FeedOracle Compliance Agent

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool explains 'WHY' and provides a 'breakdown,' but lacks details on permissions needed, rate limits, error handling, or what the output looks like (e.g., structured vs. narrative). This is a significant gap for a tool with no annotation coverage.

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

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

The description is highly concise and front-loaded: two brief sentences that directly state the tool's purpose and scope without unnecessary words. Every sentence earns its place by conveying essential information efficiently.

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

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

Given the tool's moderate complexity (explaining compliance grades) and no output schema, the description is minimally adequate. It covers the 'what' but lacks details on output format, error cases, or integration with sibling tools. With no annotations, it should provide more behavioral context to be fully complete.

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

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

Schema description coverage is 100%, with the single parameter 'symbol' documented as 'Token symbol.' The description doesn't add any meaning beyond this (e.g., format examples or asset types), so it meets the baseline of 3 where the schema does the heavy lifting.

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

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

The description clearly states the tool's purpose: 'Explains WHY an asset has a specific compliance grade' with 'Dimension-by-dimension breakdown.' It specifies the verb ('explains'), resource ('compliance grade'), and scope ('dimension-by-dimension'), though it doesn't explicitly differentiate from sibling tools like 'compliance_preflight' or 'custody_risk'.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a compliance grade first), exclusions, or compare it to siblings like 'compliance_preflight' or 'custody_risk', leaving the agent to infer usage context.

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

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions 'cryptographic provenance chain' and 'EU AI Act explainability', which hint at security and compliance aspects, but doesn't specify whether this is a read-only operation, if it requires authentication, what the output format is, or any rate limits. For a tool with no annotations, this leaves significant behavioral gaps.

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

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

The description is concise with two short phrases, making it easy to parse. However, it's front-loaded with abstract terms ('cryptographic provenance chain') without immediate clarity, which slightly reduces effectiveness. There's no wasted text, but it could benefit from more direct language.

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

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

Given no annotations, no output schema, and 50% schema coverage, the description is incomplete. It hints at functionality but doesn't provide enough detail for an agent to understand what the tool does, how to use it effectively, or what to expect in return. For a tool with two parameters and regulatory implications, this is insufficient.

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

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

Schema description coverage is 50%, with 'symbol' documented but 'frameworks' lacking a description. The tool description doesn't add any parameter-specific information beyond what's in the schema—it doesn't explain what 'symbol' represents in context or how 'frameworks' affect the provenance chain. With partial schema coverage, the description doesn't compensate adequately, meeting the baseline for minimal 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 states the tool provides 'Full cryptographic provenance chain for evidence data' which indicates a specific function, but it's vague about what 'provenance chain' means operationally. The phrase 'EU AI Act explainability' adds regulatory context but doesn't clarify the actual action. It doesn't distinguish from siblings like 'evidence_bundle' or 'audit_verify' that might handle similar evidence-related 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?

No guidance is provided on when to use this tool versus alternatives. With siblings like 'ai_explain', 'audit_query', and 'evidence_bundle', there's no indication of what makes this tool unique or appropriate for specific scenarios. The description lacks any 'when' or 'when not' instructions, leaving usage ambiguous.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool routes questions automatically but doesn't cover critical aspects like authentication needs, rate limits, error handling, or what happens if routing fails. This leaves significant gaps for a tool that presumably interacts with external APIs.

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 short sentences that are front-loaded with the core purpose. There's no wasted text, though it could be slightly more structured by explicitly separating purpose from mechanism.

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 a tool that routes to APIs, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., what APIs it routes to, response format, error cases), making it inadequate for safe and effective use by an AI agent.

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

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

Schema description coverage is 100%, so the schema already documents both parameters ('question' as required natural language input and 'symbol' as optional override). The description adds no additional meaning beyond implying the 'question' parameter is in plain English, which is redundant with the schema's description. Baseline 3 is appropriate as the schema does the heavy lifting.

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

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

The description clearly states the tool's purpose: 'Natural language evidence query' indicates it processes queries, and 'Routes plain-English questions to correct APIs automatically' specifies the routing mechanism. However, it doesn't explicitly differentiate from sibling tools like 'ai_explain' or 'audit_query', which might have overlapping query functionality.

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 mentions routing to 'correct APIs' but doesn't specify which APIs or contexts, and offers no exclusions or comparisons to sibling tools like 'ai_explain' or 'audit_query' that might handle similar queries.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'tamper-proof audit entry,' which hints at security and immutability, but lacks details on permissions required, rate limits, error handling, or what 'creates' entails (e.g., synchronous/asynchronous, confirmation). For a mutation tool with zero annotation coverage, this is insufficient.

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

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

The description is highly concise and front-loaded, consisting of two clear sentences: 'Log agent decision with evidence chain. Creates tamper-proof audit entry.' Every word contributes directly to the tool's purpose, with no wasted verbiage or redundancy.

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

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

Given the tool's complexity (7 parameters, mutation operation), lack of annotations, and no output schema, the description is incomplete. It fails to explain parameter meanings, behavioral traits like security implications, or return values. For an audit logging tool with significant input requirements, this leaves critical gaps for an AI agent.

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

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

Schema description coverage is 0%, so the description must compensate for 7 undocumented parameters. It only vaguely references 'agent decision with evidence chain,' which maps loosely to 'decision' and 'evidence_request_ids' but ignores other parameters like 'action_taken', 'jurisdiction', 'target_asset', and 'decision_type'. The description adds minimal semantic 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 the tool's purpose: 'Log agent decision with evidence chain. Creates tamper-proof audit entry.' It specifies the verb ('Log', 'Creates'), resource ('audit entry'), and key attributes ('agent decision with evidence chain', 'tamper-proof'). However, it doesn't explicitly differentiate from sibling tools like audit_query or audit_verify, which likely query or verify audit logs rather than create them.

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 doesn't mention sibling tools (e.g., audit_query for retrieving logs or compliance_preflight for pre-checks) or specify contexts like post-decision logging versus real-time compliance checks. Usage is implied only by the tool's name and purpose.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Returns chain-linked decision log' which hints at the output format, but doesn't describe permissions needed, rate limits, whether it's read-only or destructive, pagination behavior (implied by 'limit' parameter but not explained), or error conditions. For a query tool with zero annotation coverage, this is a significant gap.

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 short sentences with zero waste. It's front-loaded with the core purpose ('Query agent's audit trail history') and adds a useful detail about the return format. Every word earns its place, making it easy for an agent to parse quickly.

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 (a query tool with 3 parameters, no annotations, and no output schema), the description is incomplete. It lacks parameter explanations, behavioral context (e.g., safety, performance), and details on the return value beyond 'chain-linked decision log'. Without annotations or output schema, the description should do more to guide the agent on how to use and interpret results.

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

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It doesn't explain any of the three parameters ('client_id', 'limit', 'target_asset')—their meanings, formats, or how they affect the query. For example, it's unclear what 'client_id' refers to or how 'target_asset' filters results. The description adds no parameter semantics beyond what's inferred from the tool name.

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: 'Query agent's audit trail history' specifies the verb (query) and resource (audit trail history). It distinguishes from siblings like 'audit_log' by mentioning 'chain-linked decision log' which suggests a specific type of audit data. However, it doesn't explicitly differentiate from all siblings like 'ai_provenance' or 'evidence_profile' which might also involve historical data.

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 doesn't mention when to choose 'audit_query' over sibling tools like 'audit_log', 'ai_provenance', or 'evidence_profile', nor does it specify prerequisites or exclusions. The agent must infer usage from the name and description alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions 'verify' and 'checks for tampering', it doesn't describe what happens during verification, whether it's read-only or has side effects, what permissions are needed, or what the output looks like. This leaves significant gaps in understanding the tool's behavior.

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

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

The description is extremely concise with just two short sentences that directly state the tool's purpose. Every word earns its place, and the information is front-loaded without unnecessary elaboration.

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

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

Given the complexity of an audit verification tool with no annotations, no output schema, and incomplete parameter documentation, the description is insufficient. It doesn't explain what constitutes 'integrity', what 'tampering' means in this context, or what the verification result would indicate, leaving too many questions unanswered.

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

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

The description provides no information about the 'client_id' parameter. With 0% schema description coverage and no parameter details in the description, the agent has no guidance on what this parameter represents, its format, or its role in the verification process, which is inadequate for a tool with one required parameter.

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

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

The description clearly states the tool's purpose with specific verbs ('verify', 'checks') and resources ('audit chain integrity', 'chain hash linkage for tampering'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'audit_log' or 'audit_query', which prevents a perfect score.

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. With sibling tools like 'audit_log' and 'audit_query' available, there's no indication of when this verification tool is appropriate or what distinguishes it from other audit-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?

With no annotations provided, the description carries full burden. It discloses the return format (PASS/WARN/BLOCK with reason_codes, sources, confidence) and scope (checks multiple compliance aspects), but doesn't mention rate limits, authentication needs, error conditions, or whether it's read-only vs. mutating. It adds some behavioral context but leaves gaps.

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

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

Two concise sentences that are front-loaded with the core purpose and return format. Every word earns its place with no redundancy or 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?

For a compliance check tool with no annotations and no output schema, the description provides good purpose clarity and return format but lacks details about behavioral constraints (rate limits, auth), error handling, and how the check actually works. It's adequate but has clear gaps given the complexity.

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

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

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., doesn't explain how parameters affect the check). Baseline 3 is appropriate when schema does the heavy lifting.

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

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

The description clearly states the tool's purpose with specific verbs ('Pre-flight regulatory check', 'Checks MiCA authorization, evidence quality, custody risk') and resources (regulatory compliance). It distinguishes from siblings by focusing on a comprehensive pre-flight check rather than individual components like 'custody_risk' or 'mica_status'.

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 ('Pre-flight regulatory check', 'in one call') suggesting it's for consolidated compliance assessment, but doesn't explicitly state when to use this vs. alternatives like 'custody_risk' or 'mica_status'. No explicit exclusions or prerequisites 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?

No annotations are provided, so the description carries the full burden. It mentions risk assessment but doesn't disclose behavioral traits like whether this is a read-only query, requires authentication, has rate limits, returns structured data, or involves external API calls. This is a significant gap for a tool with potential financial implications.

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

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

The description is very concise (two brief phrases) and front-loaded with the core purpose. However, it could be more structured—for example, by separating risk factors into a list or adding a brief usage note to improve clarity without sacrificing brevity.

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

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

Given the complexity of risk assessment, no annotations, and no output schema, the description is incomplete. It doesn't explain what the output contains (e.g., risk scores, details on SIFI status), how results are formatted, or any limitations, making it inadequate for informed tool invocation.

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

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

The schema description coverage is 100%, with the single parameter 'protocol' clearly documented. The description adds no additional parameter semantics beyond implying the assessment is protocol-specific, which is already evident from the schema. This meets 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 performs 'custody & counterparty risk assessment' and mentions specific risk factors ('SIFI status, concentration risk'), which gives a specific purpose. However, it doesn't explicitly distinguish this from sibling tools like 'reserve_quality' or 'rlusd_integrity' that might also assess related financial risks.

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 doesn't mention prerequisites, appropriate contexts, or exclusions, leaving the agent to infer usage based solely on the purpose statement.

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

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

No annotations are provided, so the description carries full burden for behavioral disclosure. The description fails to indicate whether this is a read operation, write operation, or verification tool. It doesn't mention permissions required, rate limits, side effects, or what kind of response to expect.

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?

While technically concise (one phrase), the description is under-specified rather than efficiently informative. It fails to communicate the tool's function or usage context, making it ineffective despite its brevity. Every word should earn its place, but this description doesn't provide enough substance.

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 compliance tool with no annotations and no output schema, the description is severely incomplete. It doesn't explain what the tool does, when to use it, what behavior to expect, or what results will be returned. Given the complexity implied by regulatory references and multiple sibling tools, this description is inadequate.

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 one parameter documented in the schema. The description doesn't add any parameter-specific information beyond what's already in the schema (token_symbol). With high schema coverage and only one parameter, 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 description lists regulatory articles (MiCA Art. 29/30/55) and mentions 'recovery plans, redemption plans, annual audit status' but doesn't specify what action the tool performs. It's unclear whether this tool retrieves, creates, updates, or verifies these compliance documents. The description is more of a topic listing than a functional statement.

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 about when to use this tool versus alternatives. With multiple compliance-related sibling tools (compliance_preflight, mica_full_pack, mica_status, mica_market_overview), the description offers no differentiation or context for selecting this specific tool.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'signed bundle' which hints at authentication or verification needs, but doesn't clarify permissions required, rate limits, whether this is a read or write operation, or what the output format might be. For a tool with no annotation coverage, this leaves significant behavioral gaps.

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

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

The description is extremely concise with just one sentence that efficiently communicates the core functionality. Every word earns its place, and it's front-loaded with the main purpose without unnecessary elaboration.

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

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

Given the complexity of multi-framework aggregation, no annotations, no output schema, and incomplete parameter documentation (50% schema coverage), the description is insufficient. It doesn't explain what the aggregated evidence contains, how it's structured, or what 'signed bundle' entails operationally, leaving critical context gaps for proper tool invocation.

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

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

With 50% schema description coverage (only the 'asset' parameter has a description), the description doesn't add meaningful parameter semantics beyond what's in the schema. It mentions frameworks generically but doesn't explain the 'frameworks' array parameter's purpose or the significance of the default values. The baseline is 3 since the schema covers half the parameters adequately.

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 'Multi-framework evidence aggregation' with specific frameworks listed (MiCA, DORA, RWA, Macro), making it a clear verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'evidence_leaderboard' or 'evidence_profile', which appear related to evidence but serve different 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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for aggregation, or how it differs from sibling evidence-related tools, leaving the agent with no usage direction beyond the basic purpose.

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

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

No annotations are provided, so the description carries full burden. It mentions ranking by 'evidence grade A-F', which implies a read-only operation, but doesn't disclose behavioral traits like data freshness, rate limits, authentication needs, or what 'evidence grade' entails. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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, efficient sentence that front-loads the core purpose. Every word earns its place by specifying ranking, grading scale, and scope without unnecessary details. It's appropriately sized for a simple tool.

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 (ranking protocols with grades), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'evidence grade' means, how rankings are determined, the format of returned data, or any limitations. For a tool that likely returns structured rankings, more context is needed to use it effectively.

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

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

The description adds no parameter semantics beyond what the input schema provides. With 0% schema description coverage and 1 parameter (top_n), the schema alone documents it as an integer with default 15. The description doesn't explain what 'top_n' means in context (e.g., number of top-ranked protocols to return), so it doesn't compensate for the low coverage, but the baseline is 3 since there's only one simple parameter.

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

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

The description clearly states what the tool does: 'Top protocols ranked by evidence grade A-F across 61 RWA protocols & 105+ stablecoins.' This specifies the verb (ranked), resource (protocols), and scope (61 RWA protocols & 105+ stablecoins). However, it doesn't explicitly differentiate from siblings like 'evidence_profile' or 'reserve_quality', which might have overlapping 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for ranking protocols, or compare to sibling tools like 'evidence_profile' or 'market_liquidity'. The agent must infer usage from the purpose alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the output includes a grade (A-F) and dimensions, but doesn't explain what the tool actually does (e.g., retrieves data, analyzes protocols, generates reports), its data sources, potential limitations, or error handling. This leaves significant gaps in understanding the tool's behavior.

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

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

The description is very concise—a single sentence that efficiently conveys the core concept (multi-dimensional profile with grades). It's front-loaded with key information, though it could be slightly more structured by explicitly stating the action verb. There's no wasted text, making it efficient for quick understanding.

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 implied by 'multi-dimensional evidence profile' and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a report, score breakdown), how the grading is derived, or any behavioral traits. For a tool with no structured output and no annotations, more detail is needed to guide effective usage.

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

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

Schema description coverage is 100%, with the single parameter 'protocol' clearly documented as 'Protocol name or slug'. The description doesn't add any additional meaning beyond this, such as examples of valid protocols or formatting requirements. Since the schema handles the parameter documentation adequately, a 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 states the tool creates a 'multi-dimensional evidence profile' with specific dimensions (governance, custody, reserves) and a grading scale (A-F), which provides a clear purpose. However, it doesn't specify the exact verb (e.g., 'generate', 'retrieve', 'analyze') or distinguish this tool from sibling tools like 'evidence_bundle' or 'evidence_leaderboard', leaving some ambiguity about its specific function.

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

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

The description offers no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, context for usage, or comparisons to sibling tools such as 'evidence_bundle' or 'reserve_quality', leaving the agent to infer usage scenarios without explicit direction.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'scans for issuer-native yield mechanisms (prohibited)', which implies a read-only compliance check, but does not disclose critical behaviors such as whether it returns a pass/fail result, detailed reports, error handling, or rate limits. The description is insufficient for a tool with regulatory implications.

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

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

The description is concise with a single sentence, but it is not front-loaded with clear purpose. It uses technical jargon ('MiCA Art. 23/52', 'issuer-native yield mechanisms') without plain-language explanation, which may hinder understanding. While brief, it lacks structural clarity for quick comprehension by an AI agent.

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

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

Given the complexity of regulatory compliance tools and the absence of annotations and output schema, the description is incomplete. It does not explain what the tool returns (e.g., compliance status, violation details), how to interpret results, or any behavioral traits like idempotency or side effects. This leaves significant gaps for an AI agent to use the tool effectively.

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

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

Schema description coverage is 100%, with one parameter 'token_symbol' documented in the schema. The description does not add any meaning beyond the schema, as it does not explain how the token symbol is used in the scan or what format it expects. The baseline score of 3 is appropriate since the schema adequately covers the parameter, but the description adds 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 'MiCA Art. 23/52: scans for issuer-native yield mechanisms (prohibited)' is vague and tautological. It restates the tool name 'interest_check' by mentioning 'scans for...yield mechanisms' without specifying what the tool actually does (e.g., checks compliance, flags violations, or analyzes tokens). It does not clearly distinguish this tool from siblings like 'compliance_preflight' or 'mica_status'.

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 is provided. The description implies a regulatory context (MiCA Art. 23/52) but does not specify use cases, prerequisites, or exclusions. For example, it does not clarify if this is for pre-issuance checks or ongoing monitoring, or how it differs from sibling tools like 'compliance_preflight' or 'document_compliance'.

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

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

No annotations are provided, so the description carries the full burden. It mentions outcomes ('receive trust score and access level') but lacks critical behavioral details: whether this is a one-time registration, what permissions are required, if it's idempotent, error handling, or rate limits. The description is insufficient for a mutation tool with zero annotation coverage.

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 clear sentences that efficiently state the tool's purpose and outcome. It's front-loaded and wastes no words, though it could benefit from slightly more detail given the lack of annotations and schema descriptions.

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 (5 parameters, 4 required, no output schema, and no annotations), the description is incomplete. It doesn't explain parameter meanings, behavioral traits, or usage context, leaving significant gaps for an agent to understand how to invoke this tool effectively.

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

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

Schema description coverage is 0%, so the description must compensate. It mentions 'agent metadata' but doesn't explain any of the 5 parameters (e.g., what 'agent_purpose' entails, the significance of 'owner_jurisdiction' defaulting to 'EU', or format requirements). The description adds minimal value beyond the bare schema.

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

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

The description clearly states the tool's purpose: 'Know Your Agent registration' with specific actions ('Provide agent metadata') and outcomes ('receive trust score and access level'). It uses a specific verb ('register') and identifies the resource ('agent'), though it doesn't explicitly differentiate from sibling tools like 'kya_status'.

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 like 'kya_status' or other registration-related tools. It states what the tool does but offers no context about prerequisites, timing, or exclusions for 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Check' implies a read-only operation, the description doesn't specify authentication requirements, rate limits, response format, or whether this is a real-time check versus cached data. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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

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

The description is extremely concise (one sentence) and front-loaded with all essential information. Every word earns its place, with no redundant or unnecessary phrasing. The structure efficiently communicates the core purpose without wasting tokens.

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 moderate complexity (checking trust levels with breakdowns), no annotations, and no output schema, the description is minimally adequate. It states what information is returned but doesn't explain the format, structure, or interpretation of the 'score breakdown' and 'tool access' components. The agent would need to invoke the tool to understand the response.

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 the single required parameter (client_id). The description doesn't add any parameter-specific context beyond what's in the schema. The baseline score of 3 is appropriate when the schema does the heavy lifting for parameter documentation.

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 with specific verbs ('Check') and resources ('agent's KYA trust level, score breakdown, and tool access'). It distinguishes from most siblings by focusing on KYA status, though it doesn't explicitly differentiate from kya_register (which appears to be a registration tool).

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when this tool is appropriate, what prerequisites exist, or how it differs from similar tools like kya_register or mica_status. The agent must infer usage from the name alone.

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

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

No annotations are provided, so the description carries the full burden. It mentions 'analysis' which suggests a read-only operation, but doesn't disclose behavioral traits such as whether it requires authentication, has rate limits, returns real-time or historical data, or what the output format might be. This is inadequate for a tool with no annotation coverage.

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

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

The description is very concise with two brief phrases, making it front-loaded and efficient. However, it could be more structured by explicitly stating the action (e.g., 'Retrieve liquidity depth analysis for a DEX protocol'). Every sentence earns its place, but it's slightly under-specified.

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

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

Given no annotations, no output schema, and a single parameter with good schema coverage, the description is incomplete. It doesn't explain what the analysis entails, what 'exit channel' means, or what the tool returns (e.g., metrics, reports). For a tool with regulatory implications ('MiCA Art. 45'), more context is needed to guide effective use.

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

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

The input schema has 100% description coverage, with the 'protocol' parameter documented as 'Protocol name or slug'. The description doesn't add any meaning beyond this, such as examples of valid protocols or how the analysis varies by protocol. With high schema coverage, 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 description states 'DEX liquidity depth & exit channel analysis' which indicates analyzing liquidity and exit channels for decentralized exchanges, but it's vague about the specific action (e.g., retrieve, calculate, assess). The reference 'MiCA Art. 45' adds regulatory context but doesn't clarify the exact operation. It doesn't distinguish from sibling tools like 'mica_market_overview' or 'reserve_quality'.

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 is provided. The description mentions 'MiCA Art. 45', which might imply usage in regulatory compliance contexts, but it doesn't specify prerequisites, exclusions, or compare to tools like 'compliance_preflight' or 'mica_market_overview'. This leaves the agent without clear direction.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool returns an 'overall_mica_compliant flag', which hints at output behavior, but doesn't describe critical aspects like whether it's a read-only operation, if it requires authentication, potential side effects (e.g., data generation), rate limits, or error handling. For a compliance tool with no annotation coverage, this is inadequate.

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 and front-loaded, consisting of a single sentence that directly states the purpose and output. Every word earns its place, with no redundant or vague language, making it efficient for an agent to parse.

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 MiCA compliance (12 articles) and the lack of annotations and output schema, the description is incomplete. It doesn't explain the return value beyond the flag, potential errors, or how the evidence is structured. For a tool that likely involves significant processing and regulatory nuance, more context is needed to guide effective use.

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

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

The schema description coverage is 100%, with the single parameter 'token_symbol' fully documented in the schema. The description adds no additional parameter semantics beyond what's in the schema, such as format constraints or examples beyond the schema's 'e.g. EURC, USDC, RLUSD'. According to the rules, with high schema coverage, the baseline is 3 even without param info in the description.

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

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

The description clearly states the tool's purpose: 'Complete MiCA compliance evidence for one token (12 MiCA articles).' It specifies the action ('complete'), resource ('MiCA compliance evidence'), and scope ('one token', '12 MiCA articles'), distinguishing it from siblings like 'mica_status' or 'compliance_preflight'. However, it doesn't explicitly differentiate from all siblings, such as 'evidence_bundle' or 'document_compliance', which might have overlapping 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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., after preflight checks), or exclusions, leaving the agent to infer usage from the purpose alone. With many sibling tools related to compliance and evidence, this lack of explicit comparison or context 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?

No annotations are provided, so the description carries full behavioral disclosure burden. While 'market status' implies a read operation, it doesn't specify whether this is real-time data, historical snapshots, requires authentication, has rate limits, or what format the output takes. The description lists content areas but lacks operational context.

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

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

The description is extremely concise with a single sentence that efficiently lists all key components. Every word earns its place - 'Full MiCA market status' establishes scope, and the colon-separated list enumerates specific content areas 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?

For a zero-parameter tool with no output schema, the description provides adequate scope information but lacks behavioral context. The absence of annotations means the description should compensate with more operational details about what 'market status' entails, but it only lists content areas without explaining the nature of the data returned.

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

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

With 0 parameters and 100% schema description coverage, the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the schema already fully documents the empty input structure.

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

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

The description clearly states the tool provides 'Full MiCA market status' with specific components listed (peg alerts, significant issuers, interest violations, stale audits), which gives a concrete verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'mica_status' or 'mica_full_pack', which appear related based on naming.

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. With multiple MiCA-related sibling tools (mica_status, mica_full_pack), there's no indication of when this comprehensive overview is preferred over more specific tools like peg_deviation or significant_issuer.

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

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

No annotations are provided, so the description carries the full burden. It mentions cross-referencing with registers, implying a read-only lookup, but doesn't disclose behavioral traits such as data sources, accuracy, rate limits, or error handling. For a compliance tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that is front-loaded with the core purpose. It avoids unnecessary words, though it could be more structured by explicitly stating the action (e.g., 'Check' or 'Retrieve'). Overall, it's appropriately sized with minimal waste.

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

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

Given the complexity of regulatory compliance tools, no annotations, and no output schema, the description is incomplete. It lacks details on return values, error cases, or operational context (e.g., real-time vs. cached data). This leaves significant gaps for an AI agent to use the tool effectively.

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

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

The description adds no parameter semantics beyond what the input schema provides. With 100% schema description coverage and one parameter ('token_symbol') well-documented in the schema, the description doesn't compensate or add value. This meets the baseline score of 3 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 states the tool checks 'MiCA EU authorization status' and mentions cross-referencing with ESMA/EBA registers, which provides a general purpose. However, it lacks a specific verb and doesn't clearly differentiate from sibling tools like 'kya_status' or 'mica_full_pack', making the purpose somewhat vague rather than precise.

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 is provided on when to use this tool versus alternatives. The description mentions cross-referencing but doesn't specify scenarios, prerequisites, or exclusions. With sibling tools like 'kya_status' and 'mica_full_pack' available, this lack of differentiation leaves usage unclear.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'real-time' which suggests immediacy, but doesn't describe data sources, update frequency, accuracy, rate limits, or error handling. The regulatory reference adds some context but lacks operational details.

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

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

The description is extremely concise with just two brief phrases. While efficient, it might be too sparse - the regulatory reference could benefit from more context. Every word serves a purpose, but additional clarity could improve effectiveness.

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 financial data tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'peg deviation' means operationally, what format or units the output uses, data freshness guarantees, or error conditions. The regulatory reference adds some context but doesn't compensate for these 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% with the single parameter 'token_symbol' well-documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema, maintaining the baseline score 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 provides 'Real-time peg deviation for any stablecoin', specifying both the action (providing peg deviation) and resource (stablecoins). It distinguishes itself from siblings like 'peg_history' by emphasizing real-time data. However, it doesn't fully differentiate from potential similar tools beyond the real-time aspect.

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 includes 'MiCA Art. 35', which implies a regulatory compliance context, but doesn't explicitly state when to use this tool versus alternatives like 'peg_history' or 'market_liquidity'. No guidance on prerequisites, timing, or exclusions 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?

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions '30-day history' which implies a time-bound query, but doesn't specify whether this is read-only, if it requires authentication, rate limits, error handling, or what format the history data returns. The description lacks critical behavioral details needed for safe and effective tool invocation.

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

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

The description is extremely concise with just two brief phrases. It's front-loaded with the core functionality ('30-day peg deviation history') followed by regulatory context. While efficient, it might be overly terse given the lack of annotations and sibling tool context, potentially sacrificing clarity for brevity.

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

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

Given no annotations, no output schema, and multiple sibling tools in similar domains, the description is incomplete. It doesn't explain what 'peg deviation' means operationally, how the history is structured, whether this is for regulatory reporting, or how it differs from related tools. For a tool with potential compliance implications and no structured metadata, more context would be valuable.

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

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

The input schema has 100% description coverage with one parameter 'token_symbol' clearly documented. The description doesn't add any parameter-specific information beyond what the schema provides (e.g., it doesn't explain what tokens are supported or format requirements). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't detract either.

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 '30-day peg deviation history' which indicates the tool retrieves historical data about peg deviations over a 30-day period, providing a clear verb ('history') and resource ('peg deviation'). However, it doesn't distinguish from sibling tools like 'peg_deviation' or 'rlusd_integrity' which might relate to similar concepts, and the 'MiCA Art. 35' reference adds regulatory context but doesn't clarify functional uniqueness.

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 doesn't mention sibling tools like 'peg_deviation' (which might show current deviations) or 'market_liquidity' (which could relate to peg stability), nor does it specify prerequisites or exclusions. The regulatory reference implies compliance use cases but offers no practical usage 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?

No annotations are provided, so the description carries the full burden. It mentions the return values (version, status, tool count), which adds some behavioral context, but it doesn't disclose other traits like whether it's read-only, has rate limits, or requires authentication. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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

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

The description is extremely concise and front-loaded, consisting of a single, efficient sentence that directly states the tool's purpose and return values. Every word earns its place, with no wasted information or redundancy.

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

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

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is adequate but minimal. It covers the basic purpose and return values, which is sufficient for a simple ping tool, but it lacks details on usage context or behavioral traits that could enhance completeness, especially with no annotations to fill in 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 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, and since there are none, it doesn't need to compensate for any gaps. This meets the baseline for tools with no parameters.

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

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

The description clearly states the tool's function ('Server ping') and what it returns ('returns version, status, tool count'), which is specific and informative. However, it doesn't explicitly differentiate this from sibling tools like 'mica_status' or 'kya_status', which might also return status information, so it doesn't fully achieve 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 provides no guidance on when to use this tool versus alternatives. With sibling tools like 'mica_status' or 'kya_status' that might return status for specific components, there's no indication of when 'ping' is preferred, such as for general server health checks versus targeted status queries.

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

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It fails to describe what the tool does operationally—whether it's a read-only check, requires authentication, has side effects, returns structured data, or handles errors. The regulatory references don't explain tool behavior.

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

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

The description is brief but under-specified, not concise. It consists of a fragment referencing legal articles without complete sentences or clear structure. While short, it fails to convey essential information efficiently, making it ineffective rather than truly 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 no annotations, no output schema, and a regulatory-focused tool likely involving compliance checks, the description is severely incomplete. It doesn't explain the tool's function, output, or usage context, leaving critical gaps for an AI agent to understand and invoke it 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%, with the single parameter 'token_symbol' clearly documented in the schema. The description adds no additional meaning about the parameter, such as format examples or how it relates to MiCA regulations. Baseline score of 3 applies since the schema adequately covers the parameter.

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

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

The description references MiCA regulations (Art. 24/25/53) but doesn't clearly state what action the tool performs. 'Reserve management policy, Art. 53 eligibility' suggests checking eligibility or policy details, but lacks a specific verb like 'check', 'verify', or 'retrieve'. It's vague about whether this tool retrieves information, validates compliance, or performs another function.

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

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

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or differentiate it from sibling tools like 'mica_status', 'compliance_preflight', or 'custody_risk', which might relate to similar regulatory compliance domains.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It hints at real-time monitoring and verification, but doesn't specify what 'integrity' entails (e.g., data consistency, security checks), how results are presented, whether it's read-only or has side effects, or any performance considerations like rate limits. This is inadequate for a tool with zero annotation coverage.

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—a single phrase—and front-loaded with the core purpose. Every word contributes meaning without redundancy, making it efficient and easy to parse, though it could benefit from more detail for 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 complexity implied by 'real-time integrity monitoring & attestation verification' and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns, how to interpret results, or any behavioral traits, leaving significant gaps for the agent to understand its functionality.

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

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

The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it doesn't introduce any confusion about inputs. A baseline score of 4 is appropriate as it avoids misalignment with 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 'RLUSD real-time integrity monitoring & attestation verification' states a purpose but is somewhat vague. It mentions the resource (RLUSD) and general activities (monitoring, verification), but lacks a specific verb indicating what the tool actually does (e.g., 'check', 'report', 'validate'). It doesn't clearly differentiate from siblings like 'reserve_quality' or 'peg_deviation', which might involve related integrity aspects.

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 doesn't mention any context, prerequisites, or exclusions, and doesn't reference sibling tools that might handle similar functions (e.g., 'audit_verify' or 'compliance_preflight'). This leaves the agent without clear usage 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe how it works - whether it queries a database, makes API calls, has rate limits, requires authentication, or what happens on failure. For a compliance tool with zero annotation coverage, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that packs maximum information into minimal space. It's front-loaded with the most important information (regulatory context and core function) with zero wasted words or redundant phrasing.

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 single-parameter tool with no output schema and no annotations, the description provides adequate basic context about what the tool does. However, it doesn't explain what the tool returns (e.g., boolean result, detailed report, or just threshold status), which is important given the compliance nature of the check.

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

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

The schema has 100% description coverage with the token_symbol parameter clearly documented. The description doesn't add any parameter-specific information beyond what's in the schema, but doesn't need to since schema coverage is complete. This meets 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's purpose with specific regulatory context (MiCA Art. 45/58), a concrete action (checks if issuer exceeds €5B reserve threshold), and the outcome (for EBA oversight). It uses precise terminology that distinguishes it from sibling tools like compliance_preflight or mica_status.

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 through the regulatory reference (MiCA Art. 45/58), suggesting it's for compliance checks related to reserve thresholds. However, it doesn't explicitly state when to use this tool versus alternatives like mica_full_pack or custody_risk, nor does it provide exclusion criteria or prerequisites.

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