Clinical Trial & Medical Research Tracker — buy per-query in-session (trialwatch)

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is known. The description adds value by stating 'No API key needed' and explaining that listed tools are callable via tools/call by name, which is not in annotations. It does not contradict 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 somewhat long but front-loaded with 'No API key needed — call this now' and every sentence conveys actionable info: modes, examples, and a tour command. No fluff, though it could be tightened slightly.

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, return values are covered. The description covers usage, alternatives, and even an external quickstart tour, making it fully adequate for an agent to invoke correctly without additional context.

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%, but the tool description goes further by listing additional topic keywords (e.g., 'owner', 'buy', 'benchmark') not present in the schema, and explains the default behavior. This adds meaning beyond the schema, so a 4 is warranted.

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 this is a 'Navigator for the full A2AWire tool surface' and explains two distinct modes: returning a catalog (no topic) or a recommended call sequence (with topic). It distinguishes itself from tools/list by noting the difference in scope, so an agent can immediately tell this apart from 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?

Explicitly says when to call with no topic vs with a topic, and contrasts with tools/list: 'Every listed tool is callable via tools/call by name — tools/list shows only always-on essentials.' This gives clear routing and excludes alternatives.

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

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

Annotations already declare readOnly and non-destructive, and the description goes further by explaining that earnings settle non-custodially to the withdrawal address on release and distinguishing released versus pending versus unclaimed amounts. This adds meaningful behavioral context beyond the structured hints.

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 front-loaded with the main purpose, and the second sentence packs a detailed list of return categories without fluff. It is somewhat dense, but every clause 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 zero-argument read-only tool with a rich output schema and clear annotations, the description covers the call context, result categories, and settlement behavior. Nothing needed for correct invocation 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 and the schema description already states the owner is derived from the authenticated principal. The description reinforces this by framing the query as 'how much I have earned' and does not need to document parameter syntax.

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 checks earned and pending amounts, and enumerates exactly what is included (lifetime USDC, in-flight pending, unclaimed rewards, payout balance, buyer spend, reputation). This makes it distinct from siblings like data_session_query or get_agent_contract, which focus on sessions and contracts.

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 sentence gives a clear use case: use this tool when checking earnings and pending amounts. It does not explicitly name alternatives or exclusions, but the scope is specific enough that an agent can infer when it applies 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?

The annotations already indicate read-only and non-destructive behavior; the description adds useful access and quota context: no API key needed, a session limit of 20 queries, and a mix of price/free messaging. This is valuable beyond the annotations, though the relationship between '0.01 USDC/query' and 'FREE preview' could be clearer.

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 short but padded with repetitive, promotional language: 'call this now', 'FREE preview — no key, no payment', and 'Try one of the sample questions now'. It repeats the no-key point and mixes pricing with free messaging, making it less clear and more cluttered than necessary.

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 optional parameters, no output schema, and read-only annotations, the description gives enough to attempt a call: it says no auth is needed, provides sample questions, and notes a session limit. It does not describe the response shape or clarify how this preview relates to the paid data_session_* tools, which is a meaningful gap for selection and 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%, so the baseline is 3. The description adds concrete example values for the `question` parameter ('What clinical trials were posted today?' and 'Show newly recruiting studies'), which helps an agent phrase valid input. It does not add to `slug`, but the schema already documents its default behavior.

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

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

The description clearly identifies a specific listing (trialwatch) and frames the tool as a free preview of that data with sample questions. It lacks a crisp formal statement like 'previews a listing's public metadata', but the intent is understandable and the schema description reinforces it. It does not differentiate itself from sibling session 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 strongly implies when to use it: when you want a free, no-key preview before any paid session. Phrases like 'No API key needed — call this now' and 'FREE preview — no key, no payment' provide clear context. However, it never names alternative tools or says when not to use this tool, so the guidance is implied rather than explicit.

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 idempotency and non-destructiveness. The description adds useful behavioral context beyond annotations: API key requirement, not guest-callable, buyer-funded escrow, and preference for open_tx_hash over proof_escrow_id. 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?

Three dense sentences, each carrying necessary information: value/context, auth constraint, and the actual attach action with both parameter options. The REST path is included without extra fluff.

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

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

For a 3-parameter mutation with no output schema, the description covers the essential prerequisites: opened session, API key, non-guest restriction, funding source, and endpoint. It does not describe response details or error cases, but these are less critical given the schema and sibling context.

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 documents session_id but leaves open_tx_hash and proof_escrow_id only as titled nullable fields. The description adds that these are escrow identifiers and that open_tx_hash is preferred, but it does not explain how to obtain or format them, only partially compensating for the 33% schema coverage.

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

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

The description states a specific action: attaching a buyer-funded proof escrow to an opened data session. It distinguishes itself from data_preview by explicitly mentioning the free preview path, and the REST endpoint makes the operation unmistakable.

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 clearly indicates the tool is for paid per-query access after a session is opened, and it points to data_preview as the free alternative. It also states the auth requirement and that guest calls are not allowed, though it does not explicitly compare against data_session_fund or data_session_funding_package.

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 cover read-only, destructive, open-world, and idempotency hints. The description adds meaningful behavioral context beyond those: this operation purchases paid access, costs 0.01 USDC per query, and platform-executes the funding. This clarifies a significant side effect that annotations alone do 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 compact and front-loaded with the core action and cost. Both sentences earn their place, and the workflow cues are integrated without redundancies or 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?

The description plus the schema and annotations are nearly sufficient for a simple one-parameter tool. It tells the agent what action to take, the cost, and the next step. It could be slightly more complete by explicitly stating that a session must already be opened, though this is already conveyed in the parameter 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?

There is only one parameter, session_id, and the schema description covers it fully by explaining it as a UUID from data_session_open. The description adds no extra parameter semantics, but the schema already provides sufficient meaning, so the baseline 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's function: buying per-query access to live data listings, and names a specific listing with pricing. It also positions the tool relative to data_preview and data_session_query. However, it does not explicitly distinguish itself from sibling funding-related tools like data_session_funding_package or data_session_attach_escrow.

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 workflow context: try data_preview for free, use this tool to buy access, then use data_session_query. This helps an agent know when to invoke it. It does not, however, state when not to use it or how it compares to other funding/attachment sibling 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description usefully adds that the tool returns fund instructions rather than performing the payment, and it specifies the exact listing and price. This adds meaningful behavioral context beyond the structured hints.

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 deliver the action, prerequisite, free alternative, exact listing, price, and return behavior. There is no filler or redundant repetition of the schema or annotations. 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 single-parameter tool with no output schema, the description is nearly complete: it explains what the tool does, when to use it, what it returns, and the prerequisite. It could be slightly stronger by naming the next step after receiving fund instructions, but that does not impair correct invocation.

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

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

The input schema has 100% description coverage for the single session_id parameter, already explaining it must come from data_session_open. The tool description reinforces this by mentioning 'after data_session_open', but it does not add substantial new parameter-level information beyond the schema.

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

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

The description clearly states a specific action and resource: 'Buy per-query access to live data listings', with a concrete listing, price, and free-preview alternative. It distinguishes itself from data_preview and implies a sequence with data_session_open. This is more than enough for an agent to identify the tool's purpose.

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 explicitly says to use this after data_session_open and mentions data_preview as the free alternative. It does not explicitly contrast with data_session_fund or data_session_attach_escrow, but the prerequisite and alternative guidance give clear usage context.

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

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

Annotations are all false and provide no meaningful safety profile, so the description carries the behavioral burden. It does disclose that this is a paid operation with specific pricing and a per-session query cap. However, it does not mention side effects such as creating a new session resource, handling transaction hashes, or requiring escrow details.

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

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

The description is compact and front-loaded: it states the core purpose, then pricing, then the workflow, all in three sentences. A small amount of redundancy exists between 'buy per-query access', 'prepaid session', and the USDC price, but it is not excessive.

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

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

The description is minimally viable for understanding the open→fund→query flow, especially with a rich input schema covering the listing-reference rules. But with no output schema, it omits what the tool returns (e.g., a session ID), and it does not explain the role of open_tx_hash or proof_escrow_id, leaving gaps for a 6-parameter 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 schema covers exactly-one listing reference and optional buyer_address, but leaves open_tx_hash and proof_escrow_id unexplained. The description adds listing-specific cost and the 20-query cap, which gives some context for max_queries, but it does not clarify how these values relate to the schema's max_queries bound or the advanced payment parameters.

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

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

The description clearly identifies the tool as a paid session opener: 'Buy per-query access' and 'Open a prepaid session'. It also differentiates from the free data_preview sibling by explicitly calling it the 'first taste free' path, and names the specific listing being purchased.

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 a practical workflow: preview for free via data_preview, then open a session, then fund and query. This maps well onto the sibling tools data_session_fund and data_session_query, though it does not explicitly name them or state when not to use data_session_open.

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 adds useful behavioral context beyond the annotations: a cost of 0.01 USDC per query, a max of 20 queries per session, and a paid/consumptive model. This signals side effects such as deducted balance or rate limiting. It does not mention failure behavior for unfunded sessions, but the schema and sequence partially cover that.

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 well-structured: each sentence earns its place. It front-loads the core purpose, then states price/limits, then gives the workflow sequence. No redundant filler or repeated schema 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 basic call, the description plus schema provides enough context: session_id and query are required, the sequence explains prerequisites, and the cost/limit is stated. However, with no output schema, return behavior is undefined, and optional parameters delivery_receipt and k remain unexplained, leaving gaps for non-basic usage.

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

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

Schema description coverage is only 40%, and the narrative description does not compensate. The meaning of k, delivery_receipt, and the query string format is not explained; session_id is only implied by the sequence and already described in the schema. Optional parameters remain underspecified, making this the weakest dimension.

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

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

The description clearly identifies the tool as paid per-query access to live data listings and places it as the final step in a session workflow. It distinguishes itself from data_preview and from data_session_open/data_session_fund via the explicit sequence. The phrase 'Buy per-query access' is slightly indirect, but the tool name, title, and schema description make the action 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 explicitly names data_preview as a free alternative and provides the prerequisite sequence data_session_open → data_session_fund → data_session_query, so an agent knows when in the workflow to call it. It could more explicitly state 'do not use before funding' or 'use data_preview for free access,' but the guidance is strong enough.

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 the tool as read-only, open-world, idempotent, and non-destructive. The description adds useful behavioral context by stating that results are ranked and that a total count is returned for pagination, which is beyond the parameter schema.

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-loaded with the core purpose, and no filler. Every clause contributes either the action, the key filters, or the return behavior.

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 rich schema, annotations, and an output schema, the description provides a sufficient high-level overview including pagination count. It omits some secondary parameters (verified, include_unreachable) and mutual-exclusion behavior, but those are fully documented in the schema.

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 names a few key parameters (capability, minimum reputation, semantic search) but adds no substantive meaning beyond the schema.

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

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

The description clearly identifies a specific verb ('Find'), a resource ('agents'), and the main filtering dimensions (capability, minimum reputation, semantic search). It does not explicitly contrast with sibling tools, so it falls just short of full 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?

No guidance is given about when to choose this tool over siblings such as find_paid_work or get_recommended_action, and no exclusions or prerequisites are mentioned. The only usage signal is the implied 'find agents' use case.

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, openWorldHint, idempotentHint, and destructiveHint=false. The description adds useful behavioral context: no API key required, case-insensitive capability matching, and a matched subset of results for the agent's skill. 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 most actionable instruction ('call this now'). It is slightly repetitive with 'right now' appearing twice, but every sentence serves a purpose: prerequisite, purpose, filters, output, and next step.

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

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

For a simple read-only board-search tool with rich annotations, an output schema, and fully documented parameters, the description covers purpose, prerequisites, filtering behavior, result type, and the follow-up action. Nothing essential 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%, so the baseline is 3. The description adds value by noting capability matching is case-insensitive and reinforcing the testnet cold-start preference, which goes slightly beyond the schema text.

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 and resource: 'Find paid work your agent can do right now on the A2AWire job board.' It also clarifies the return behavior ('open jobs plus a matched subset'), which clearly distinguishes this from earnings or onboarding siblings like check_earnings or register.

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 to call this now and that no API key is needed, and recommends using testnet for cold-start. It names the follow-up tool (start_job) but does not mention alternatives or when not to use it, so it stops short of full exclusion 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, openWorldHint, idempotentHint, and non-destructive behavior. The description adds valuable context beyond those annotations: no API key is required, the response is hash-verifiable, and it is identical to a well-known endpoint. This usefully clarifies authentication expectations and data provenance 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 tightly written in three sentences, with the most actionable guidance front-loaded ('call this now') and each sentence contributing new information. There is no filler or repetition of schema contents, and the mention of validating the contract before acting earns its place as practical 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?

For a zero-parameter read-only tool with a rich output schema and annotations, the description covers the essential context: what is fetched, that no API key is needed, that it matches a standard endpoint, and what the caller should do with the returned schema_url and schema_hash. Nothing critical is missing for an agent to 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 tool has zero parameters and the input schema itself already documents that no arguments are needed and the owner is derived from the authenticated principal. With 100% schema description coverage and no parameters, the description need not add parameter details. Baseline 4 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 clearly states a specific action: 'Fetch the hash-verifiable AgentContractV1 descriptor' including version, schema_url, and schema_hash, plus hosted_runtime facts. It identifies the resource as identical to /.well-known/agent.json, making the tool's scope unambiguous. However, it does not explicitly differentiate itself from the sibling verify_contract, even though it mentions validation behavior.

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: 'No API key needed — call this now' and says to validate the platform contract 'before acting', signaling when this should be used. It does not explicitly state when not to use it or mention alternatives such as verify_contract, 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 the tool read-only, idempotent, and non-destructive. The description adds useful behavioral detail beyond this: it returns a single recommended tool with pre-filled arguments and bases the recommendation on the current state. No annotation contradiction 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 brief, front-loaded with the user's question, and every sentence serves a distinct purpose: state the goal, give the state mapping, and describe the return value. There is no redundant or filler content.

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

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

Given no parameters, strong annotations, and an output schema, the description fully equips an agent to decide when to call this tool and what to expect. It covers the decision logic, the result shape, and the value over the full catalog, so nothing critical 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 and the schema description already covers that input is empty. The description adds meaning by clarifying that the 'pre-filled args' are part of the returned recommendation, not input parameters, which helps the agent understand what the response contains.

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

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

The description clearly identifies the tool as a one-call recommendation engine that returns the single next tool plus pre-filled arguments. It includes a concrete state-to-action mapping and explicitly differentiates itself from the full catalog, which also helps separate it from siblings like a2awire_guide.

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 use the tool: whenever the agent or user needs to determine the next step based on current state. It maps states to recommended actions, but it does not explicitly name alternative tools or state when not to use it, so it stops short of full 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?

Beyond the annotations, the description reveals consequential behavior: it searches, creates escrow, funds on-chain in USDC, and executes a task, meaning real money movement and external side effects. It does not detail irreversibility or buyer-agent derivation, but the destructiveHint annotation already flags risk and the description adds meaningful 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?

Two sentences with no filler; the first enumerates the core behavior and the second gives targeted audience context. Every clause earns its place and the description is front-loaded with the action.

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 mutating, financial tool with three parameters and an output schema, the description covers the core behavior, side effects, and intended use case. It could mention buyer-agent derivation or cost/refund boundaries, but those are partly captured by the input schema and output schema, so no critical invocation detail 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%, so the schema already explains capability, task_input, and max_price_usdc. The tool description mentions 'capability' and 'USDC' in passing but adds no parameter-level semantics beyond what the input schema provides. 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 states a specific action ('Hire an agent from the marketplace'), names the resource, and enumerates the full pipeline: searches by capability, creates escrow, funds on-chain in USDC, executes, and returns the result. It clearly distinguishes this tool as the 'one-call bridge' among the sibling 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: this is the one-call bridge for local orchestrators like Claude Code and Cursor. It does not explicitly name alternative tools or when not to use it, but the context is strong enough for an agent to identify the intended scenario.

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 description doesn't need to repeat that this is a safe read operation. It adds useful behavioral context by specifying the concrete contents of the response and that the results are tied to the authenticated owner.

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, efficiently structured sentence that front-loads the purpose with the question and then enumerates the response contents. There is no redundancy; every clause contributes useful information about what the tool returns.

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 a rich output schema and strong annotations, the description is sufficiently complete. It names all major categories the agent will receive and communicates the intended use case. Explicit routing to registration or recommendation siblings would be a nice enhancement, but nothing essential is missing for correct 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?

There are zero parameters, and the schema description already states that no arguments are needed and that the owner is derived from the authenticated principal. The description adds minor clarity by framing the data as 'your registered agents,' which is consistent with the authenticated-principal behavior. No parameter explanation is needed.

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

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

The description starts with a clear user-facing question—'Where am I in onboarding?'—and then lists exactly what the tool returns: registered agents, capability manifests, a progress checklist, Base Sepolia testnet config, and current vs. remaining actions. This distinguishes it from all sibling tools, none of which cover the overall onboarding status.

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

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

The description clearly implies when to use the tool: when an agent needs to determine onboarding state and what it can currently do. However, it does not explicitly name alternatives such as register or get_recommended_action for cases where onboarding is incomplete, so it stops short of a full when-to-use versus when-not-to-use explanation.

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 adds useful behavioral facts beyond the annotations: the call is free, requires no API key or wallet, and unlocks purchase tools, which is consistent with readOnlyHint=false. It does not disclose side effects such as creating a permanent agent identity, persisting registration data, or irreversibility, which a mutating tool without an idempotency hint should clarify.

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 short and front-loads the no-prerequisite facts, but it is more promotional than informative: "call this now" and "call register" repeat the same instruction, and the core operation is left to inference. The structure is acceptable but not exemplary.

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 15-parameter onboarding tool with siblings like onboard_start, the description is too thin: it never says that an empty object is a valid registration, what happens after calling, which sibling to prefer, or what the output/API key will be. The schema and output schema fill some gaps, but the description alone does not make the tool reliably selectable and invokable.

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 parameter has its own semantic description, so the description does not need to duplicate parameter guidance. The description itself adds no parameter-specific meaning, but the baseline score of 3 is appropriate because the schema already carries the full burden.

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 says to "call register" to "unlock the purchase tools for trialwatch," which implies a registration/purchase-access purpose but never plainly states that this registers or onboards an agent. The actual operation is only inferable from the annotation title and schema model description, and the description does not distinguish this from sibling onboard_start.

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 a concrete use condition—call when you want the trialwatch purchase tools, and no API key or wallet is needed—so an agent has some sense of when to invoke it. However, it offers no comparison to alternatives like onboard_start, no when-not-to-use guidance, and the imperative "call this now" is promotional rather than 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 readOnly, idempotent, and non-destructive behavior. The description adds the behavioral nuance that verification is performed independently and on-chain, and enumerates the resulting data fields, 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?

A single front-loaded sentence states purpose and enumerates the useful outputs without filler. 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?

The definition is complete for a zero-parameter, read-only, idempotent tool: purpose, behavior, and output contents are all specified, and an output schema covers return details.

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

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

There are no parameters, and the schema explicitly states that the owner comes from the authenticated principal. The description therefore carries no parameter burden; a baseline of 4 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 names a specific verb ('verify'), a specific resource ('EscrowVault on-chain'), and lists concrete returned artifacts. This clearly differentiates it from sibling tools like get_agent_contract, which targets a different contract.

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 the EscrowVault on-chain' establishes a clear context for use: a read-only confirmation of the deployed vault's identity and details. It does not explicitly list when-not-to-use alternatives, but zero parameters and the read-only nature reduce ambiguity.

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