AccordTrace

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

With no annotations provided, the description properly carries the behavioral burden. It discloses two meaningful non-obvious traits: the proof conditionally includes an Ed25519 issuer signature, and submitted content is not stored. It stops short of covering prerequisites or error behavior, but the disclosure is substantive.

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 tight sentences: the first establishes purpose, the second adds security and data-handling context. Every clause contributes information, and there is no filler or repetition.

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?

Together with the schema, the description lets an agent know it must pass data and may pass metadata, and it communicates that content is not stored. However, with no output schema and no annotations, the return shape, the meaning of metadata, and how issuer-signing configuration is determined remain unexplained, leaving meaningful ambiguity for 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 0%, so the description must compensate for parameter meaning. It does not name or explain 'data' or 'metadata' directly; 'submitted content' vaguely maps to data, and metadata semantics are entirely absent. This leaves the agent without enough information about the shape or intent of the inputs.

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 opens with a specific, actionable statement: 'Create an AccordTrace hash-bound service record.' This clearly identifies the tool as the creation-oriented sibling of accord_trace_get_proof and accord_trace_verify, and the mention of an Ed25519 issuer signature adds a distinguishing detail.

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 verb 'Create' implies this tool should be used when a hash-bound service record/proof is needed, which gives some directional guidance. However, the description does not explicitly state when to use it versus alternatives, and it does not mention when not to use it.

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

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

With no annotations provided, the description carries the burden of behavioral disclosure. It adds useful context by explicitly stating the operation is limited to 'public non-secret' metadata, signaling that no sensitive proof data will be exposed. It does not cover error behavior or not-found handling, but for a simple getter the key behavioral risk is addressed.

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 clear sentence with no filler. The verb and resource are front-loaded, and the meaningful qualifier 'public non-secret' earns its place by setting expectations about access scope.

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 with one string parameter and no output schema. The description states the resource type and access scope but omits details about return fields, error behavior, and how to obtain a valid proof ID. It is adequate but not fully complete.

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

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

Schema description coverage is 0%, so the description must compensate for the lack of parameter documentation. It only restates 'by proof ID,' which adds little beyond the parameter name proof_id. The description does not clarify the expected format, origin, or examples of the ID.

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 specifies the verb ('Retrieve'), the resource ('AccordTrace proof metadata'), and the lookup key ('by proof ID'). It differentiates the tool from siblings like accord_trace_create_proof and accord_trace_verify by focusing specifically on read-only metadata retrieval.

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 you need public, non-secret proof metadata and have a proof ID. However, it does not explicitly mention alternative tools or state when not to use this tool, so the guidance is 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?

No annotations are provided, so the description carries the behavioral burden. It discloses that the tool computes a canonical SHA-256 and does not create a proof, which suggests a pure read-only computation. However, it does not mention side effects, return format, input limitations, or whether data is transmitted/stored, so behavioral context is only partial.

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?

One tight sentence with no filler. The core action, input scope, and key exclusion are front-loaded, and every clause 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?

For a one-parameter hashing tool, the description covers the main input requirement and the key behavioral distinction. However, there is no output schema and the description does not state the return value (e.g., hex-encoded digest), which the agent would need to interpret the result. This keeps it from being fully complete.

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

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

Schema description coverage is 0% and the single 'data' parameter has no schema-level description. The description compensates partially by specifying 'JSON-compatible data', which clarifies the expected input type. However, it does not explain canonicalization rules or what shapes of JSON are accepted, so it does not fully cover the semantic gap.

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 names a specific operation ('Compute AccordTrace canonical SHA-256') and a clear input class ('JSON-compatible data'). The phrase 'without creating a proof' distinguishes it directly from the sibling accord_trace_create_proof, so an agent can tell them apart.

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

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

The description conveys when to use the tool: when only a canonical hash is needed, not a proof. It implicitly excludes proof-creation use cases via 'without creating a proof', but it does not explicitly name sibling tools or provide a conditional routing rule, leaving a small gap in guidance.

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

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

With no annotations provided, the description carries the behavioral burden and handles it well by explicitly stating 'Read-only' and 'does not enroll or attribute an agent.' This tells an agent the operation is side-effect free. It does not cover auth, rate limits, or failure modes, but those are minor for a parameterless read probe.

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 with no wasted words. The first sentence front-loads the precise data scope, and the second removes any side-effect ambiguity. Everything 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?

For a no-parameter, no-output-schema, no-annotation tool, this description provides enough scope detail for an agent to invoke it confidently. It is slightly light on return-value shape, but the enumerated content areas compensate well.

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

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

The tool has zero parameters and 100% schema coverage, so the empty schema fully documents the input contract. The description has no parameter semantics to add, and the baseline of 4 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 begins with a specific verb ('Read') and names the exact resource and scope: the live one-level AccordTrace Agent Affiliate Network policy, economics, anti-downline rules, and payout activation status. This makes it easy to distinguish from sibling capabilities tools like accord_trace_network_stats or accord_trace_passport_product_capabilities.

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?

It gives clear context for when to use the tool: whenever the agent needs current network policy, economics, anti-downline rules, or payout activation status. It also states an explicit negative ('does not enroll or attribute an agent'), but it does not name alternative sibling tools or conditions for choosing them.

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 behavioral disclosure burden. It does say 'Read' (implying non-mutating access) and 'live aggregate', which is useful, but it does not describe the output shape, whether it returns a snapshot, or any rate-limit, freshness, or error characteristics.

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. The enumeration of five distinct metric types is dense but each item adds meaningful information about what the tool reports.

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

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

For a zero-input read tool, the description is largely complete: it states the operation, scope, liveness, and the metric categories involved. It omits the exact response format, but since no output schema or parameters exist and the tool is simple, this is a minor gap rather than a blocking one.

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 the input schema is an empty object with 100% coverage, so there are no parameter semantics for the description to explain. The description still adds meaning by clarifying the categories of data the tool exposes, which earns the baseline of 4.

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 ('Read') with a concrete resource ('aggregate live affiliate-network states') and enumerates the distinct metrics it covers: generated invitations, attributions, qualified direct sales, earned commissions, and paid commissions. This is precise enough to separate it from siblings like accord_trace_network_capabilities or accord_trace_verify.

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 choose this tool over its siblings, when not to use it, or what prerequisites or context might apply. The read-only stats purpose is implied by the name and description, but the description never states selection criteria or alternative tools.

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

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

With no annotations provided, the description carries the full behavioral burden. It explicitly states 'Read-only' and adds a meaningful side-effect guarantee: 'it never initiates checkout.' More details about return format or errors could be added, but this is solid for a parameterless read 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?

Two short, purposeful sentences: the first states the action and resource, the second clarifies the critical read-only behavior. No filler or redundancy.

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

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

For a zero-parameter tool with no annotations and no output schema, the description covers the essentials: what is read, that it is live, and that it has no checkout side effect. It does not describe the output shape or expand on 'commercial readiness gates,' but these are minor omissions for such a simple 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 tool has zero parameters, so the baseline is 4. There are no parameter semantics to explain, and the description implicitly confirms that no arguments are required.

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 names a specific action ('Read'), a concrete resource ('live Agent Passport Certificate product'), and the exact data being read ('price and commercial readiness gates'). This distinguishes it clearly from sibling tools such as network_capabilities or proof operations.

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 gives clear context for when to call this tool: whenever the live Agent Passport Certificate product price or commercial readiness gates are needed. It does not explicitly name alternatives or state when not to use it, so it stops short of a 5.

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 present, the description carries the behavioral disclosure burden. It clearly states the operation has no side effects ('without reserving attribution or creating a sale') and that it only resolves active, public referral records. It does not detail error handling or response format, but for a simple lookup this is adequate.

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 entire description is a single, front-loaded sentence with no filler or redundancy. Every phrase earns its place by clarifying purpose, scope, and side effects.

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 only one parameter and no output schema, the description explains what the input represents, what the tool returns conceptually, and what it intentionally avoids doing. It is missing explicit usage guidance relative to siblings, but the provided context is largely 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?

The schema has 0% description coverage, so the description must compensate. It adds domain meaning by calling it a 'direct AccordTrace referral code', but it does not explain expected format, prefix, or example values beyond the schema's min/max length constraints.

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 names a specific verb ('Resolve'), a specific resource ('direct AccordTrace referral code'), and a precise outcome ('active public referral record and disclosure'). It distinguishes itself from sale/proof-creating operations by explicitly saying it does so 'without reserving attribution or creating a sale.'

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: this is for resolving a direct referral code to its public record when no attribution or sale should be created. It does not explicitly name alternative tools or provide a 'use when...' statement, but the exclusion is strong and practical.

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 conditional behavior (issuer signature verification only when present) and optional data/hash comparison. However, it does not state whether the operation is read-only, what the result format is, or how failures like missing proofs are handled, leaving meaningful behavioral gaps.

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

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

The description is a single, front-loaded sentence that covers the primary purpose and the optional/conditional behaviors with no filler or redundancy. Every phrase adds distinct information and the structure is easy to parse.

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

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

For a 3-parameter tool with no output schema and no annotations, the description is under-specified. It omits the return value or result shape, error behavior, and any explicit side-effect guarantee. It also leaves ambiguous whether data and hash may be supplied together or are mutually exclusive, which an agent would need to know to invoke the tool correctly.

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

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

Schema description coverage is 0%, so the description must compensate. It explains that data and hash are for optional comparison and that issuer signature verification is conditional, which adds meaning beyond the raw schema. Still, it does not clarify the expected format of hash, the type of data, or the exact role of proof_id beyond being the identifier of the proof.

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 'verify' with the resource 'AccordTrace recorded proof,' making the core action clear. It also distinguishes itself from siblings by mentioning optional data/hash comparison and issuer signature verification, which are not covered by get_proof, create_proof, or hash 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 used to verify proofs, but it gives no explicit guidance on when to use this tool versus alternates such as accord_trace_get_proof. The 'optionally' and 'when one is present' clauses describe parameter behavior, not tool selection criteria, so usage context is only partially 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 and explicitly discloses that the operation is read-only, never creates a wallet, and never moves funds. It also details the specific policy boundaries returned. It could mention error behavior or auth requirements, but the side-effect-free nature is clearly conveyed.

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 with no filler. The first sentence front-loads the resource and exact items being read; the second sentence reinforces safety by declaring read-only behavior. Every phrase 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?

For a no-parameter, read-only tool with no output schema, the description is complete. It tells the agent exactly what topics the response covers and explicitly rules out side effects. Nothing an agent needs to decide whether and how to call it is missing.

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

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

The tool has zero parameters, so the description cannot add parameter-level meaning. A baseline of 4 is appropriate because no parameter documentation is needed; the schema already confirms no required inputs.

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 'Read' and the specific resource: machine-facing Agent Wallet feature gates, Ed25519 signing contract, funded-balance policy, USDC representation, and no-credit boundary. This level of specificity distinguishes it from sibling capability tools like network_capabilities and passport_product_capabilities.

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: it is for reading wallet-specific capabilities, not creating proofs or querying network stats. However, it does not explicitly state when not to use it or name an alternative, so it stops short of a 5.

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