mica

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

With no annotations provided, the description must fully disclose behavior, but it only says 'with check conditions' which hints at evaluation logic without detailing side effects, required permissions, or return format. It does not contradict any annotations since none exist.

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

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

The description is extremely short, which is efficient, but it is a fragment without a clear sentence structure or front-loaded context. It conveys minimal information in one phrase, making it under-specified rather than properly concise.

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

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

Given the lack of an output schema and annotations, the description is incomplete. An agent cannot infer what the 'Ampel' output looks like or what 'check conditions' entails, nor can it determine which of the three optional parameters are relevant for a given query.

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 each parameter already has a basic description. The tool description adds no extra parameter semantics, such as how parameters interact or whether all are needed, but the schema handles the baseline meaning.

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

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

The description uses 'Ampel' jargon to imply a status indicator but lacks an explicit verb like 'get' or 'retrieve' and does not clearly state what the tool produces. It somewhat distinguishes from sibling 'entity_ampel' by mentioning 'specific MiCA article', but the purpose remains vague and ambiguous.

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

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

No guidance is provided on when to use this tool versus alternatives such as 'entity_ampel' or 'assess_entity'. The description does not mention prerequisites, exclusions, or typical use cases, leaving the agent without 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 must carry transparency. It adds key context by stating 'Runs live FeedOracle assessment,' indicating real-time execution. However, it does not disclose return format, performance implications, side effects, or error conditions, leaving gaps for an 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 two sentences, front-loads the primary action, and contains no redundant information. Every word contributes to understanding the tool's function.

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 optional parameter, no output schema), the description covers the core function and the live-assessment aspect. It is distinct from siblings, though it lacks output details or clarification of 'FeedOracle.' This is sufficient for a basic assessment tool but not fully 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?

The schema has one optional entity_id with a minimal description ('Entity ID (optional)'). The tool description adds no further meaning about the parameter, such as how to find or format entity_id. With 100% schema coverage, baseline is 3, and the description does not elevate it.

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

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

The description states a specific action: 'Assess ALL tokens for an entity in one call.' This clearly distinguishes it from the sibling tool assess_token, which likely handles a single token. The verb 'assess' and resource 'entity's tokens' are explicit.

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

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

The phrase 'ALL tokens' implies a batch use case, contrasting with single-token assessment. It doesn't explicitly name alternatives but the 'ALL vs token' distinction provides clear context for when to use this tool. No exclusionary guidance is given, but for a simple tool this is 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?

With no annotations, the description bears full responsibility for disclosing side effects. It does disclose that the operation is live, uses a specific pack, and updates Ampel, which are important behavioral traits. However, it omits details about permissions, reversibility, rate limits, or what the caller receives, leaving a partial transparency picture.

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

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

The description is exceptionally concise, using two short sentences that convey the core action, method, scope, and side effect without any filler. Every word contributes useful 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?

The description covers the main purpose and side effect, but with no output schema and no annotations, it lacks details about the return value, prerequisites, or expected result format. It is adequately informative for a simple action but not fully complete for an agent deciding whether 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 description coverage is 100% for both parameters, providing clear meanings for entity_id and token_symbol. The description adds no additional parameter semantics, so 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 clearly states a specific action ('Run LIVE MiCA assessment'), the resource ('FeedOracle mica_full_pack'), and the scope ('Evaluates 18 checks, updates Ampel'). It distinguishes itself from siblings like assess_entity by focusing on tokens, making the purpose unambiguous.

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

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

The description implies use for token-level MiCA assessments and mentions 'LIVE', but it does not explicitly state when to use this tool over alternatives or provide exclusions. There is no mention of when to use assess_entity or other sibling tools, leaving usage guidance mostly 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?

With no annotations, the description carries full responsibility for behavioral disclosure. It only describes the audit log's nature without stating whether the tool is read-only, what it returns, or any side effects. This is a critical gap for an agent deciding to invoke it.

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

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

The description is very short and free of fluff, but it is under-specified, lacking a verb and adequate context. It is not an effective sentence, though it is undeniably 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?

The tool is low complexity, but the description fails to state the core action (e.g., retrieving or verifying the audit trail). With no output schema, the description should at least indicate what the tool returns, making it 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 description coverage is 100%, so the schema already explains both parameters (limit, entity_id). The description adds no additional meaning about parameter usage or relationships, so 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 is a noun phrase without a verb, failing to state an action such as 'retrieve' or 'verify'. It adds modifiers like 'chain-linked' and 'integrity check', but this does not clearly differentiate it from sibling tools like gap_report or freshness_check.

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 use cases, prerequisites, or exclusions, leaving the agent without context for tool selection.

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

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

The description discloses the effect of approval: 'Approval upgrades Ampel to GREEN.' However, it does not disclose what happens when rejecting, nor any auth requirements, reversibility, or side effects. Since no annotations are provided, the description carries the full burden and is only partially transparent.

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

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

The description is extremely concise, two sentences, and gets straight to the point. No wasted words are present.

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 the core purpose and an effect, but lacks details on rejection behavior, required inputs (e.g., resolution_id for the operation), and the response format. Given no output schema and no annotations, it is only minimally 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% parameter description coverage, so the schema already documents each parameter. The description adds no extra parameter meaning beyond the schema.

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

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

The description clearly states the tool's function: 'Approve or reject a bridge resolution.' The additional effect 'Approval upgrades Ampel to GREEN' reinforces the specific purpose and differentiates it from sibling tools like bridge_resolve and bridge_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 is provided on when to use this tool versus alternatives. The description implies it is used after a bridge resolution has been created, but it does not specify when to choose this over bridge_status or other workflow tools.

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

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

With no annotations provided, the description carries the full burden. It discloses that a template is generated, but does not indicate whether this creates a persistent record, requires specific permissions, or has any side effects. The mutation nature is under-described.

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 sentence with no filler. Every phrase adds value, and it efficiently conveys the tool's core purpose.

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

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

Given the lack of an output schema and annotations, the description should clarify what the tool returns and how the parameters behave (especially since all are optional). It only mentions generating a template, leaving the operational context vague.

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 parameters, so the baseline is 3. The tool description adds no extra meaning about parameters like check_id or entity_id, so it stays at baseline.

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 action ('Start bridge resolution') and the target ('MiCA gap'). It also lists the template types generated, which distinguishes it from sibling tools like bridge_approve and bridge_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 phrase 'for a MiCA gap' implies when to use it, but there is no explicit comparison to alternatives or exclusions. It doesn't say 'use this instead of X when Y', so the guidance is only implied.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. The verb 'Show' implies read-only behavior, but the description does not explain what 'bridge resolutions' are, whether filters are required despite the schema making them optional, or any output characteristics. Minimal behavioral context is provided.

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 sentence that is front-loaded with the action and resource. It contains no filler or redundant details, making it easy 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?

The description is incomplete for reliable invocation. It does not clarify what 'bridge resolutions' are, nor does it reconcile the phrase 'for an entity/token' with the schema's optional parameters. With no output schema and no annotations, the agent lacks important context about return values and whether zero-filter calls are allowed.

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 entity_id and token_symbol. The description adds little beyond the phrase 'entity/token', so the schema does the heavy lifting. Baseline 3 is appropriate because the description does not fully compensate for the ambiguity around optional filters.

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

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

The description uses a specific verb ('Show') and names a resource ('bridge resolutions'), scoped to entity/token. It clearly indicates a read-only listing operation and is distinguishable from siblings like bridge_resolve or bridge_approve, though it does not explicitly mention alternatives.

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

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

There is no guidance on when to use bridge_status versus sibling tools such as bridge_resolve or audit_trail. The description defines what the tool does but not the context, prerequisites, or exclusions that would help an agent choose it over alternatives.

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

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

With no annotations, the description must disclose behavioral traits, but it only lists topics (events, cross-refs, connected oracles). It does not state whether the operation is read-only, what output format to expect, or any side effects. This is a significant transparency 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 brief (5 words), but it is under-specification rather than effective conciseness. It front-loads the resource name but omits essential operational detail, so the brevity does not serve the agent well.

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

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

Given no output schema and no annotations, the description carries the full burden of explaining what the tool returns and how to invoke it. It fails to define events, cross-refs, or connected oracles, leaving the agent without enough context to confidently use the tool.

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

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

The input schema already fully describes the single parameter entity_id as 'Entity ID for cross-refs' (100% coverage). The description mentions cross-refs but does not add any new meaning beyond the schema, matching 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 'Oracle Event Bus status: events, cross-refs, connected oracles' identifies the resource (Oracle Event Bus) and implies a status check, but it is vague about what the status actually reports. It distinguishes from siblings like article_status or bridge_status via the resource name, but lacks a clear verb and specific scope.

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

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

No guidance is provided on when to use this tool versus alternatives. The description does not mention any conditions, prerequisites, or compare with sibling status tools. It is a bare label without 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?

With no annotations, the description must fully disclose behavioral traits. It only states 'Register' without explaining what this entails: whether it is permanent, requires approvals, validates inputs, or returns any confirmation. This is inadequate for a mutation tool.

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

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

The description is a single, concise sentence with zero wasted words. However, it is slightly too brief for a tool with four parameters and no annotations, but the conciseness itself is good.

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 mutation tool with no annotations and no output schema, the description is incomplete. It does not specify what happens after registration, whether the entity must exist elsewhere, or what the response will be. The one-line description is insufficient for an agent to understand the tool's full behavior.

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

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

Schema coverage is 100%, so each parameter has a description. The tool description adds no additional meaning beyond the schema, but the baseline of 3 is appropriate given that the schema already documents the fields and their types.

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

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

The description clearly states the tool's purpose with a specific verb ('Register') and resource ('new regulated entity'), and the name 'create_entity' aligns with this. It also distinguishes from sibling tools like assess_entity and entity_list, which concern existing entities rather than creating new ones.

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 lacks context for appropriate usage, prerequisites, or exclusions. For example, it does not mention whether this tool is for initial onboarding or if entity_type is required for certain jurisdictions.

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 transparency burden. It discloses that the tool maps signatures and provides assessment, implying a read-only evaluation behavior. However, it does not explicitly state that it is non-mutating, mention authentication or rate limits, or describe any failure or edge-case behavior.

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

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

The description is concise and well-structured: two sentences that front-load the main purpose and then provide additional context on the mapping to the EU trust framework. Every word earns its place, with no redundant or vague 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?

The tool has no output schema and no annotations, so the description must explain return values and usage nuances. It fails to describe what each action (status, assess, reference) actually produces or when to use them. The description provides an overview but leaves significant gaps for an agent to know how to invoke the tool correctly and what to expect.

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

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

The input schema already provides descriptions for all three parameters (action, entity_id, token_symbol), so the baseline is 3. The tool description adds context about eIDAS and FeedOracle, which helps interpret the 'assess' action, but it does not delve into parameter-specific usage or interactions beyond what the schema gives.

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

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

The description clearly identifies the tool's purpose: providing eIDAS-qualified timestamp integration status and assessment. It distinguishes itself from siblings by focusing on the specific EU trust framework and FeedOracle ES256K signatures, making it unique among the listed tools. However, it lacks a direct action verb like 'retrieves' or 'assesses,' instead using a noun phrase ('status and assessment').

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 usage context is implied through the description—users needing eIDAS timestamp integration status or mapping would use this tool. But the description does not explicitly state when to use it over sibling tools like assess_entity or assess_token, nor does it provide exclusion criteria or alternative suggestions.

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

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It describes what the tool does but does not mention whether it is a read-only operation, possible side effects, failure modes, or requirements. This leaves significant behavioral context unstated.

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 sentence that efficiently states the verb, resource, scope, and output. Every word earns its place with no 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 tool is simple with one optional parameter. The description explains the output format (per-token breakdown + overall score), which compensates for the lack of an output schema. However, it does not cover edge cases such as missing entities or the interpretation of the 'Ampel' score, leaving moderate gaps in contextual 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 fully describes the single optional parameter entity_id, providing 100% coverage. The description adds no additional detail beyond what the schema already states, so 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 clearly states the tool aggregates the MiCA Ampel for an entity across all custodied tokens, distinguishing it from sibling tools like assess_entity and assess_token. It also specifies the output includes a per-token breakdown and overall score, making the purpose specific and unambiguous.

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

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

The description implies usage for an entity-wide aggregate view, but does not explicitly state when to use this tool versus alternatives or provide exclusions. The phrase 'ALL tokens' contrasts with per-token tools, but without explicit naming or differentiation, guidance remains only 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?

With no annotations, the description carries the burden. 'List' implies a read-only operation, but it does not disclose details about pagination, permissions, or any side effects. For a simple listing tool, this is adequate but minimal.

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

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

The description is a single, concise sentence with no wasted words, making it highly scannable 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 zero-parameter schema and simple listing purpose, the description is complete enough for an agent to invoke correctly. It lacks return format details, but no output schema exists, and complexity is low.

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?

There are zero parameters, so the baseline is 4. The description adds no parameter-specific information, but none is needed.

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 action ('List') and resource ('all registered entities'), which is specific and distinguishes it from siblings like issuer_list (issuers vs. entities) or assess_entity (assessment vs. listing).

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

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

Usage is implied: this tool lists all entities. However, there is no explicit guidance on when to prefer this over alternatives, nor exclusions (e.g., filtered listing 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, the description carries the transparency burden. It clearly states the action (downgrade), the condition (older than max_age_days), and the direction (GREEN to YELLOW). It does not disclose the scope when entity_id is omitted or whether the operation is idempotent, but the core behavior is transparent.

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

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

The description is extremely concise: two sentences, no filler. The first sentence states the action, the second explains the trigger and schedule. Every word contributes 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?

The tool is simple, but the description leaves ambiguity about the scope when entity_id is not provided (does it process all entities?), and token_symbol is not explained. It also doesn't clarify behavior for already-yellow evidence. Given the lack of output schema and annotations, these gaps make it slightly 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 description coverage is 100%, so baseline is 3. The description adds meaning to max_age_days by tying it to the downgrade condition. However, it provides no additional insight into entity_id or token_symbol beyond the schema's minimal 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 states a specific verb ('Expire') and resource ('stale evidence'), then elaborates with a concrete state transition ('GREEN→YELLOW') and condition ('older than max_age_days'). This clearly identifies the tool's function and distinguishes it from siblings like readiness_check or health_check.

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

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

Provides explicit usage frequency ('Run daily'), which gives clear operational context. However, it does not mention alternatives or when not to use the tool, so it misses the 'when-not' aspect.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals the output format (RED/YELLOW/GREY, priority, actions) but does not state whether the operation is read-only, has side effects, requires authentication, or has rate limits. This is insufficient for a tool with no annotation safety signals.

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

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

The description is a single concise sentence that front-loads the core topic and packs meaningful output details. It is appropriately short, though the fragment 'RED/YELLOW/GREY with priority and actions' could be integrated into a fuller sentence.

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, no annotations, and only a terse description. It does not explain what a gap report consists of beyond color labels, how to invoke it meaningfully, or what the optional parameters do at a behavioral level. This is incomplete for an agent to confidently use the tool.

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

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

The input schema covers both parameters (entity_id and token_symbol) with descriptions, and schema coverage is 100%. The description adds no parameter-specific meaning, so 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 identifies the resource (MiCA compliance gaps) and the output categories (RED/YELLOW/GREY with priority and actions), but it lacks an explicit action verb like 'generates' or 'reports.' It is understandable but does not clearly state what the tool does as a discrete operation, and does not distinguish it from siblings like assess_entity or readiness_check.

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

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

No guidance is provided on when to use this tool versus alternatives such as assess_entity, mica_watchdog, or generate_report. The description offers no context for selecting it, no prerequisites, and no exclusions.

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

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

With no annotations, the description carries the full burden of disclosing behavioral traits. It states the report includes article breakdown, evidence, bridges, and audit, but fails to disclose whether the operation is read-only or creates a record, whether it has side effects, what the return format is, or any permission requirements. 'Generate' suggests mutation but is ambiguous, leaving the agent without critical safety or runtime 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 two short sentences, front-loaded with the core purpose, and every word adds value. The second sentence efficiently lists report contents. No wasted information, making it easy to parse and act on.

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 appears complex, with no output schema and only a minimal description. It fails to specify return format, required inputs, or how the report relates to sibling tools like audit_trail or bridge_approve. The listed contents provide some context, but the description is insufficient for an agent to confidently invoke the tool with the correct parameters and expectations.

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 both parameters described ('Entity ID' and 'Token e.g. USDC'), so the schema already provides basic meaning. The description adds no additional semantics beyond the token focus, such as whether entity_id is needed alongside token_symbol or how they interact. This meets the baseline for adequate but not enhanced parameter understanding.

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

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

The description clearly states the tool generates a MiCA compliance report for a token, with a specific verb and resource. The phrase 'Full article breakdown, evidence, bridges, audit' outlines the report's scope. However, it does not explicitly differentiate from sibling report tools like gap_report or assess_token, so it misses the high bar of distinguishing among alternatives.

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 implies it is for comprehensive compliance reporting, but it does not mention prerequisites, which parameters are required (entity_id, token_symbol, or both), or situations where a narrower tool like assess_token or gap_report would be preferable. The context signals show multiple sibling tools with overlapping purposes, but the description offers no differentiation.

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

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

With no annotations, the description carries full burden for behavioral disclosure. 'Server + DB status' implies a read-only operation but does not state whether it performs network calls, requires permissions, or what exactly is returned. The description is too minimal to convey safety or side effects.

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

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

The description is extremely brief and front-loaded, which is appropriate for a parameterless tool. However, it is slightly under-specified, though that is more a completeness issue than a conciseness issue.

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

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

The description is too terse to be complete. With no output schema and no annotations, it should at least indicate what the status output contains (e.g., UP/DOWN, response times, last checked). The presence of many sibling status tools further demands differentiation, which is absent.

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

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

The tool has zero parameters and schema coverage is 100%, so the schema is trivial. Per the rubric, 0 parameters yields a baseline of 4. The description adds no parameter details, but none are needed.

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

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

The description 'Server + DB status' clearly indicates the resource scope (server and database) and implies a status-checking function. It distinguishes itself from sibling tools like article_status or bus_status by specifying the target resources, though it lacks a verb.

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 many sibling status tools (readiness_check, freshness_check, bridge_status), the description gives no context 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?

Without annotations, the description carries the full burden of behavioral disclosure. It does add one behavioral trait: 'AI-assisted with mandatory human sign-off', which indicates human approval is required. However, it does not disclose what happens during classification, delay, or disclosure, whether records are created, whether it has side effects, or any prerequisites. The description is thin on behavioral 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 concise at two sentences and front-loads the core purpose. It includes regulatory references (MiCA Art. 87-88, Implementing Regulation 2024/2861) which are informative but slightly dense. It avoids unnecessary fluff, earning a good score, though the regulatory citation may be overly specific for a broad audience.

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, no annotations, and 6 parameters, the description is incomplete. It does not explain what actions are available (though the schema lists 'classify, delay, or status'), what the tool returns, or the workflow steps. The description mentions a workflow but does not describe its steps, making it insufficient for a complex regulatory 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%, so the baseline is 3. The description adds no parameter-specific information beyond what the schema already provides. It does not explain how the parameters relate to the workflow or offer usage examples. Since the schema fully describes each parameter, the description does not need to compensate, but it also 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 states that the tool handles 'Inside Information classification, delay and disclosure workflow per MiCA Art. 87-88', which clearly identifies the resource (inside information) and the actions (classify, delay, disclose). It distinguishes itself from sibling tools by focusing on this specific regulatory workflow. However, the description uses a noun phrase ('workflow') rather than a specific verb, and does not explicitly say 'performs' or 'manages', making it slightly less direct than a full purpose 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?

There is no guidance on when to use this tool versus alternatives. The description implies it is for inside information handling, but does not state explicit use cases, exclusions, or compare with sibling tools like article_status or assess_entity. No 'when to use' or 'when not to use' context is provided.

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

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

With no annotations, the description carries the burden of disclosing behavior. The verb 'List' clearly indicates a read-only operation with no side effects, and specifying 'all known' and the included attributes gives a good sense of the output. It does not mention edge cases like pagination or filtering, but this is minor given the zero-parameter interface.

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, self-contained sentence with no redundancy. It front-loads the action and clearly states the output scope and 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 simplicity of the tool (no parameters, no output schema, no annotations), the description is adequately complete. It tells the agent what entities are returned and what details are included. It could benefit from mentioning the return format explicitly, but the basic usage is clear.

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?

There are no parameters, so per the rubric the baseline is 4. The description does not need to explain parameter semantics beyond noting the output fields, which it does.

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 a specific verb ('List') and resource ('token issuers'), and further specifies the attributes included (MiCA authorization status and tokens). This distinguishes it from sibling tools like issuer_profile (which implies a single entity) and entity_list (which may cover a broader entity set).

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 its usage: when an agent needs an overview of token issuers and their compliance status. However, it does not explicitly mention when not to use it or provide alternatives, such as preferring issuer_profile for detailed information on a single 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 conveys that this is a read-only operation ('Shows') and lists the data returned. However, it does not disclose behavior like what happens if the issuer_id is not found, whether the data is real-time or cached, or any access restrictions. This is adequate for a simple getter but leaves some 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 sentence consisting of two succinct phrases. It is front-loaded with the core purpose and then lists supporting details. Every word earns its place, with no extraneous information.

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

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

For a simple read tool with one parameter and no output schema, the description covers the main functional aspects: it returns issuer profile, token list, aggregate rating, authorization status, headquarters, and token scores. It does not explicitly mention the required parameter (though the schema does) or return format, but the level of detail is sufficient for the tool's simplicity. Sibling tool differentiation is missing, but that's covered under usage guidelines.

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 covers 100% of the single parameter (issuer_id) with a clear explanation and examples. The tool description adds no additional parameter semantics, which is acceptable given the high schema coverage. Baseline 3 is appropriate.

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

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

The description clearly states the tool's purpose: it shows an issuer profile with all tokens and aggregate MiCA Ampel, plus authorization status, headquarters, and token scores. The verb 'Shows' and resource 'Issuer profile' are specific. It distinguishes from siblings by mentioning the unique combination of issuer-level data, but it does not explicitly name or contrast with any sibling 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?

There is no guidance on when to use this tool versus alternatives like issuer_list or entity_ampel. The description only lists what the tool displays; it does not provide context, prerequisites, or exclusions.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state whether the operation is idempotent, what side effects occur, whether permissions are required, or what happens if the link already exists. The only disclosed behavior is the action itself.

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, direct sentence with no filler or redundant wording. Every word contributes to the purpose, making it appropriately 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?

For a tool with three optional parameters, no output schema, and no annotations, the description is too thin. It does not clarify the required parameters, the meaning of the 'relationship' values beyond the schema hint, or the overall link lifecycle. More context is needed for reliable invocation.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-specific meaning beyond the schema, but the schema already documents each parameter adequately with simple 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 uses a specific verb ('Link') and identifies both the direct object ('a token') and indirect object ('an entity'), with a clear purpose ('for monitoring'). It distinguishes from sibling tools focused on assessment or status checks, though the concept of 'entity' and 'monitoring' remains somewhat generic.

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, nor does it mention any prerequisites or exclusions. No sibling tools are referenced, and there is no hint about when linking is appropriate.

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

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

Description provides minimal behavioral information: it states it returns monitored sources and alerts, but does not disclose whether it makes external network calls, requires authentication, or has side effects. With no annotations, the description carries full burden but falls short.

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 short sentences, front-loaded with the main action. Both sentences add value: purpose and output. 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?

Given the tool's simplicity (one param, no output schema), the description gives a basic idea of purpose and return type, but it is vague about the structure of returned alerts and how the parameter works in practice. Overall adequate but with gaps.

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

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

The schema fully documents the single parameter 'days_back' (100% coverage), so the baseline is 3. The description does not add additional meaning beyond the schema, such as how the parameter affects the monitoring scope.

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

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

The description uses the specific verb 'Monitor' and identifies specific regulators (ESMA/EBA/BaFin) and topic (MiCA regulatory changes), clearly distinguishing it from sibling tools like freshness_check or health_check.

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 implies usage for tracking MiCA regulatory updates but does not mention exclusions or alternative tools.

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

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

With no annotations, the description carries the full burden. It discloses the output format (score and 10 article statuses) which is helpful, but it does not detail side effects, data dependencies, or whether a token_symbol or entity_id is required. The behavior is clearly a read-only assessment but lacks depth.

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

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

The description is a single sentence, front-loaded with the core purpose and output. It is concise, with no wasted words or redundancy.

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

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

Given no output schema, the description adequately conveys the return structure (score and color per article). However, it does not explain how to choose between the two optional parameters or whether at least one is required. The tool's moderate complexity is only partially covered.

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 description adds no additional meaning beyond the schema. Both entity_id and token_symbol are described in the schema, so the baseline of 3 applies. The description does not clarify optionality or selection logic between the two 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 computes a 'MiCA readiness score + Ampel per article for a token', specifying the resource (token) and the precise output (GREEN/YELLOW/RED/GREY for 10 articles, score 0-100). This distinguishes it from sibling tools like article_status or entity_ampel by focusing on a complete per-article token assessment.

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 given for when to use this tool versus alternatives. It implies usage for token readiness checks, but does not mention prerequisites, exclusions, or why it should be preferred over assess_token or gap_report.

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

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

With no annotations, the description carries the burden. It discloses the human sign-off requirement for 'reasonable suspicion' and AI-assisted detection, which are important behavioral traits. However, it doesn't explain what happens with each action (detect/escalate/status), authentication requirements, or any side effects. The information is relevant but incomplete.

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

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

A single sentence that is well-structured, front-loading the full tool name, regulatory basis, and key operational trait. No redundancy or filler. It achieves maximum information density in minimal space.

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 (5 params, no annotations, no output schema), the description is too brief. It doesn't explain the workflow phases (what 'detect' vs 'escalate' vs 'status' do), return values, or the sequence of steps. The mandatory sign-off is mentioned but not detailed. This leaves significant gaps for an agent trying to invoke the correct action.

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

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

Schema description coverage is 100% for all 5 parameters, so the schema does the heavy lifting. The description only adds context that human sign-off is mandatory, which relates to approved_by but doesn't clarify exact parameter usage or relationships. Baselines at 3 due to high schema coverage, and the description doesn't significantly enhance understanding.

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

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

The description clearly identifies the tool as a STOR workflow under MiCA Art. 92, with AI-assisted detection and mandatory human sign-off. It distinguishes itself from generic entity assessment tools by focusing on regulatory reporting. However, it lacks a specific verb like 'create' or 'manage', and the multi-action nature (detect/escalate/status) is only implied, not stated.

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. Sibling tools like insider_escalation could overlap, but the description doesn't mention any exclusions or comparative context. The regulatory reference (MiCA Art. 92) provides some context but doesn't clarify selection criteria.

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

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

With no annotations provided, the description carries the full burden and partly meets it by listing the specific validation checks (iXBRL/XHTML, taxonomy, mandatory fields, etc.). However, it does not disclose return behavior, whether any action is taken (e.g., archiving), or any side effects, leaving gaps in transparency.

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

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

The description is a single dense sentence that front-loads the core purpose and then lists specific check items. Every part adds value and there is no redundant or filler content.

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

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

The description covers the scope of validation well but omits the return value/output format, which is important since no output schema exists. It also leaves the relationship to sibling tools implicit, making it 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%, so parameters (url, format, token_symbol) are already documented. The description adds only high-level context about format and token but no additional parameter-level detail, so it stays at the baseline.

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

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

The description uses a specific verb ('Validate') and resource ('crypto-asset whitepaper'), with explicit legal references (MiCA Art. 6(10)-(11), ITS 2024/2984). This clearly distinguishes it from sibling tools like assess_token or gap_report, even though no alternative is named.

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

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

The description implies the tool should be used when whitepaper validation against MiCA/ITS is needed, but it does not explicitly state when to use it over alternatives (e.g., assess_token, readiness_check) or provide exclusion criteria.

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