quantum

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

No annotations are provided, so the description must carry full behavioral disclosure. It indicates a read-only operation ('Show') and a non-destructive trait ('gets smarter'), but does not disclose potential side effects, permission requirements, or data freshness. The description adds some context but lacks comprehensive behavioral 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 two sentences: the first clearly states the tool's output, the second adds a motivational note about the mesh improving. The second sentence is slightly extraneous but not verbose. Overall concise and front-loaded with actionable information.

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

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

Given no output schema, the description should give a complete picture of what the tool returns. It lists types of information (weights, rewards, etc.) but does not specify format, structure, or scope (e.g., time range, aggregation). The description is moderately complete but lacks detail for an agent to fully anticipate 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?

The tool has zero parameters, so schema coverage is effectively 100%. The baseline for no parameters is 4. The description adds value by listing what data the tool returns, which is helpful even without formal parameters. No contradiction or omission.

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 shows OracleNet mesh intelligence, listing specific elements like learned weights, rewards, synapse history, and top-performing oracles. It uses a specific verb 'Show' with a clear resource, and the unique 'neural' prefix distinguishes it from the sibling 'quantum_*' tools.

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

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

The description implies the tool is for viewing mesh intelligence but does not explicitly state when to use it versus alternatives. No exclusion criteria or when-not-to-use guidance is provided. While the purpose is clear, there is no comparative guidance against sibling tools like quantum_status.

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 present, so the description must carry the burden. It mentions execution and result delivery but omits side effects, authentication needs, or error handling. The 'execute' parameter implies preview capability, but behavioral traits like mutability or permission requirements are absent.

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, but the metaphor 'front door of OracleNet' may be unclear. Information is front-loaded with the key concept, though a more direct statement could improve clarity.

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

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

Given the complexity (4 parameters, nested objects, no output schema) and lack of annotations, the description is insufficient. It does not explain return values, error states, or the 'oracle' concept, leaving agents underinformed 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 coverage is 100%, all parameters have descriptions. The description adds no new semantic value beyond the schema; it only reiterates the general workflow. Baseline score of 3 is appropriate as schema does the heavy lifting.

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

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

The description clearly states it is the front door of OracleNet, taking natural language needs and returning results. It indicates a general-purpose gateway, distinguishing it from sibling tools like quantum_execute or quantum_scan. However, the exact resource and action are somewhat vague due to undefined 'oracle' concept.

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

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

No guidance on when to use versus alternatives. The description implies using for any natural language need, but does not mention when to avoid it or highlight specific scenarios. Sibling tools exist for more specific functions, but no comparisons are provided.

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

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

With no annotations, the description must disclose behavioral traits. It fails to mention side effects, idempotency, error handling, or authentication requirements beyond the DID parameter. The description is too brief for a tool handling deals and ratings.

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

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

The description is concise (two sentences) and front-loaded with the key action. It wastes no words, though it could be slightly expanded for clarity. It earns a high score for efficiency.

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

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

Given the tool's complexity (3 params, no output schema, no annotations), the description is insufficient. It does not explain the deal lifecycle, return values, or error states. The agent receives minimal guidance on how 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 input schema has 100% coverage, so the parameters are adequately described. The description adds general context ('agent-to-agent commerce') but does not enrich the meaning of individual parameters beyond what the schema provides. The baseline of 3 is appropriate.

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

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

The description clearly states the tool's purpose: proposing and rating deals in agent-to-agent commerce. It uses specific verbs ('propose', 'rate') and identifies the resource ('deal'). However, it could be more explicit about the 'get terms' aspect and how it differs from similar tools like quantum_offer.

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 quantum_offer or quantum_rate. There is no mention of prerequisites, context, or exclusions. The agent is left to infer usage from the generic 'agent-to-agent commerce' phrase.

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 details the execution process (routing, calling, logging, weight updates) but lacks disclosure of side effects or permissions; still fairly transparent without annotations.

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

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

Two succinct sentences plus a clear usage tip, all front-loaded without wasted words.

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

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

Given the tool's complexity (4 params, nested object, no output schema), the description covers workflow, output routing, and prerequisite step (quantum_intent) adequately.

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

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

Schema coverage is 100% with descriptions for all parameters; the description adds no additional parameter meaning, so baseline score is appropriate.

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

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

The description clearly states the verb 'Execute' and the resource 'tool on an OracleNet oracle', and distinguishes from siblings by instructing to use quantum_intent first.

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

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

Explicitly says 'Use quantum_intent first to find the right tool, then quantum_execute to run it', providing clear when-to-use and an alternative.

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 states the tool returns events (signals, changes, alerts) and is designed for polling. While it could mention rate limits or empty results, the core behavior is clear.

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 conveys purpose and usage without any unnecessary words. Every part is valuable.

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

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

Given the absence of an output schema, the description adequately explains that the tool returns an event feed. It covers the key inputs and usage scenario. A mention of the return format (e.g., array) would improve completeness, but it is sufficient.

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

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

Schema coverage is 100%, so baseline is 3. The description supplements the schema by explaining 'limit' as 'Max events (default 20)' and 'event_type' as 'Filter: heartbeat, new_capability, mesh_event, etc.,' adding meaningful context beyond the field names.

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

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

The description clearly states it is an 'OracleNet event feed' providing 'latest signals, changes, alerts.' It distinguishes itself from siblings by explicitly mentioning polling as an alternative to webhooks.

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

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

The description provides clear context for when to use this tool: 'Poll this for updates if you cannot use webhooks.' It does not explicitly exclude any scenarios, but the guidance is direct and helpful.

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. It implies a read-only retrieval and suggestion capability, but does not explicitly state safety, authorization needs, or side effects. The lack of explicit behavioral disclosure is a 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 a single, short sentence with no fluff. However, it is arguably too brief to be fully useful; adding a few more details would not harm conciseness and would improve clarity.

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

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

For a tool with two parameters and no output schema, the description should explain the return format and parameter usage. It only gives a vague idea of output (history and suggestions) and fails to describe how limit and agent_did affect 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. However, it does not mention any parameters (agent_did, limit) or their meanings. The agent receives no help in understanding what values to provide.

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 shows past OracleNet interactions and provides re-engagement suggestions. It distinguishes from siblings like quantum_status (current status) and quantum_ask (questioning), though it lacks an explicit verb like 'retrieve' or 'list'.

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

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

No guidance on when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusions, leaving the agent to infer 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, the description carries full burden. It discloses the use of Gemma 4 LLM, understanding of context/urgency/multi-step, and return structure. However, it does not mention potential failures, auth needs, rate limits, or side effects, leaving some 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 three sentences with no redundant fluff. It efficiently conveys the tool's role, how it works, and its outputs, making it easy to scan.

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

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

Given the absence of an output schema, the description adequately explains what the tool returns. It also positions the tool as the initial step in the OracleNet workflow ('front door'). Minor gap: no mention of error handling or fallback 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?

Both parameters are fully described in the schema (100% coverage). The description adds no new semantic information beyond what the schema provides, such as the details of the 'llm' parameter and its fast routing option. Baseline score applies.

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

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

The description clearly states it is an intent parser that accepts natural language and returns oracles, tools, workflow steps, and API calls. It distinguishes itself as 'the front door of OracleNet,' setting it apart from sibling tools like quantum_execute or quantum_ask.

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 this tool is the first step ('front door'), guiding the agent to use it for initial intent parsing. However, it does not explicitly state when not to use it or provide alternatives, though the context of siblings makes the usage clear.

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 provided. The description states outcomes (trust score, mesh visibility, tool access) but does not disclose side effects, persistence, authorization needs, or potential destructive actions. For a join operation, important behavioral traits are omitted.

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?

Extremely concise: two sentences, no wasted words. Essential information is front-loaded (the join action and key inputs). Every sentence earns its place.

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

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

Given the complexity of a join/registration tool, the description is minimal. It covers what is needed and what is gained, but lacks details on return format, restrictions (e.g., one-time use), and error cases. No output schema exists, so description should compensate.

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

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

Schema coverage is 100%, so baseline is 3. The description mentions 'Provide your agent card URL' but does not add significant semantic value beyond the schema's descriptions. No explanation of how parameters interact or the EITHER/OR constraint is reinforced.

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: joining OracleNet in one call, with specific outcomes like trust score, mesh visibility, and tool access. The verb 'join' and resource 'OracleNet' are explicit, but it lacks differentiation from sibling tools, though none seem to have a join 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 on when to use this tool vs alternatives. It does not mention prerequisites, when not to use it, or how it relates to other quantum_* tools. The description assumes the agent knows to provide an agent card URL, but no context on scoping or exclusion.

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, and the description does not disclose behavioral traits like read-only nature, rate limits, or if it requires authentication. It only states what is listed without additional 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 a single, concise sentence that efficiently communicates the tool's purpose without any extraneous words.

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

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

Given the simple nature of the tool with two optional parameters and a clear output description, it is fairly complete. However, missing pagination details or output format are minor 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 covers 100% of parameters with clear descriptions. The tool's description adds value by specifying what data (trust scores, grades, activity) is returned, which is not in 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 action (list) and the resource (OracleNet nodes) including specific attributes (trust scores, grades, activity). It distinguishes itself from sibling tools like quantum_status or quantum_scan by focusing on node 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?

No guidance is provided on when to use this tool versus alternatives, such as filtering by user or workspace. The description does not mention any 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 provided. The description does not indicate whether the tool is read-only, modifies data, or has side effects. Minimal behavioral context beyond labeling.

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, highly concise. It is efficient but could benefit from additional structure or front-loading.

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

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

With one optional parameter, no output schema, and no annotations, the description is insufficient. It does not clarify return format, expected behavior, or how the catalog is presented.

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 has 100% coverage with one optional parameter 'tool' described as 'Optional filter'. The description adds no extra meaning beyond the schema, so baseline 3 is appropriate.

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

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

The description 'OracleNet Offer Card: catalog with pricing, SLAs, payment methods' vaguely indicates the tool deals with offers but lacks a specific verb (e.g., get, list, search). It does not clearly distinguish from sibling tools like quantum_deal or quantum_catalog.

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

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

No guidance on when to use this tool versus alternatives. The description merely labels the tool's content without clarifying context or exclusion conditions.

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

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

No annotations are provided, so the description carries full burden. It mentions identity verification and trust recommendations, but does not disclose whether the tool mutates state, requires authentication, or has rate limits. The term 'pre-flight' implies read-only, but it is not explicit.

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

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

The description is concise with two sentences that front-load the purpose. It is clear and without wasted words, though a slightly more structured format could improve clarity.

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

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

Given the tool's simplicity (2 parameters, no output schema, no annotations), the description covers the basic purpose and actions. However, it lacks details on return values, prerequisites, and whether the tool is destructive, which would enhance completeness.

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

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

Schema description coverage is 100%, with each parameter described. The description adds context about what the tool does with the inputs (verifies identity, recommends escrow/direct), but does not detail how parameters influence the check. 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 is a pre-flight check for agent-to-agent interactions, verifying identity and trust, and recommending escrow or direct. This distinguishes it from siblings like quantum_trust_passport and quantum_deal.

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 indicates usage before agent-to-agent interaction, but lacks explicit when-not-to-use or alternative tools. Sibling names like quantum_trust_passport suggest related functionality, but no guidance is provided.

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

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

The description reveals that the tool 'Adjusts neural weights and reputation', which provides some behavioral context beyond a simple rating. However, no annotations exist, and the description does not mention other side effects, permissions, or reversibility. It is adequate but not comprehensive.

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, clear sentence that front-loads the key action and effects. It is concise without unnecessary words, though it could be slightly restructured to list parameters.

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

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

Given the tool has 4 parameters, no output schema, and low schema description coverage, the description omits important details like return value, parameter constraints, and side effects beyond reputation. It is incomplete for an agent to invoke 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?

The input schema has 4 parameters with 0% description coverage. The description only adds meaning for the 'rating' parameter (1-5 stars). The other parameters (rated_did, rater_did, feedback) are left unexplained, and the description does not compensate for the schema's lack of descriptions.

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

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

The description clearly states the verb 'rate' and the resource 'agent', and specifies the rating scale (1-5 stars). It provides a concise purpose. However, given the sibling tools like quantum_reputation and quantum_feedback, it could do more to differentiate.

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 'after interaction' as a usage context, but lacks when-not-to-use or alternatives. There is no guidance on prerequisites or exclusions, which is insufficient for the agent to choose this tool over similar ones.

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 must convey behavioral traits. It only says 'points you to who CAN help,' implying a read operation, but does not state side effects, authentication needs, or rate limits. For a tool with no annotations, 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 concise (two sentences) but could pack more information without increasing length. It achieves brevity but sacrifices clarity on parameters and return format.

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

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

Given the lack of output schema and annotations, the description should explain return values (format of referral) and constraints. It fails to do so, leaving ambiguity about what the tool returns.

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

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

Schema coverage is 0%, so the description should elaborate on each parameter. It mentions 'need' implicitly but does not explain 'current_oracle' (optional). The description adds minimal value beyond the parameter names.

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: 'Get referral to best oracle for your need.' It uses a specific verb-resource combination and differentiates from siblings like quantum_ask or quantum_offer by focusing on referral rather than direct interaction.

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. Given the many sibling tools with similar 'quantum_' prefixes, the description should at least hint at scenarios where a referral is needed over direct queries (quantum_ask) or offers (quantum_offer).

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 convey behavioral traits. It implies a read operation ('Query') and lists output format, which is helpful. However, it does not explicitly confirm idempotency, auth requirements, or rate limits, making it adequate but not thorough.

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 wasted words. It efficiently conveys the action, resource, and output format, earning its place.

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

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

The tool is simple, but without an output schema, the description must fully describe return values. It covers score, grade, and trust level, but omits details on trust level format and does not explain parameters. This makes it minimally complete for a basic query 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 0%, so the description must explain parameters. It mentions none of the two parameters (agent_did, period_days), leaving the agent without guidance on how to supply inputs correctly.

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 'Query' and identifies the resource as 'agent reputation', with clear output details (score 0-100, grade A+ to F, trust level). This distinguishes it from sibling tools like quantum_rate or quantum_status, which have different focuses.

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 (e.g., quantum_rate for ratings, quantum_trust_passport for trust details). The description only states what it does, not when it should be invoked, leaving the agent without decision 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 must disclose behavioral traits. It mentions it returns ranked candidates and considers trust, capabilities, availability, but does not state if it is read-only, requires authentication, or has side effects. The description is insufficient for full 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?

Two sentences, each essential. The first sentence states the primary purpose, the second adds key considerations. Front-loaded with the verb 'Find', making it immediately actionable.

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

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

No output schema exists, so the description should explain the return format. It only says 'Returns ranked candidates' without specifying ranking order, result count, or structure. Given the tool involves nested objects in input, more detail on output would be expected.

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

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

Schema coverage is 100%, so the description adds minimal value beyond the schema. It mentions considerations like trust and capabilities, which gives context to the constraints parameter, but does not explain the meaning of the task parameter beyond the schema's 'What you need'.

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 finds the best oracle for a task, considering trust, capabilities, and availability. It distinguishes itself from sibling tools like quantum_execute (which likely executes tasks) and quantum_ask (which may query oracles) by specifying it returns ranked candidates.

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

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

The description implicitly indicates use when you need to find an oracle, but provides no explicit guidance on when not to use it or how to choose between alternatives like quantum_scan or quantum_reputation. No exclusions or context are given.

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

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

No annotations provided, so description carries burden. It discloses scanning scope and output (signal layers present/weak/missing, and OracleNet additions) but does not mention side effects, permissions, or limitations (e.g., public data only, rate limits). Adequate but not thorough.

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

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

Single sentence packs significant detail (what it reads, mapping, checks, output) without fluff. Well-structured 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?

No output schema, but description explains return value (signal layers present/weak/missing and OracleNet additions). Lists many checked protocols. Sufficient for a scanning tool with one parameter.

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 has 100% coverage on the single parameter 'domain' with a clear description. Tool description does not add extra semantics beyond the schema 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?

Description clearly states verb 'Reads' and resource 'public machine-readable signals from any domain', mapping to OracleNet Signal Theory. Lists specific checks (well-known files, agent cards, etc.), distinguishing it from siblings like quantum_status or quantum_nodes.

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 among many siblings (e.g., quantum_status, quantum_reputation). No mention of limitations or when not to use.

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 exist, so description carries full burden. It discloses mutation (update trust score and revenue), but doesn't detail side effects, authorization needs, or error conditions.

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

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

Two sentences, no wasted words, action verb front-loaded. Highly 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?

With 4 parameters and no output schema or annotations, the description covers the basics but lacks details on error handling, trust score mechanics, or return values.

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

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

Schema has 100% coverage with parameter descriptions. The description adds context that the tool updates trust score and revenue, beyond what individual parameter descriptions provide.

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

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

Description clearly states 'Record a completed deal settlement' and specifies effects ('Updates trust score and revenue tracking'), distinguishing it from sibling tools like quantum_deal or quantum_execute.

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?

Implies usage for completed deals, but lacks explicit when-to-use or when-not-to-use guidance compared to alternatives. No exclusions or prerequisites 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 the full burden. It states 'live status' suggesting real-time data, but does not disclose caching behavior, update frequency, or any side effects. The behavioral transparency is 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, front-loaded sentence that efficiently conveys the tool's purpose and scope without unnecessary words.

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

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

Given the tool has no parameters and no output schema, the description provides a high-level purpose but lacks detail on the output format, freshness guarantees, or how the data is presented. It is adequate but 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?

The tool has zero parameters, and schema coverage is 100% (empty). The description adds value by explaining what data the tool returns, beyond the empty schema.

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

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

The description clearly states the tool provides live status of the entire OracleNet, listing specific components (nodes, attestations, routes, revenue, how to join). This distinguishes it from sibling tools like quantum_nodes (specific to nodes) or quantum_route (specific to routes).

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 is provided. The description implies it is for an overall overview, but does not mention when to use specific sibling tools or when not to use this tool.

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

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

With no annotations, the description carries full burden. It reveals the tool is push-based and uses webhooks, but lacks details on side effects (e.g., creating webhook registrations), permissions, or lifecycle. Basic transparency is present.

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

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

The description is very concise—two sentences with no fluff. It is front-loaded with the core purpose and uses bullet-like examples effectively.

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 5 parameters and no output schema, the description provides a high-level overview but omits details like response format, registration lifecycle, or limitations. Sufficient for basic understanding but not comprehensive.

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

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

Schema coverage is 100%, so parameters are already documented. The description does not add extra meaning beyond the schema. Baseline score of 3 applies.

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

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

The description clearly states the tool subscribes to OracleNet events via webhook, listing specific event types (server changes, capabilities, deals, trust scores). It distinguishes itself from sibling tools that likely perform other actions like querying or executing.

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 push notifications and event monitoring. While it doesn't explicitly name alternatives, the context is clear. It could be improved by stating when not to use it or mentioning 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?

Without annotations, the description must disclose behavioral traits. It states the output is a signed, portable credential, implying read-only behavior and a specific format. However, it does not mention side effects, authentication requirements, or error handling, which are important 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 a single sentence that concisely conveys the action, result, and purpose. It is front-loaded with the key information and contains no unnecessary words.

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

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

For a simple get operation with one parameter and no output schema, the description covers the essential information: what is returned (a Trust Passport) and what is needed (node_id). It could be slightly more complete by mentioning the response format, but the W3C Verifiable Credential reference provides a strong hint.

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

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

The schema already provides a clear description for the only parameter (node_id). The tool description does not add any additional meaning or context beyond what the schema offers. Since schema coverage is 100%, a baseline of 3 is appropriate.

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

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

The description clearly states the tool retrieves a signed, portable Trust Passport (W3C Verifiable Credential) that proves trust level in OracleNet. It specifies the action (Get), the resource (Trust Passport), and the purpose (proving trust level), making it distinct from sibling tools like quantum_reputation.

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. There is no mention of prerequisites, context, or when not to use it, leaving the agent to infer usage from the name alone.

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