotations: it runs in-browser, is deterministic, handles no PII and no egress, exports an AP2 artifact with execution_hash for provenance, and feeds into a specific downstream validator. Annotations already indicate read-only, idempotent, non-destructive; the description confirms safety and determinism.

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 plus a URL, front-loading the purpose and key characteristics. Every sentence adds value: purpose, runtime environment, safety, output, provenance, downstream integration. No unnecessary words.

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

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

For a tool assessing ISO 42001 conformance, the description lacks details about the output (e.g., what the conformance result looks like) and the policy_parameters object is not explained. However, it mentions the output artifact and a downstream validator. With no output schema, the description could be more complete about return values.

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 4 parameters, so the schema already documents them. The description does not add specific parameter semantics beyond mentioning 'execution_hash' which relates to parent_hashes. Given schema coverage is high, the 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 tool name and title clearly indicate it assesses ISO 42001 AIMS clause conformance. The description explains it's an OpenChainGraph compute node that produces an AP2 artifact. It distinguishes itself from sibling 'assess_ai_act_conformity' by targeting a specific standard. However, the description does not explicitly state the verb 'assesses' or 'evaluates', relying on the title.

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 it 'runs deterministically in-browser; zero PII, zero egress', implying safe usage for sensitive data. It also mentions the output feeds into another validator, suggesting a workflow. However, there is no explicit guidance on when to use this tool versus similar assessment tools, nor exclusions 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 already declare readOnly, idempotent, and non-destructive. The description adds value by specifying deterministic in-browser execution, zero PII, zero egress, and artifact export with execution_hash. No contradictions. It could mention error handling or output specifics, but the additions are sufficient.

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

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

The description is a single paragraph. It is front-loaded with the technical nature but includes a URL and specific artifact IDs. Could be more concise and structured. While not overly long, it lacks clear separation of purpose, behavior, and usage.

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, so the description should explain what the assessment result is. It mentions an AP2 artifact with execution_hash, but not what the artifact contains (e.g., a readiness score, report). The consumption/production chain is described, but the functional outcome 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%, with each parameter having a clear description. The description adds minimal value beyond the schema; it ties parameters to upstream/downstream artifacts but doesn't deepen 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 and title indicate it assesses MAR-Crypto Surveillance-Readiness, but the description focuses on technical execution (compute node, browser, artifact export) rather than explicitly stating what the assessment evaluates. The functional purpose is vague; it doesn't clarify what 'readiness' means or what criteria are used.

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 its many siblings (e.g., assess_mica_casp_readiness, assess_psd3_readiness). The mention of upstream/downstream artifacts implies a pipeline but does not help an agent decide when to invoke this specific assessment.

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 states deterministic in-browser execution, zero PII/egress, and the export of an AP2 artifact with execution_hash for provenance. This confirms the readOnlyHint, idempotentHint, and destructiveHint from annotations and enriches understanding of side effects and data flow.

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: one sentence that front-loads the tool name and purpose, then provides key behavioral details (deterministic, browser, zero data), artifact specification, and dependencies. No wasted words; every sentence earns its place.

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

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

While the description covers purpose, behavior, and artifact flow, it lacks details about the assessment output beyond being an exported artifact. With no output schema, the description could specify what the AP2 artifact contains (e.g., readiness score, status). The completeness is adequate for a simple tool but leaves uncertainty about the result 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 input schema already has 100% coverage with detailed descriptions for all four parameters. The tool description does not add additional parameter-level information beyond what is in the schema. With full schema coverage, a baseline of 3 is appropriate, as no extra 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 identifies the tool as a CASP Authorization-Readiness Assessor under MiCA, specifying it's an OpenChainGraph compute node for compliance mandates. It distinguishes itself from sibling assessment tools by naming its specific regulatory focus (MiCA CASP) and listing its unique upstream and downstream artifacts.

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 within a ChainGraph pipeline but does not explicitly state when to use this tool versus alternative assessment tools like assess_psd3_readiness or assess_ai_act_conformity. Given the large number of sibling assessment tools, explicit guidance on selection would improve clarity.

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, and destructiveHint=false. The description adds valuable context: runs deterministically in-browser, zero PII, zero egress, exports an AP2 artifact with execution_hash, and lists output feeds. This enhances transparency without contradicting 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 front-loaded with the purpose and type, then provides key details (deadline, execution, output) in a single paragraph. It is slightly lengthy but each sentence adds relevant information. Could be more concise by omitting the URL, but still effective.

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 a nested object) and no output schema, the description explains the output as an AP2 artifact with execution_hash and lists downstream feeds. However, it does not describe the readiness assessment format or what constitutes the result. Partially compensates for missing output schema but leaves some ambiguity.

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 parameters. The tool description does not add additional meaning or examples for parameters like `compute`, `parent_hashes`, or `policy_parameters`. Baseline score of 3 is appropriate as the schema provides sufficient 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 identifies the tool as a PSD3/PSR Readiness Checker, states it is an OpenChainGraph compute node for compliance mandate, and provides regulatory deadlines. The purpose is specific and distinguishable from sibling tools by name and regulatory focus, but 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 provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, context of use, or when not to use it. With many similar sibling tools, the lack of usage guidelines is a significant gap.

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

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

The description adds significant behavioral context beyond annotations: it runs deterministically in-browser, zero PII and egress, exports an AP2 artifact with execution hash for chain provenance. This complements the idempotentHint and readOnlyHint annotations without contradiction. The open URL provides further 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 (four sentences) and front-loaded with the tool's identity. Every sentence adds value: stating the regulatory purpose, execution environment, data safety, output format, upstream dependency, and a reference URL. No redundant or irrelevant content.

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

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

Given the tool's complexity (4 parameters, nested objects, no output schema), the description covers the essential behavioral aspects: execution, data handling, output artifact, upstream dependency. The annotations further complete the safety profile. However, it omits guidance on parameter usage (e.g., what policy_parameters expects) and does not describe the return format, leaving some 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 for all four parameters, so the baseline is 3. The tool description adds context about consuming upstream artifacts (linking to parent_hashes/parent_tool_ids) but does not explain 'policy_parameters' beyond what the schema provides. No additional semantic value is added.

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

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

The description clearly identifies the tool as a 'DSCSA Suspect/Illegitimate Product Quarantine Assessor' and specifies it is an OpenChainGraph compute node. It distinguishes itself from general assess tools by focusing on a specific regulatory domain (DSCSA) and mentions it consumes upstream artifacts, but it could be more directly functional in stating the decision-making 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?

The description provides no explicit guidance on when to use this tool versus alternatives. It mentions it consumes artifacts from 'art-113-saleable-returns-verifier', implying a sequence, but does not state prerequisites, when it is appropriate, or when not to use it. Sibling tools like 'assess_ai_act_conformity' 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?

The description adds valuable context beyond annotations: 'Runs deterministically in-browser; zero PII, zero egress' confirms read-only and idempotent nature. It also notes 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 concise (4-5 sentences) and each sentence adds information. It front-loads the title and nature but uses technical jargon. Could be restructured for clarity, but no unnecessary content.

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

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

Covers technical details (deterministic, zero PII, artifact export) and pipeline context (upstream/downstream artifacts). However, lacks business context for what the 'assessment' entails and does not explain output since no output schema exists. Missing domain explanation.

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 any parameter-specific information or clarify the technical schema descriptions (e.g., compute modes, parent_hashes). No enhanced semantics 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 identifies the tool as a 'ViDA DRR Transaction Reporter' and 'OpenChainGraph compute node (compliance_mandate)', stating it exports an AP2 artifact for chain provenance. However, it does not explicitly state the high-level function of assessing a reporting obligation, and uses domain-specific jargon that may be unclear to an agent.

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. With many sibling tools including assess_vida_recapitulative_migration, the description lacks any usage context or differentiation, leaving the agent without criteria 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 indicate read-only and idempotent behavior. The description adds valuable context: determinstic in-browser execution, zero PII/egress, and artifact export with execution_hash. There is 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 concise at four sentences, with the tool name and purpose front-loaded. It could be better structured but is efficient and includes a URL for further context.

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 clarify the artifact's content or the assessment result. It explains the compute context and upstream consumption but omits output details. Adequate for a read-only, idempotent tool but not 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?

The input schema has 100% description coverage, so the baseline is 3. The description adds minimal value beyond the schema, only noting the upstream artifact for parent_hashes. Policy_parameters are explained in the schema but not elaborated 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 identifies the tool as a 'ViDA Recapitulative Statement Migration Assessor' and states it exports an AP2 artifact for chain provenance. It distinguishes from siblings like 'assess_vida_drr_reporting_obligation' by specifying 'migration' rather than 'reporting obligation'. However, it does not fully clarify what the assessment entails.

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 mentions deterministic in-browser execution and upstream artifact consumption, but lacks context for selection among many sibling assess 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 readOnlyHint and idempotentHint. The description adds valuable behavioral details: deterministic execution in-browser, zero PII, zero egress. This goes beyond the annotations alone and provides important context for side effects 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 concise and front-loaded with the tool's purpose. It fits in a single paragraph but packs essential information. Minor improvement could be structural separation, but it is still 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 there is no output schema, the description partially compensates by stating the tool exports an AP2 artifact with execution_hash and mentions output feeds. It covers the main functional behavior, though details on return fields are absent. Overall adequate for an AI agent to understand the tool's role.

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%, so the schema already documents all parameters. The description adds context about the overall process (execution hash, output feeds) but does not enhance parameter meanings beyond what is in 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 creates a self-attestation pack for MCP servers, specifying it as an OpenChainGraph compute node that runs in-browser and exports an AP2 artifact for chain provenance. This distinguishes it from the many sibling tools that focus on validation, assessment, or regulatory compliance.

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

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

The description does not provide explicit guidance on when to use this tool versus alternatives like validate_mcp_server_identity or check_mcp_registry_entry. It lacks any 'when to use' or 'when not to use' instructions, leaving the AI agent without decision criteria.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable behavioral traits: deterministic in-browser execution, zero PII, zero egress, and export of an artifact with execution_hash for chain provenance. This enriches the agent's understanding 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 the tool's identity and purpose. It uses structured elements (em dash, line breaks) to separate context, but the technical jargon slightly reduces clarity. Every sentence adds value, though the overall density could be improved.

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 good chain context (upstream/downstream artifacts, browser execution) but lacks details on what the conformance audit specifically checks, how parameters like policy_parameters influence the result, and what the output artifact contains. Given the absence of an output schema, more descriptive context would be beneficial.

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 provide additional meaning for any parameter; it relies entirely on the schema's own descriptions.

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 this tool as a conformance auditor for ACP/UCP product feeds. It distinguishes itself from sibling audit tools by specifying its role in an OpenChainGraph compute node with upstream/downstream artifact links.

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 (e.g., other audit tools). No exclusions, prerequisites, or context for selection are mentioned.

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

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

Annotations already declare read-only and idempotent behavior. The description adds value by specifying deterministic execution, browser-based operation, zero PII/egress, and artifact output with execution_hash. However, it does not disclose what auditing steps occur or how the computation relates to parameters.

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 moderately concise but includes extraneous details like the URL and references to downstream artifacts. It could be restructured to prioritize the tool's core function over implementation specifics.

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 with nested objects, no output schema), the description lacks critical context about outputs and how to interpret results. It mentions an artifact but does not explain its structure or how to use it, leaving the agent underinformed.

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

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

The input schema provides full descriptions for all 4 parameters (100% coverage). The tool description adds no additional meaning to the parameters, so the baseline score of 3 is appropriate given the schema already 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 name and title suggest auditing key rotation, but the description does not explicitly state the primary function. It focuses on technical details (compute node, in-browser, artifact export) rather than clarifying what the tool does for the user, leaving the core purpose vague.

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 sibling audit tools or alternatives. There is no mention of prerequisites, context, or conditions for invocation, making it difficult for an agent to determine appropriate usage.

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

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

Annotations already indicate readOnly, idempotent, and non-destructive. The description adds crucial behavioral traits: renders an interactive widget, inputs via AIN Bridge, runs client-side with zero PII and zero network. This goes well beyond annotations and fully informs the agent.

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

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

The description is three sentences, each adding unique value: purpose+checks, usage context, and behavioral details. No filler or redundancy; information is front-loaded with the main purpose.

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

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

Given the lack of an output schema, the description could explicitly mention the output (e.g., audit report or widget display). However, it implies the output is the widget itself and describes inputs and behavior well, so it is mostly 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% for the single 'inputs' parameter, so baseline is 3. The description adds value by explaining that inputs are applied via AIN Bridge prefill and that the tool renders a widget, giving context on how the parameter is used.

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 and specifies exact RFC checks (9728, 8707) and risk assessments. It distinguishes from sibling tools by focusing on OAuth rather than general sandbox, mandate, or validation tasks.

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

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

The description explicitly says 'Use when a developer is securing an MCP server's authorization,' providing clear usage context. While it does not mention alternatives or when not to use, the context is sufficient for an agent to decide.

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 value beyond annotations by stating 'zero PII, zero egress' and 'deterministically in-browser', which align with readOnlyHint and idempotentHint. The mention of server-side compute options in the schema introduces a minor inconsistency, but overall the description usefully supplements behavioral traits.

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

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

The description is four sentences with technical jargon, lacking a clear structure. It front-loads the title-like phrase but then jumps to implementation details. While not overly long, it could be more concise and better 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?

No output schema is provided, and the description does not describe the return format comprehensively. It mentions exporting an AP2 artifact with execution_hash, but details like structure, fields, and error handling are missing. Given the complexity and sibling count, more context on input/output 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?

Schema coverage is 100%, so parameters are well-documented in the schema. The description does not add meaningful semantics about parameters; it only mentions 'execution_hash' for chain provenance, which relates indirectly to parent_hashes. 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 suggests auditing scope and revocation, but the description focuses on execution environment and output format rather than stating a clear verb+resource action. Phrases like 'runs deterministically in-browser' and 'exports an AP2 artifact' imply the tool performs some audit function, but the core purpose is vague.

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 over alternatives like 'audit_mcp_oauth' or 'audit_agent_key_rotation'. The description mentions an output feed to 'art-151-agent-obo-mandate-validator' but does not clarify the use case or 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 provide readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral context: 'Browser-based, client-side only, zero PII', 'inputs are applied via the AIN Bridge and the tool runs client-side (zero PII, zero network)'. This goes beyond annotations by explaining execution environment and data handling, though it does not detail all edge cases.

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

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

The description is two sentences. The first sentence is concise and informative. The second sentence repeats 'zero PII' and describes the widget rendering, which could be more concise or merged. It is not overly long but has some 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 has one nested parameter and no output schema, the description covers inputs (weight matrix applied via AIN Bridge), outputs (comparison matrix and memo), and behavioral traits (client-side, no PII). It provides a good overview for an interactive widget, though details on output structure or error handling are 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?

Schema coverage is 100% with one parameter 'inputs' described as a map of IDs to values. The description mentions 'user-adjustable 1-5 weighting matrix' and 'applied via AIN Bridge prefill', adding some meaning beyond the schema. However, it does not detail the structure or valid values for the input map, leaving some ambiguity.

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: 'Score and compare BaaS providers across 10 capability dimensions'. It specifies the verb 'score and compare', the resource 'BaaS providers', and the output 'weighted comparison matrix and Markdown evaluation memo'. There is no ambiguity, and it differentiates from sibling tools due to its unique 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 implies usage context but does not explicitly state when to use this tool versus alternatives. It mentions the capability dimensions and outputs, but lacks guidance on prerequisites or when not to use it. Given the sibling tools are diverse, some explicit differentiation would help, but it's adequate.

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 value beyond annotations by stating deterministic runs, zero PII, zero egress, and AP2 artifact export. It aligns with readOnlyHint, idempotentHint, and destructiveHint. However, it does not address auth or rate limits, though these are less critical for an in-browser tool.

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

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

The description is concise and front-loaded with purpose. It packs relevant details into a single paragraph, though some jargon may reduce clarity. It earns its sentences without major 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 (4 params, nested objects, no output schema), the description provides pipeline context and mentions artifact type but lacks details on output format or policy_parameters fields. The reference to an external manifest partially compensates but leaves 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 is fully described (100% coverage), so the baseline is 3. The description does not add extra meaning for parameters beyond the schema; it includes pipeline context but no new param-specific details.

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 agent-traffic acceptance policy builder with deterministic in-browser execution and AP2 artifact export. It distinguishes from sibling builders by mentioning agent_guardrail_mandate and specific pipeline context, 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 provides pipeline context (upstream/downstream artifacts) but lacks explicit guidance on when to use this tool versus alternatives (e.g., other build tools). No when-not-to-use or comparison information 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 (readOnlyHint, idempotentHint), the description adds key behavioral traits: runs deterministically in-browser, zero PII/egress, and exports an AP2 artifact with execution_hash for provenance. This provides valuable context not captured in 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 at about 4 sentences, front-loading the purpose and key characteristics. It avoids fluff but could be slightly more streamlined (e.g., the URL is operational info). Still, it is well-structured 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?

Given the complexity (4 parameters, nested objects, no output schema), the description is moderately complete. It covers dependencies and output format but lacks details on the AP2 artifact structure or how parameters influence the result. The presence of annotations partially compensates.

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 description does not add any additional meaning to the parameters beyond what the schema already provides. The baseline score of 3 is appropriate as the schema fully describes each parameter, including the enum type for 'compute'.

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 'AI Act Conformity Pack Builder', a compute node that builds a conformity pack artifact. It distinguishes from siblings like 'assess_ai_act_conformity' (assessment) and 'run_ai_act_highrisk_fit' (diagnostic) by positioning itself as a downstream builder consuming those 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 implicitly indicates usage by listing upstream and downstream tools (e.g., consumes from the high-risk fit diagnostic), but lacks explicit guidance on when to use this tool versus alternatives, such as when not to use it or 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 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?

Annotations already indicate readOnlyHint=true, idempotentHint=true, 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', which align with annotations and provide extra safety and privacy assurances.

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 purpose and key traits. It includes a URL for direct access. While concise, it could be more structured (e.g., bullet points). Every sentence adds value, but the URL at the end is somewhat tangential.

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, chaining context, compute modes), the description provides enough context for an agent to understand its role in a workflow and its safety profile. The absence of an output schema is compensated by mentioning 'Exports an AP2 artifact'. However, 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 description coverage is 100%, so the input schema already documents all parameters. The description does not add significant meaning beyond the schema, except for mentioning 'execution_hash values' and 'tool_id values' for chaining. The note 'See the tool's manifest for field names' for policy_parameters is vague and does not enhance clarity.

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: 'FRIA & Post-Market Monitoring Plan Builder' and identifies it as an OpenChainGraph compute node. It specifies the compliance mandate and provides context about being deterministic and in-browser, differentiating it from siblings that may operate server-side or on different domains.

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 consuming upstream artifacts and feeding into specific downstream tools (e.g., 'art-64-ai-act-highrisk-fit-diagnostic', '451-sr11-7-model-risk-management-gap-assessor'), which implies a workflow position. However, it does not explicitly state when to use this tool over alternatives (e.g., other 'build_' tools) or provide 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?

Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds 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 discloses execution model and data handling 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 extremely concise, consisting of two sentences that cover purpose, target specification, and operational context with no redundancy or filler words.

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

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

Given the tool has one parameter, no output schema, and clear annotations, the description covers key aspects: what it builds, how it runs (client-side, zero PII, zero network), and its target spec. Minor context missing (e.g., what 'VDC' stands for) but acceptable for domain-specific 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 description coverage is 100%, with the single 'inputs' parameter well-documented. The description adds value by explaining that inputs are applied via AIN Bridge prefill and that the tool renders as a widget, providing context on how parameters are used.

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

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

The description explicitly states the tool's function: 'Build or validate a Google AP2 Checkout/Payment Mandate VDC (Open/Closed).' It differentiates itself by noting it targets the external AP2 spec, not the AINumbers Policy Mandate, distinguishing it from siblings like 'ap2_aml_mandate_builder' and 'validate_ap2_mcp_policy'.

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 by specifying the tool targets the external AP2 spec, implying it is not for AINumbers Policy Mandate usage. However, it does not explicitly state when to use this tool versus alternatives or provide exclusion criteria, leaving a slight gap.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, indicating safety. The description adds behavioral details: runs in-browser, zero PII, zero egress, exports execution_hash for provenance, and lists upstream/downstream artifacts. This complements 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 focused paragraph that conveys essential information without verbosity. It includes a URL for direct access, which is valuable. It could be slightly more structured (e.g., bullet points), but it is concise and front-loaded.

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

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

Given the tool has 4 parameters (all optional) and no output schema, the description provides sufficient context about the tool's role and execution. However, it lacks details on what the exported artifact contains or how policy_parameters should be structured, relying on a vague 'see the tool's manifest' which may not be accessible.

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%, so each parameter already has a description. The tool description does not add extra semantics beyond the schema. For example, policy_parameters is described in the schema as 'Input parameters for this tool's decision function' and references a manifest, but the tool description does not elaborate further.

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

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

The description clearly states the tool's purpose: it is an OpenChainGraph compute node for compliance control that builds a Mastercard Agentic Token scope, runs in-browser, and exports an AP2 artifact. This distinguishes it from sibling tools like build_chaingraph or build_google_ap2_mandate by being specific to Mastercard Agentic.

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 where the tool fits in a pipeline (consumes upstream artifacts, feeds downstream) and notes it is deterministic and zero-egress. However, it does not explicitly state when to use this tool versus alternatives or provide contraindications, leaving usage implicit.

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

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds context about deterministic in-browser execution, zero PII/egress, and the exported artifact's execution_hash, which are useful 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 relatively concise and front-loaded with key details. The inclusion of a URL 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 params, nested objects, no output schema), the description covers purpose and some behavioral traits but is incomplete on output format and full chain context. The mention of upstream/downstream artifacts helps but gaps remain.

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 significantly add meaning to the parameters beyond what the schema provides. The note about consuming upstream artifacts relates to parent_hashes but is implicit.

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 No-Russia-Clause Pack as a compute node, specifying data handling and provenance. However, it does not differentiate from sibling tools like build_ai_conformity_pack or 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 lacks guidance on when to use this tool versus alternatives. It mentions upstream/downstream artifacts but no explicit conditions 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?

Annotations already indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral traits: deterministic execution, in-browser computation (privacy), zero PII, zero egress, and the export format (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 three sentences long and conveys key information: behavior (deterministic, in-browser), privacy (zero PII, zero egress), pipeline integration, and a URL. It is dense but clear, though the first sentence repeats the title 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 4 parameters (none required) with nested objects and no output schema, the description should elaborate more on the output (AP2 artifact structure, contents of execution_hash). It provides pipeline links but lacks details on what the tool returns, which is important for downstream consumption.

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 describes all four parameters clearly. The tool description does not add any additional context or examples for the parameters, so it remains at 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 title and description clearly state this tool builds a Digital Product Passport Cradle-to-Gate Lineage. It specifies the resource (lineage builder), the action (build), and distinguishes from siblings by mentioning specific upstream and downstream artifacts (art-115-dpp-data-carrier-validator and art-117-product-authenticity-verifier).

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 pipeline context (consumes from upstream, feeds downstream) which helps the agent understand when to use this tool in a workflow. However, it does not explicitly state when the tool should not be used or list alternative sibling tools for 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?

Annotations already declare safe, read-only, idempotent behavior. The description adds the key property of determinism ('same hashes same order produce same root') and mentions regulatory context, going beyond 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?

Three sentences with no wasted words. First sentence states the action, second lists returns, third adds constraints and properties. Well-structured and front-loaded.

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

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

For a tool with 4 params and no output schema, the description covers the main return (session receipt and audit prompt), deterministic property, and compliance. It lacks error handling details, but overall is sufficient for selecting and invoking correctly.

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

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

Schema coverage is 100% with parameter descriptions. The description adds value by reinforcing the ordering requirement for 'execution_hashes' and 'tool_ids' and clarifying that hashes come from ChainGraph tool calls, beyond the schema's brief descriptions.

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

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

The description clearly states the verb 'aggregates' and the resource 'execution_hashes into a SHA-256 Merkle root,' and distinguishes itself from siblings by mentioning the audit prompt and regulatory compliance (EU AI Act, DORA).

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 an entire agent session and orders hashes, providing clear context. It lacks explicit exclusions or alternative tool mentions, but the sibling tools like 'verify_execution_hash' are implicitly different.

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 readOnly and idempotent. Description adds key behavioral context: zero server-side execution, all logic runs in browser, and pre-fill via base64url fragments. 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?

Description includes a massive redundant list of chain names already present in the schema parameter description. This wastes tokens and harms conciseness. The core purpose is stated in the first two sentences, but the bloated list detracts from structure.

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 lacks details about the return format (e.g., array of URL strings). It explains the workflow use case and behavioral traits, but omits specifics of the deep-links' structure. Adequate but not 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 coverage is 100% with descriptions for both parameters (chain, steps). Description repeats the chain list from schema, adding marginal value. It explains mutual exclusivity and pre-fill behavior, which is helpful but not essential 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 states the tool constructs ordered deep-links for workflow chains or ad-hoc sequences, with specific verbs and resources. It distinguishes itself from sibling tools by focusing on ready-to-use browser deep-links for workflow handoff, not server-side execution.

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 explicitly says 'Use this to hand a user a complete workflow' and explains the workflow process. It mentions zero server-side execution, but lacks explicit when-not-to-use or alternative tool mentions. However, the intent is clear for an agent.

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 context beyond annotations: deterministic in-browser execution, zero PII/egress, artifact exports with execution_hash, and chain provenance details. 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 and well-structured, front-loading the purpose. However, it uses jargon like 'AP2 artifact' that might require external knowledge. No wasted words.

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

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

Given the complexity (nested objects, no output schema), the description provides ample context: data flow, compute modes, and safety characteristics. It explains the tool's role in the chain sufficiently for an agent to decide when to invoke 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?

Schema coverage is 100% and the schema descriptions are detailed. The description does not add new meaning beyond the schema, but it does provide context about the tool's place in the chain, which indirectly relates to parameters. Baseline 3 with no extra 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?

The description clearly identifies it as a CBAM Embedded-Emissions Calculator and describes its role in a computation chain. However, it could be more direct in stating the primary function (calculating embedded emissions) as a simple verb+noun phrase.

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 compute modes and upstream/downstream dependencies, implying when to use it in a pipeline, but lacks explicit guidance on when to choose this tool over siblings 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?

The description adds behavioral context beyond annotations by stating deterministic in-browser execution, zero PII/egress, and artifact export with execution_hash. These details align with the readOnlyHint and idempotentHint annotations, enhancing transparency 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 concise and front-loaded with the tool's purpose. However, it includes dense technical terms (e.g., AP2 artifact, chain provenance) that may reduce readability, but still efficiently conveys essential 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, nested object, no output schema) and rich annotations, the description provides adequate context about its role, execution environment, and data flow. It lacks details on error handling or performance but is sufficient for deployment 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?

Input schema has 100% description coverage, so the description adds minimal value. It only reiterates compute mode and references the manifest for policy_parameters, which is not helpful 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 CSDR Cash-Penalty Calculator with specific verb and resource. It distinguishes itself from siblings by detailing its deterministic in-browser execution, chain provenance, and artifact flows, which is unique among similar calculators.

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 guidance on when to use this tool versus alternatives. It mentions upstream and downstream artifacts but does not provide explicit context for selection among siblings like 'model_buy_in_exposure' or 'compute_settlement_efficiency_kpi'.

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 key behavioral traits: runs deterministically in-browser, zero PII, zero egress, and exports an AP2 artifact with execution_hash for chain provenance. This provides privacy and execution context not covered by annotations. No contradictions 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?

Description is four sentences, front-loaded with purpose, then behavioral traits, then chain dependencies, and ends with a URL. Every sentence serves a distinct purpose with no redundancy or fluff. Highly efficient and well-structured.

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

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

The description covers purpose, determinism, privacy, and chain integration. However, it lacks explicit clarification of what 'Art 67 Own-Funds' calculates and the output format beyond 'AP2 artifact with execution_hash'. Without an output schema, more detail on the return value would enhance completeness. Still, it is mostly sufficient for domain experts.

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 fully described in the input schema (100% coverage). The tool description does not add any new information about parameters beyond what the schema already provides. Baseline of 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?

Clearly states it is an 'Art 67 Own-Funds Calculator' and an 'OpenChainGraph compute node (compliance_mandate)', specifying the resource (own funds) and verb (calculate). It distinguishes itself from siblings by mentioning upstream/downstream artifact chain dependencies, which is unique among sibling tools.

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

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

The description mentions it consumes artifacts from 'art-100-mica-casp-authorization-readiness' and outputs to 'cry-04-merkle-batch-verifier', implying a chain usage. However, it does not explicitly state when to use this tool vs alternatives, nor provides any exclusion criteria. Usage is inferred but not directly guided.

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, destructiveHint=false, etc. The description adds valuable context: deterministic in-browser execution, zero PII/egress, exports AP2 artifact with execution_hash for provenance, and references consuming upstream artifacts. This fully discloses behavioral traits 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 (two sentences plus a URL) and front-loaded with the title. It efficiently conveys core characteristics, though the technical jargon (e.g., OpenChainGraph, AP2 artifact) may be dense but is appropriate for the domain. Every sentence adds value.

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

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

Given the complexity (4 parameters, nested objects, no output schema), the description covers execution environment, data handling, and chain provenance. However, it does not describe the output artifact structure or detail the policy_parameters object fields, leaving some gaps. Still, it is mostly complete for 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?

Schema description coverage is 100% per context signals, so the baseline is 3. The description mentions consuming upstream artifacts from a specific gap checker, which gives context for parent_hashes and parent_tool_ids, but does not add detailed semantics for parameters like policy_parameters beyond what the schema provides.

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 it calculates NIS2 penalty exposure under Article 34, referencing the regulation and providing specific details like being an OpenChainGraph compute node. This clearly identifies the tool's function and distinguishes it from siblings that focus on other NIS2 aspects (e.g., checks, scoring).

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 within a compliance chain graph (consumes upstream artifacts) but does not explicitly state when to use this tool versus alternatives like score_nis2_incident_significance or check_nis2_art21_measures. No exclusions or alternative recommendations are provided, leaving the agent to infer context from the sibling list.

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 key behavioral traits: deterministic in-browser execution, zero PII/egress, export of AP2 artifact with execution hash for chain provenance. This provides useful context not in 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?

Description is brief yet informative: front-loaded with name and key attributes (deterministic, browser-run, zero PII), followed by output paths. Every sentence adds value.

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

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

Given full schema coverage, annotations, and the description's coverage of determinism, artifact export, and downstream feeds, the description is complete for an AI agent to select and invoke the tool correctly.

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

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

Schema description coverage is 100%, so the schema defines parameter semantics well. The description adds little beyond mentioning compute modes and parent hashes, so no significant added 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?

The title and description clearly state the tool calculates a repo haircut on-chain, specifying it is a 'OpenChainGraph compute node (collateral_mandate)' and listing output feeders. This differentiates it from sibling tools like 'calculate_cbam_embedded_emissions' by focus and 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 implies usage for on-chain repo haircut calculation with collateral mandate, but provides no explicit guidance on when to use it 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?

The description goes beyond annotations by stating deterministic in-browser execution, zero PII, zero egress, and export of an artifact with execution_hash for provenance. This aligns with annotations (readOnlyHint=true, idempotentHint=true) and adds valuable context about safety and determinism.

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

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

The description is a single, well-structured paragraph with front-loaded purpose. It is concise but includes a URL which, while informative, adds length. Could be slightly trimmed without losing critical information.

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

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

For a tool with 4 optional parameters, high schema coverage, and full annotations, the description is mostly complete. It explains the compute modes, chaining via parent_hashes, and artifact export. The main gap is the lack of detail on 'policy_parameters' content, but the schema's additionalProperties provides flexibility.

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 description does not add meaning beyond what the input schema already provides for each parameter. The description omits any details about the 'policy_parameters' nested object fields, relying on the schema's generic 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 title and description clearly state the tool calculates the Solvency II SCR Ratio. It identifies itself as an OpenChainGraph compute node and specifies the output feeds into a reconciliation bridger, distinguishing it from sibling calculation tools by its specific regulatory domain (Solvency II).

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?

While the description implies use for SCR ratio calculation and chain provenance, it does not explicitly state when to use this tool over alternatives or provide conditions for non-use. No guidance on trade-offs with sibling tools like 'calculate_cbam_embedded_emissions'.

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 safe read-only and idempotent behavior. The description adds valuable context: it runs deterministically in-browser, has zero PII and zero egress, and exports an AP2 artifact with execution_hash. 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 two sentences, front-loading the core purpose and then adding key details (determinism, PII, artifact, inputs/outputs, URL). Every sentence earns its place with no unnecessary words.

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

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

Given no output schema, the description explains that it exports an AP2 artifact with execution_hash for chain provenance and mentions upstream/downstream artifacts. While it doesn't detail the calculation itself, the annotations and schema cover safety and parameters adequately for this complex tool.

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

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

Schema description coverage is 100%, and the description does not add significant meaning beyond what the schema already provides. It mentions compute modes and policy_parameters briefly, but the schema already details these comprehensively.

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 XVA / CVA Calculator and specifies its role as a deterministic compute node in OpenChainGraph. It mentions input/output artifacts and a URL, distinguishing it from sibling tools that focus on other calculations.

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 within a pipeline (consumes from qfa-01, feeds ptg-01) but does not explicitly state when to use this tool over alternatives or when not to use it. No direct comparison to other calculators 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?

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint), the description discloses determinism, in-browser execution, zero PII, zero egress, artifact export with execution_hash for chain provenance, and upstream/downstream dependencies. This provides rich behavioral context not captured in 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 purpose and regulatory context, then covers behavior, artifact details, dependencies, and a URL. It is dense but not excessively long; every sentence adds value. Slightly more structure (e.g., bullet points) could improve scanability, but it remains effective.

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, behavior, and dependencies well, but lacks detail on the output format (e.g., what the AP2 artifact contains beyond execution_hash, whether the result is a boolean, attestation status, or full report). Since no output schema exists, the description should clarify return values more thoroughly.

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 description does not add additional meaning beyond the schema's parameter descriptions. While it mentions 'compute mode' and 'policy_parameters' in context, it doesn't elaborate on their usage or semantics beyond what the schema provides, so baseline 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 the tool checks agent identity and authorization attestation, with specific reference to regulatory context and artifact chaining. It distinguishes itself from sibling tools by focusing on agent KYA compliance and OpenChainGraph compute node, making its purpose unambiguous.

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

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

The description provides context for when this tool might be needed (EU AI Act compliance deadline) and mentions upstream/downstream artifact dependencies, but it does not explicitly state when to use this tool versus alternatives or provide conditions for non-use. The guidance is implied rather than 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: 'Runs deterministically in-browser; zero PII, zero egress,' and mentions output chain provenance. Annotations already indicate non-destructive and idempotent behavior, so the description complements 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 relatively concise for the amount of information provided, but it includes technical jargon that could be clearer. It front-loads the purpose but the structure is a single dense paragraph.

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

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

While the description provides context about execution environment and artifact export, it lacks explanation of what the marking checker actually evaluates (e.g., criteria for Art. 50 compliance). No output schema exists, so description should compensate more.

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

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

The schema already covers all 4 parameters with descriptions (100% coverage). The description adds minimal extra semantic value beyond the schema, mostly contextualizing the node behavior.

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 'EU AI Act Art. 50 Marking Checker' and specifies its role as an OpenChainGraph compute node for compliance mandates, distinguishing it from siblings by mentioning specific output feeds and a URL.

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

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

No guidance is provided on when to use this tool versus its siblings. It does not mention when not to use it or what alternatives exist among the many compliance-related tools.

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

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

The description adds significant behavioral context beyond annotations: deterministic in-browser execution, zero PII, zero egress, and exports an AP2 artifact with execution_hash for chain provenance. This aligns with readOnlyHint and idempotentHint. No contraction with annotations. Slight deduction for not explicitly stating that no state is mutated, but the readOnlyHint already covers that.

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 purpose. All sentences add value (purpose, execution traits, pipeline dependencies, URL). It could be slightly more structured (e.g., bullet points), but it is efficient and not verbose.

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

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

Given the tool has 4 parameters and no output schema, the description explains its role as a compute node in a chain graph and the artifact it produces (AP2 with execution_hash). However, it does not describe the actual conformance result (e.g., pass/fail, detailed violations). The output semantics are only implied by the pipeline context. This is a gap for a tool intended to check conformance.

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 4 parameters, so the baseline is 3. The description does not repeat parameter details but adds overarching context about the tool's pipeline role (parent_hashes, parent_tool_ids implied by upstream artifacts). However, it does not add specific parameter semantics beyond the schema, so no extra 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?

The description clearly states it is an 'Allocation/Affirmation Conformance Checker' and an 'OpenChainGraph compute node', specifying its role in a compliance pipeline. It lists upstream and downstream artifacts, which clarifies the specific context. However, it does not explicitly differentiate from sibling conformance checkers like check_ai_act_art50_marking or check_cra_annex1_completeness, preventing a 5.

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 pipeline context (upstream and downstream artifacts) but gives no explicit guidance on when to use this tool versus alternatives. There is no 'use for X, not for Y' or conditional logic. An AI agent would struggle to know when to invoke this over other conformance checkers.

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: deterministic in-browser execution, no PII/egress, exports artifact with execution_hash, and consumes specific upstream artifacts. Annotations already declared readOnlyHint, idempotentHint, and destructiveHint false, so the description enriches safety and provenance understanding.

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 informative with 5 sentences covering purpose, behavior, and dependencies. The URL adds context. It is well-structured and front-loaded, though could be slightly more 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 annotations cover safety and idempotency, and no output schema exists, the description sufficiently explains the tool's nature and output (artifact with execution_hash). It is complete for a checker tool with clear behavioral 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?

Schema coverage is 100%, so the input schema already fully documents parameters. The description does not add meaning beyond the schema (e.g., does not explain 'policy_parameters' or 'parent_hashes' further). 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's an 'On-Chain Cash-Leg Finality Checker' with a specific verb (check) and resource (cash-leg finality). However, it does not differentiate from sibling tools, which is expected given the specialized name but still a gap.

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 deterministic, in-browser context with zero PII and zero egress, and notes it consumes upstream artifacts. But it provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or conditions.

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 no destructive behavior. The description adds valuable behavioral context: deterministic in-browser execution, zero PII/egress, and AP2 artifact export with execution_hash. It aligns with annotations and adds nuance, though could mention side effects like chain provenance.

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 short but includes unnecessary technical details (URL, specific artifact IDs) that could be streamlined. It front-loads the main purpose but reads densely. Every sentence adds some value, though some could be merged or removed.

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 only mentions exporting an AP2 artifact without describing its content or format. The artifact chain context is useful, but the absence of output details leaves a significant gap 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?

Schema coverage is 100% with descriptions for each parameter. The description does not add meaning beyond the schema; it only references artifact consumption/output. Baseline score of 3 is appropriate as the description adds no further parameter insight.

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 CRA Annex I Completeness Checker and states its deterministic, in-browser execution with zero PII/egress. It distinguishes from sibling check tools by specifying the compliance mandate and artifact chain, though the jargon may obscure the core action.

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 hints at when to use by mentioning upstream/downstream artifacts (art-138, art-140), but provides no explicit guidance on when to choose this tool over alternatives or when not to use it. No exclusions or alternatives 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 valuable behavioral details: runs deterministically in-browser, zero PII/egress, exports AP2 artifact with execution_hash for chain provenance. This goes beyond annotations and clarifies safety and execution environment, though it doesn't cover all potential edge cases.

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

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

The description is extremely concise: two sentences and a URL. It front-loads the purpose and key traits (deterministic, zero PII, provenance) and lists upstream/downstream artifacts. Every sentence adds value without redundancy. The URL provides additional reference without cluttering the 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?

Despite good schema coverage and annotations, the description lacks crucial information: what constitutes a compliance check (specific rules, criteria), and what the output of the tool is (no output schema, no mention of result format). For a compliance checker, this is a significant gap. The tool's role in a chain is clear, but the functional output and success/failure conditions are not described.

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 four parameters have descriptions in the input schema). The description adds no additional parameter-specific semantics. Since the schema already explains compute modes, parent_hashes, etc., the description's lack of parameter context is acceptable, achieving 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 title 'Digital Trade Rules Compliance Checker' suggests the tool checks compliance with digital trade rules, but the description focuses on technical details (OpenChainGraph compute node, deterministic in-browser, zero PII/egress) without specifying what rules are checked or what the compliance criteria are. Compared to siblings like 'check_ai_act_art50_marking', the purpose is vague.

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 vs alternatives. The description only mentions upstream and downstream artifacts, implying it's part of a chain, but does not state prerequisites, preferred contexts, or exclusion cases. With many sibling compliance check tools, this omission makes selection difficult.

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 annotations declare readOnlyHint, idempotentHint, and destructiveHint as false/true. The description adds valuable behavioral details: deterministic execution, zero PII/egress, exports AP2 artifact with execution_hash, and runs in-browser. This provides significant context beyond what annotations offer, though it could mention output 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 three sentences long, covering purpose, safety, and chain dependencies. It is concise but contains jargon ('AP2 artifact', 'execution_hash') that may require domain knowledge. The structure is acceptable but could better 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?

The description covers execution environment, safety, and chain links. However, it lacks details about the output (what the AP2 artifact contains, completeness status) and specific criteria for completeness. Given the complexity and absence of an output schema, more context on the result 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 for all 4 parameters. The description does not add new parameter-level information beyond mentioning upstream artifact IDs, which aligns with the schema's description for parent_hashes/parent_tool_ids. The baseline score of 3 is appropriate as the schema already documents parameters thoroughly.

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 state that the tool checks EMIR UTI completeness. The description adds context about being an OpenChainGraph compute node and its role in a pipeline. However, it does not define what 'completeness' entails or what specific checks are performed, which slightly diminishes clarity.

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 (art-153, art-155) which imply when to use the tool in a chain. However, it does not explicitly state when to use this tool versus alternatives, nor does it give prerequisites or exclusions. The usage context is implied but not fully articulated.

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: deterministic in-browser execution, zero PII/egress, and artifact export with execution_hash. This 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 front-loaded with purpose and context, followed by behavioral details and outputs. It is reasonably concise given the information provided, though the regulatory deadline list could be 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 fails to explain what the tool returns or how to interpret the results. It mentions exporting an artifact but does not describe the direct output of the tool call. Given no output schema, this is a significant gap.

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 description does not need to elaborate on parameters. The description adds no additional parameter semantics beyond what the schema already provides.

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 readiness checker for EUDI Wallet credential acceptance, specifying its role as an OpenChainGraph compute node. It provides regulatory context and output feeds, but does not explicitly differentiate from sibling tools like assess_eudi_* or other readiness checkers.

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 regulatory deadlines and output feeds but lacks explicit guidance on when to use this tool versus alternatives. No 'when to use' or 'when not to use' instructions 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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. Description adds deterministic in-browser execution, zero PII, zero egress, and artifact export with execution_hash for provenance, providing valuable 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?

Description is a compact paragraph with relevant information front-loaded. Each sentence adds value, though it is slightly dense. No wasted words.

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

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

Given no output schema, description explains place in chain and behavior, but lacks detail on what the conformance check actually entails (e.g., specific tests or criteria). Provides sufficient context for integration but not full functional 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 coverage is 100%, so baseline is 3. Description adds marginal value by referencing execution_hash and chain.parent_hashes, but does not elaborate on policy_parameters 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 states 'FIDO2 / WebAuthn PQC Conformance Checker' with clear verb and resource. It distinguishes from sibling tools like assess_ai_act_conformity by being specific to FIDO2 PQC, but does not explicitly contrast with similar check tools like check_iso20022_pqc_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?

No explicit guidance on when to use this tool versus alternatives. The description mentions upstream and downstream artifacts, implying use in a chain, but does not provide criteria for selection among 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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. The description adds valuable behavioral context: deterministic in-browser execution, zero PII, zero egress, and export of an AP2 artifact with execution_hash. This goes 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 a single paragraph that front-loads the purpose before adding implementation details. It includes a URL and pipeline info, which are somewhat auxiliary but not excessive. Slightly verbose but efficient overall.

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

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

The tool has no output schema, yet the description doesn't explain what the conformance check returns (e.g., pass/fail, metrics). It does provide pipeline context (inputs/outputs) and runtime behavior. Given the complexity (4 params, nested objects), the description is adequate but leaves functional 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?

Schema description coverage is 100%, so the schema already documents each parameter. The description adds minimal extra meaning—only implicit pipeline context. 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 a conformance check for the GPAI Code of Practice. While it focuses on implementation details (compute node mechanics), the core purpose is discernible and distinguishes it from sibling tools 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?

The description mentions upstream and downstream artifacts but gives no explicit guidance on when to use this tool versus alternatives. Sibling tools include many similar check/assess functions, and no criteria or exclusions 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?

Annotations already indicate the tool is read-only, idempotent, and non-destructive. The description adds valuable behavioral context: it runs deterministically in-browser, handles zero PII, zero egress, and exports an artifact with an execution_hash for chain provenance. It also lists a specific upstream dependency. 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 concise with a few sentences, front-loading the tool's purpose. It contains technical details (e.g., URL, artifact export) that are earned. However, it could be slightly more streamlined by omitting the full URL or some implementation specifics.

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 of IFRS 17 and the chain graph context, the description reasonably covers what the tool does, its compute modes, and its position in the pipeline. It lacks a description of what the 'risk adjustment' computes, but the name and title imply the function. No output schema exists, but the exported artifact is mentioned. Overall, adequate but could benefit from a brief note on 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 description coverage is 100% with all four parameters described. The description does not add significant meaning beyond the schema; it only indirectly references parent hashes and tool IDs when mentioning upstream artifacts. With full schema coverage, baseline is 3, and the description provides marginal extra 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?

The description clearly states the tool is an 'IFRS 17 Risk Adjustment Checker' and an 'OpenChainGraph compute node (compliance_mandate)'. It specifies that it runs in-browser, deterministic, and exports an artifact. It distinguishes itself from sibling tool 'validate_ifrs17_csm_rollforward' by noting it consumes upstream artifacts from that validator, establishing its role in the pipeline.

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 mentions the tool's place in a chain (consuming from a specific upstream artifact) but does not articulate when an agent should invoke it directly or what scenarios warrant its use. No when-not-to-use or alternative recommendations 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 valuable behavioral context: 'Runs deterministically in-browser; zero PII, zero egress. Exports an AP2 artifact with execution_hash for chain provenance.' This supplements the 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 concise (two sentences) and front-loaded with the tool's purpose. It includes essential operational details without fluff. Minor improvement would be splitting into bullet points for readability, but it's effective.

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 partially compensates by mentioning the artifact and execution_hash, but it lacks details on the output structure or how to interpret the readiness result. The upstream/downstream dependencies are clear, but completeness is moderate.

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 all parameters adequately. The description does not add further meaning to the parameters beyond what is in the schema. Baseline score 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 a 'SWIFT / ISO 20022 PQC Readiness Checker' and an 'OpenChainGraph compute node (compliance_mandate)', giving a specific verb+resource. However, it does not differentiate from sibling tools like run_pqc_timeline_fit or check_fido_pqc_conformance, which could be confused.

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

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

There is no explicit guidance on when to use this tool versus alternatives. The description lists upstream and downstream artifacts but does not explain the conditions or context for invoking this tool, nor when to avoid 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, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral details: 'Runs deterministically in-browser; zero PII, zero egress' confirms safe, isolated execution, and 'Exports an AP2 artifact with execution_hash for chain provenance' explains the output side effect without contradicting 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 moderate length, front-loaded with the tool's purpose and key characteristics. It is reasonably concise and avoids unnecessary repetition, though it could be slightly more structured.

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

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

The description covers execution environment, safety, and artifact export, but lacks detail on what the tool actually outputs (e.g., conformance pass/fail, scoring) and does not define 'MCP Registry Entry'. With no output schema, the description should at least indicate the nature of results, which 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?

Schema coverage is 100% and each parameter has a description. The description does not add additional parameter semantics beyond what is already in the schema. The mention of consuming upstream artifacts maps to parent_hashes/parent_tool_ids but does not enrich the parameter definitions.

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 explicitly names it a 'Conformance Checker' and the description mentions it runs deterministically in-browser and exports an artifact, but it never clearly states what exactly it checks (e.g., conformance of MCP registry entries). The verb is implied but not directly stated, making purpose somewhat vague.

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 the upstream dependency (art-148-mcp-authorization-metadata-validator) and provides a URL, but gives no guidance on when to use this tool versus any of the 200+ sibling tools. There are no when-to-use or when-not-to-use instructions.

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 useful 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 readOnlyHint, idempotentHint, and non-destructive hints, providing additional reassurance about safety and determinism.

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 (about 80 words) and front-loaded with the title. However, it includes jargon like 'OpenChainGraph compute node' and 'AP2 artifact' that may not be immediately clear to an AI agent. Still, it avoids 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?

The description lacks details about the output artifact's content and how to interpret the gap check results. Since there is no output schema, the description should compensate, but it does not explain what the tool returns or how it feeds into downstream tools. The core function (NIS2 Article 21 gap analysis) remains underspecified.

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 (compute, parent_hashes, parent_tool_ids, policy_parameters). The description does not add meaning beyond the schema; it only implicitly references the 'compute' mode. 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 and description indicate it's a gap checker for NIS2 Article 21, but the description focuses on technical execution details (e.g., OpenChainGraph compute node, browser execution) rather than explicitly stating what it computes (e.g., assessing compliance with ten cybersecurity measures). The purpose is implied but not clearly articulated.

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 (art-141 and art-143) but provides no guidance on when to use this tool over sibling tools like check_nis2_governance_readiness or score_nis2_incident_significance. No explicit 'use when' or 'do not use if' statements.

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 convey read-only, idempotent, non-destructive behavior. The description adds valuable context: deterministic in-browser execution, zero PII, zero egress, export of execution_hash for provenance, and dependency on upstream artifacts. 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?