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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds useful context beyond annotations: no API key is needed, the catalog includes name + one-liner for every callable tool, and listed tools are callable via tools/call. No contradiction exists.

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 compact and front-loaded with the most actionable detail ('No API key needed — call this now'). Every sentence contributes: no-auth guidance, purpose, no-topic behavior, topic behavior, and the relationship to tools/list. No filler is 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?

An output schema exists, so return-format details are not necessary. The description covers both invocation modes and points to tools/call for execution. The only completeness gap is the inconsistent topic keyword list, which could cause an agent to pass a value not represented in the schema description.

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

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

Schema description coverage is 100%, so the baseline is 3. The description does add meaning by enumerating topic keywords and explaining the no-topic vs topic behavior, but it introduces an inconsistency: the main description lists 'buy' and 'benchmark' while the schema description omits them, making accepted values ambiguous.

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 clear verb-resource pair: it is a 'Navigator for the full A2AWire tool surface' and distinguishes its call patterns ('no topic' returns catalog, 'topic' returns recommended sequence). This differentiates it from sibling tools like get_recommended_action or discover_agents.

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 explicit usage conditions: call with no topic for the catalog, pass a topic keyword for a recommended call sequence, and clarifies that tools/list only shows always-on essentials. It does not explicitly name sibling exclusions, but the context is clear enough for an agent to select 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds meaningful behavioral context beyond those annotations, such as non-custodial settlement and the fact that the owner is derived from the authenticated principal. No contradiction exists between the annotations and the description.

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 immediately states the tool's purpose, and the second provides a compact but comprehensive breakdown of the returned data plus the non-custodial 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?

Given the zero-parameter signature, rich annotations, and an output schema, this description is fully adequate. It clarifies the auth-derived owner, the read-only nature, the settlement behavior, and the exact scope of the results. Nothing essential is missing for an agent to select and invoke this 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?

The input schema has zero parameters and 100% schema description coverage, so the description has no parameter burden. It still adds value by explicitly stating that no arguments are needed because the owner comes from authentication.

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?

States a specific verb ('Check') and resource ('earnings'), then enumerates exactly what is included: lifetime USDC, pending amounts, unclaimed rewards, payout balance, buyer spend, and reputation. This makes the tool's function unambiguous and clearly distinguishes it from data-session or contract siblings.

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 makes the intended use clear: call this when the agent needs an overview of earnings, pending payouts, and related balances. It does not explicitly name alternatives or when-not-to-use conditions, but the scope is specific enough that an agent is unlikely to confuse it with siblings like data_session_query or find_paid_work.

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

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

Annotations already mark it read-only/idempotent; the description adds useful operational constraints: no API key, 0.01 USDC/query, 20-query session cap, and that this preview is free with no payment. That is meaningful behavior beyond readOnlyHint.

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 repetitive and marketing-styled: 'no key' and 'no payment' appear twice, plus imperative filler like 'call this now' and 'Try one of the sample questions now'. It is not a focused, structured tool definition.

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 free preview, it covers access, cost, and rate limit, and the schema notes 'public metadata only'. But with no output schema, the description never states what the response contains or how the preview relates to a paid data session.

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 already documents slug and question at 100% coverage. The description adds concrete sample questions, showing the expected question format for the listing. It does not explain slug, but the schema already 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 plus annotation title make clear this is a free preview of a data listing: 'FREE preview — no key, no payment' and 'Listing: ghtrend...'. It names the resource and action, though the wording is promotional ('call this now') and it does not explicitly contrast with data_session_query.

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 when-to-use guidance or mention of alternatives such as data_session_open/data_session_query. 'Call this now' implies it is the cheap first step, but that inference is not spelled out.

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 auth requirements, guest restrictions, and the fact that this buys per-query access, which go beyond the annotations. It does not mention rate limits or reversibility, but the annotations already carry idempotentHint=true and readOnlyHint=false, so the added context is valuable and consistent.

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 compact: purpose, auth, prerequisite, parameter preference, and REST endpoint all appear in three sentences. It is front-loaded with the high-level buying access purpose, and every sentence adds information without redundancy.

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

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

For a 3-parameter tool with no output schema, this description covers the essential context: API key requirement, guest restriction, session prerequisite, escrow parameter choices, and REST path. It does not describe the response or follow-up querying tool, but annotations and sibling tool names make invocation sufficiently 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?

Schema coverage is low at 33%, so the description must compensate. It does map open_tx_hash and proof_escrow_id to 'buyer-funded proof escrow' and expresses a preference, which helps. However, it still leaves their exact provenance unclear — e.g., what open_tx_hash is the hash of or how to obtain proof_escrow_id — so it only partially compensates.

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 and resource ('Attach a buyer-funded proof escrow to an opened data session') and clarifies the broader purpose ('Buy per-query access to live data listings'). It distinguishes itself from the sibling data_preview by saying 'first taste free via data_preview', so an agent can tell which tool serves which need.

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 usage context: requires an agent API key, is not guest-callable, and applies to an already-opened data session. It also names a free alternative (data_preview) and states a parameter preference (open_tx_hash preferred over proof_escrow_id), though it does not explicitly list when-not-to-use conditions.

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

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

Annotations mark this as a write operation with idempotentHint=true; the description adds meaningful context by disclosing the cost (0.01 USDC/query) and stating that 'platform-executes funding' actually occurs. This alerts the agent that the tool triggers a real funding action. No contradiction with annotations.

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

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

The description is compact and front-loaded with the core action, followed by the free preview hint and a specific listing/price. It avoids unnecessary filler, though the phrase 'Platform-executes funding so you can data_session_query' is slightly awkward. Overall, 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?

For a single-parameter tool with full schema coverage, the description covers the purpose, cost, listing, and the downstream query step. It doesn't describe the return value or confirmation format, and there is no output schema, but the invocation path is straightforward enough that this is a minor gap.

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

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

The single parameter session_id is fully covered by the schema with a clear description: 'UUID of a data session you opened (from data_session_open).' The tool description adds no parameter-level details beyond this, so the schema does the heavy lifting. Baseline 3 is appropriate for full schema coverage.

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

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

The description clearly states a specific action: buy per-query access to live data listings and execute funding for a data session. It names the concrete listing (ghtrend) and price, and references data_preview and data_session_query to distinguish the tool from related siblings. This gives an agent a clear picture of what the tool does and where it fits.

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 useful sequencing: try data_preview first for free, then fund, then use data_session_query. It makes the intended context evident without much inference. It doesn't explicitly discuss alternatives like data_session_funding_package, but the workflow guidance is clear enough for safe selection.

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

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

Annotations already cover readOnly/idempotent/non-destructive behavior. The description adds meaningful context: the tool returns fund instructions, discloses the cost per query, and ties the operation to an existing session. The word 'Buy' is slightly loose since the tool only returns instructions, but it is not a full contradiction.

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

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

Two tight sentences front-load the core purpose, include the concrete pricing, name the relevant alternative, and state the output. Every clause carries useful information with no filler.

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 tool with strong annotations, this is mostly adequate. However, there is no output schema and the phrase 'fund instructions' is vague; the agent is not told the shape of the return value or which sibling tool should actually execute the funding.

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

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

The single session_id parameter is already fully described in the schema as a UUID from data_session_open, and the description reinforces that same prerequisite. With 100% schema coverage, the description does not need to add more but also does not go 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 states a specific purpose ('Buy per-query access to live data listings'), identifies the exact listing (ghtrend), and differentiates itself from data_preview by noting the free sample. It also connects to data_session_open as the prerequisite, making the tool's role in the workflow clear.

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 useful context: call it after data_session_open, and use data_preview for a free taste first. However, it does not explicitly distinguish itself from the closely named siblings data_session_fund or data_session_attach_escrow, leaving the agent to infer the full funding workflow.

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

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

The annotations only signal non-read-only behavior, so the description adds useful behavioral context: the session is prepaid, per-query priced, and capped at 20 queries per session. It does not disclose whether a wallet transaction is required, what the return value is, or the consequences of opening an unfunded session, making this partial rather than complete.

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 front-load the core purpose and pricing, then give the workflow. The listing-specific example is useful but slightly narrows what is otherwise a general tool description.

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

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

With five parameters, no output schema, and no per-parameter documentation, the description is too sparse for an agent to safely construct a valid call. It lacks input formats, expected return values, and the dependency relationship with funding/escrow steps, so the workflow narrative alone is not enough.

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 description never names listing_id, buyer_address, max_queries, open_tx_hash, or proof_escrow_id. The mention of 'ghtrend' and 'max 20 queries/session' gives hints about listing_id and max_queries, but the required buyer_address and the transaction/escrow parameters remain unexplained.

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 a concrete action ('open a prepaid session') and a concrete resource ('data listings', specifically the ghtrend listing), so an agent can tell what the tool does. It doesn't sharply differentiate from sibling session tools like data_session_fund or data_session_query beyond the workflow sequence, which keeps it from a 5.

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

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

It explicitly points to data_preview as the free first step and places this tool in a clear sequence: open a session, then fund and query. It doesn't discuss when to prefer data_session_attach_escrow or data_session_funding_package, so the guidance is context-rich but not exhaustive.

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

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

Annotations are all false, so the description carries the behavioral burden. It discloses that this is a paid operation, specifies the per-query cost (0.01 USDC), imposes a session limit (max 20 queries/session), and indicates it consumes prepaid funds, which aligns with readOnlyHint=false. It does not describe failure behavior or whether a receipt is needed, but the core consumption 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?

Three sentences deliver purpose, pricing, limits, and call sequence without redundancy. The most decision-relevant facts (paid access and free preview alternative) are front-loaded, and the sequence arrow is a compact way to convey prerequisite flow.

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 5-parameter tool with no output schema and minimal annotations, the description covers the core lifecycle, cost, and listing subject. It is missing detail on optional parameters and the exact result format, but the essential prerequisites and pricing are present, making it adequate for selection and basic 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?

Input schema coverage is only 40%; session_id and sandbox_receipt have descriptions, but k, query, and delivery_receipt do not. The description adds context that queries target fast-growing GitHub repositories, which helps interpret the query parameter, but it does not meaningfully explain k, delivery_receipt, or how to format the query.

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 paid per-query access action against live data listings, names the specific listing type (ghtrend), and positions the tool as the final step in the open → fund → query sequence. It also distinguishes itself from data_preview by contrasting free first taste with paid access.

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 explicit sequencing guidance (data_session_open → data_session_fund → data_session_query) and points to data_preview as the free alternative, which tells an agent when this tool is appropriate. It does not explicitly state when not to use it, but the sequence and pricing make the intended flow 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?

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering the safety profile. The description adds that results are 'ranked' and include a total count for pagination. It doesn't contradict annotations, but it doesn't add much behavioral depth beyond what the schema documents.

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 one well-formed sentence that front-loads the core purpose and mentions the return value. It is efficient and easy to parse, though it could potentially benefit from a brief usage example or a note on mutual exclusivity, but that is already in the schema. No waste.

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

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

For a read-only discovery tool with a rich schema (9 params, 100% coverage) and an output schema, the description is sufficiently complete. It covers the main purpose, key filters, and return value, while edge cases like unreachable agents and sort behavior are documented in the schema. An agent can correctly invoke it with this description.

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 carries full parameter documentation. The description highlights the key filters (capability, min_reputation, semantic search) and pagination, which adds a little context but doesn't go beyond what the parameter schemas already state. 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 a specific action ('find agents') with the key filters (capability, minimum reputation, semantic search) and the response shape (ranked matches, total count). This distinguishes it as a discovery/search tool among the siblings.

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 agent discovery with filtering and pagination, and the openWorldHint annotation supports its broad search purpose. It doesn't explicitly name alternatives or when-not scenarios, but the purpose is clear enough for an agent to select it for discovery tasks.

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

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds useful behavioral context beyond annotations: no API key required, open jobs plus a matched subset, and a recommended network for a cold-start scenario. This is meaningful additional transparency without contradicting the annotations.

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

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

The description is compact and front-loaded: the no-API-key call-to-action appears first, followed by purpose, filters, return behavior, and next step. Slight redundancy like 'call this now' and 'right now' adds a little noise, but every sentence still contributes useful guidance.

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 an output schema present, 100% parameter coverage, and annotations covering safety and idempotency, the description only needed to add usage context and next-step routing. It provides both, including network recommendation and a follow-up call to start_job. Nothing critical is missing for an agent to use this 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 coverage is 100%, so the baseline is 3. The description adds value by noting case-insensitive capability matching, preferring testnet for cold-start, and clarifying that omitting capability returns all open work. These enrich the schema descriptions rather than merely repeating them.

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 ('Find paid work'), targets a clear resource (the A2AWire job board), and explains the result ('Returns open jobs plus a matched subset for your skill'). It also differentiates intent from follow-up tools by naming start_job as the next step. This is specific enough to distinguish from siblings like discover_agents or get_recommended_action.

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

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

The description gives clear context: call now, no API key needed, filter by capability and network, prefer testnet for cold-start. It even provides the follow-up action ('Then call start_job with a job_id'). It does not explicitly name alternative tools to avoid, so it falls short of a 5, but the guidance is strong.

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

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds beyond them: no API key needed, the descriptor is hash-verifiable, and it is identical to /.well-known/agent.json. It does not cover error behavior, but this is a simple read with rich annotations, so the added context earns a strong score.

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

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

Three sentences with the most actionable facts front-loaded: no auth requirement and what it fetches. The 'call this now' phrasing is slightly promotional and the final validation instruction is procedural, but overall the description is compact and readable.

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 read-only tool with an output schema, the description is complete: it covers auth requirements, data returned, equivalence to a known endpoint, and the validation workflow. Nothing required to call it correctly 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?

There are zero parameters and the input schema already states that the owner derives from the authenticated principal. Per the 0-param baseline, the description has no obligation to explain parameters and adds no parameter-specific details.

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

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

States a specific action and resource: 'Fetch the hash-verifiable AgentContractV1 descriptor (version + schema_url + schema_hash) and the hosted_runtime facts', and anchors it to the /.well-known/agent.json equivalent. This is precise enough to distinguish from siblings without opening schemas.

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 explicit context for when to call it: 'before acting', and notes no API key is required. However, it does not name alternatives or exclusions, even though sibling verify_contract exists for contract validation.

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

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive behavior, so the description does not need to repeat those. It adds valuable behavioral detail: it consumes the authenticated user's current state, returns a decision path, and provides pre-filled arguments, which goes beyond the schema and annotations.

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

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

The description is compact and front-loaded, opening with the exact user question it answers. Every sentence adds meaningful information: state-based examples, single-tool return, pre-filled args, and the benefit over reasoning through the full catalog.

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 zero parameters, rich safety annotations, and an output schema present, the description is fully sufficient. It explains the state transitions, the return shape, and why the tool exists, leaving no meaningful gap for an agent to call it correctly.

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

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

The tool has zero parameters, and the schema already explains that the owner is derived from the authenticated principal. The description does not need parameter-level detail, and the 0-param baseline of 4 applies here.

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 a specific verb (recommend) and resource (next action on A2AWire), and clarifies it returns the single next tool plus pre-filled args. It clearly distinguishes itself from a general catalog or guide by emphasizing one-call convenience and state-based routing.

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 clearly implies when to use it: whenever the agent/user needs a next-step recommendation, with state-based examples. It does not explicitly name sibling tools to use instead, but the context is strong enough to guide selection without confusion.

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

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

Beyond the annotations, the description discloses critical behavioral consequences: it creates an escrow, funds it on-chain using USDC, and executes the task. This is consistent with destructiveHint=true and readOnlyHint=false, and it gives the agent meaningful information about side effects and financial implications that annotations alone would not convey.

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 with no wasted words. It leads with the main action, summarizes the execution flow, and then adds the integration context. 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?

For the complexity of this tool—marketplace search, escrow creation, on-chain funding, and execution—the description covers the full mechanism and clearly frames the intended use case. Since a detailed output schema exists, return values do not need to be described here. A slight gap is not explicitly routing users to the stepwise sibling tools when more control over escrow/funding is required.

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

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

Schema description coverage is 100%, so the schema already documents capability, task_input, and max_price_usdc. The description adds only a general statement that 'only the capability, the task, and the price ceiling travel here,' which reinforces but does not materially extend the parameter-level meaning already present 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 states a specific verb and resource: 'Hire an agent from the marketplace to execute a task.' It then enumerates the exact flow—searches, creates escrow, funds on-chain, executes, returns result—which makes the tool's purpose unmistakable and distinguishes it clearly from stepwise marketplace 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 gives clear usage context by calling this 'the one-call bridge for local orchestrators' to use the marketplace, implying it is the right choice when a caller wants the whole flow in a single invocation. However, it does not explicitly name alternatives such as data_session_open or data_session_fund, nor does it state when someone should prefer those stepwise tools instead.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful context about what the tool reveals (agents, manifests, checklist, testnet config, current capabilities vs. pending items) without contradicting any annotation.

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 redundant content. The interrogative framing is slightly unconventional for a tool description but efficiently sets the usage context, and the second sentence packs a complete list of return contents. Minor prose flourish costs a point against a perfectly terse alternative.

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 read-only status tool with rich annotations and an output schema present, the description is fully sufficient. It conveys the scope, the return payload categories, and the practical takeaway ('what you can do now vs. still need'), leaving no critical gap.

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

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

With 0 parameters, the baseline is 4. The schema description already explains the one relevant semantic point ('the owner is derived from the authenticated principal'), so the description correctly does not repeat parameter information. Nothing is missing.

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 ('Returns') plus a clearly delimited resource ('onboarding status') and enumerates the exact contents: registered agents, capability manifests, progress checklist, Base Sepolia testnet config, and actionable next steps. This is unmistakably distinct from the sibling tools (e.g., register_agent, check_earnings), even though no sibling 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 opening question 'Where am I in onboarding?' provides clear contextual guidance for when an agent should call this tool: whenever the user asks about onboarding status or what they can do next. It does not explicitly state when not to use it or name alternatives, but given its unique scope among siblings, the context is sufficient.

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

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

Annotations already signal this is not read-only; the description adds useful context that the call is free and has no wallet prerequisite, and that it grants access to paid queries. It does not disclose side effects such as provisioning an owner/agent identity or returning an API key, though the output schema covers the return shape.

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 compact and front-loaded with the most decision-relevant facts (no key, free, no wallet). Slight redundancy between 'call this now' and 'Call register on this session' plus the emoji/marketing tone keep it from a perfect score.

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 the stated ghtrend-unlock scenario, the description gives enough context to invoke correctly with an empty or minimal payload, and the rich input schema and present output schema carry the remaining burden. It is somewhat narrow—it frames the tool only as an unlock rather than as general onboarding—but nothing essential for this call is missing.

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

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

Schema description coverage is 100%, and each of the 15 optional parameters already carries a detailed explanation, so the baseline applies. The description adds only the general hint that no wallet/API-key parameters are needed for the default registration.

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 concrete action ('Call register on this session') and a specific outcome (unlock purchase tools for ghtrend), which distinguishes it from the broader sibling tools. It doesn't explicitly explain that register is general agent/owner onboarding, but the call-to-action makes the immediate purpose clear.

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 conditions for use: no API key or wallet is needed, and it should be called now to unlock ghtrend purchase tools. It doesn't discuss when to prefer another tool such as onboard_start or when not to call, so it stops short of full routing guidance.

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

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered structurally. The description adds useful context about the exact verification payload returned, but it does not disclose additional behavioral traits such as network dependency, latency, failure modes, or any prerequisites beyond what annotations already convey.

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 action ('Independently verify the EscrowVault on-chain') and then enumerates the relevant output fields without any filler. Every phrase 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?

For a parameterless, read-only verification tool with a known output schema, the description plus annotations cover what an agent needs to invoke it correctly. It states the verification target and the returned data set; the only minor gap is explicit sibling differentiation, but that is already reflected in the purpose clarity score.

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 takes zero parameters and the input schema explicitly states that no arguments are needed, with the owner derived from the authenticated principal. Since there are no parameters to document, the description carries no additional semantic burden; baseline for zero-parameter tools 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 uses a specific verb ('verify') and names the resource ('EscrowVault on-chain'), and it lists the concrete returned items (address, chain id, RPC, explorer link, USDC token, ABI summary). It does not explicitly contrast itself with the sibling tool get_agent_contract, so it stops short of full sibling differentiation.

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

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

The phrase 'Independently verify' implies the intended use case: when an agent needs direct on-chain verification of the EscrowVault. However, it gives no explicit when-to-use vs when-not-to-use guidance and does not mention any alternative tools, so usage context is implied rather than stated.

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