Product Hunt Launches — new & upcoming products (producthuntwatch)

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

Annotations already declare the tool read-only, idempotent, and non-destructive, so the description's key value is its extra context: no API key required, the output is a catalog or recommended sequence, and listed tools are invoked via tools/call while tools/list only shows always-on essentials. This goes beyond the annotations without contradicting them.

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 fact: no API key needed, call now. Every sentence contributes useful guidance, though the pipe-dense topic list partially duplicates the schema and makes the middle slightly harder to scan.

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

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

For a zero-required-parameter, read-only guide with an output schema, the description is complete. It covers both call modes, what each returns, the available topic values, and the relationship to tools/call and tools/list, so an agent has everything needed to invoke 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 single optional topic parameter already has 100% schema description coverage, so the baseline is 3. The description adds value by listing additional topic keywords (buy, benchmark) not present in the schema description and clearly mapping topic presence/absence to different return 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 the tool as a navigator for the full A2AWire tool surface and distinguishes the two call modes: no topic returns a categorized catalog, while a topic returns a recommended call sequence. This makes it obviously distinct from operational sibling tools like hire_and_execute or check_earnings.

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 tells agents to call with no topic for the catalog and with a specific topic for a call sequence. It also provides practical context by stating no API key is needed and contrasts the guide with tools/list, though it does not name alternative tools to prefer for specific 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. The description adds meaningful behavioral context by stating earnings settle non-custodially to the withdrawal address and that the owner is derived from the authenticated principal. It reinforces the read-only nature without contradicting 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 dense but well-organized: it states the core purpose in the first sentence, then itemizes the returned categories, and ends with a relevant non-custodial settlement note. It is longer than minimal, but every sentence 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?

With no output schema and no parameters, the description carries the burden of explaining what the agent will receive. It does so thoroughly by listing lifetime earned USDC, pending amounts, unclaimed claim-later rewards, payout-address balance, buyer spend summary, and first-agent reputation. Nothing essential is missing for a successful call.

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

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

The tool has zero parameters and schema coverage is 100%, so the baseline is 4. The description adds value by clarifying that the context is the authenticated principal's earnings and specifying what the returned data represents, even though no parameters need explanation.

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

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

The description opens with a direct verb and resource ('Check how much I have earned and what is pending') and then enumerates the exact data categories returned, making the tool's purpose unmistakable. It clearly distinguishes itself as a read-only earnings overview tool among the sibling 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 makes it clear this tool is for checking earnings and pending amounts, which is sufficient context for the typical caller. It does not explicitly name alternative tools or state when not to use it, but the zero-parameter design and specific output scope reduce ambiguity.

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, so the bar for additional disclosure is lower. The description adds useful context: no API key, public metadata only, guest-callable, and a 20-query/session cap. However, the 'Price 0.01 USDC/query' line is ambiguous and could be misread as a cost of this tool, conflicting with the 'FREE preview' claim.

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 most important fact is front-loaded ('No API key needed — call this now'), but the description repeats 'free/no key/no payment' multiple times and ends with filler like 'Try one of the sample questions now.' The promotional tone and redundancy keep it from being appropriately concise.

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

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

Given the low complexity, zero required parameters, and rich annotations, the essential context is present: auth-free, free, read-only, specific listing, and example questions. Missing are a clear statement of what the response returns and resolution of the 0.01 USDC pricing ambiguity. It is adequate but not fully complete.

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

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

Both parameters are fully documented in the schema (100% coverage), so the baseline is 3 even without description support. The sample questions add concrete examples for the question parameter, and the schema already explains slug defaulting. The description does not materially expand parameter semantics beyond those examples.

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 this as a free, no-key preview of the producthuntwatch listing and gives sample questions to try. It distinguishes itself from paid/session-based siblings by emphasizing 'FREE preview — no key, no payment.' It lacks an explicit 'preview a data listing' verb phrase, but the schema description 'Free, guest-callable taste of a listing' reinforces the 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 'No API key needed — call this now' and 'FREE preview — no key, no payment,' making it clear this is the free entry point. It implies use before funded session tools like data_session_query, but it never names alternatives or states when not to use it. The context is strong, but exclusion guidance is missing.

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 value beyond the annotations by disclosing the API-key requirement, guest-call restriction, REST endpoint, and the preference for open_tx_hash over proof_escrow_id. The annotations already provide idempotentHint and destructiveHint, and the description does not contradict them.

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: purpose, free-trial alternative, auth requirement, parameter preference, guest restriction, and REST endpoint each earn their place. There is no redundant filler, and an agent can extract the key info quickly.

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

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

The description covers the essential invocation context: which session to target, which escrow identifier to pass, how to authenticate, who is allowed to call, and the HTTP endpoint. Missing response or error details are less critical for selection and invocation, especially since there is no output schema to reconcile.

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 33%, but the description compensates by naming the escrow identifier options and their preference: open_tx_hash preferred, or proof_escrow_id. It also clarifies that the escrow must be buyer-funded. It does not fully explain how each parameter is obtained or how they interact, but the guidance is sufficient for basic invocation.

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

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

The description clearly states a specific verb and resource: attaching a buyer-funded proof escrow to an opened data session to buy per-query access. It references data_preview as the free-trial path, which helps differentiate it from one sibling. However, it does not explicitly distinguish itself from sibling tools like data_session_fund or data_session_funding_package, so it stops short of full disambiguation.

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 concrete preconditions: an opened data session, an agent API key via Bearer or X-API-Key, and a buyer-funded proof escrow. It also explicitly states the tool is not guest-callable. This is actionable guidance, though it does not spell out when to prefer a sibling tool like data_session_fund or data_session_funding_package 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?

The description discloses that this operation actually 'platform-executes funding' and specifies the real cost ('0.01 USDC/query'), going beyond the generic annotations. Since annotations already indicate idempotent and non-destructive behavior, the added pricing and execution semantics are meaningful. It does not cover balance/precondition failures, but the core behavioral disclosure 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 compact—two sentences—and front-loads the value proposition and the workflow. The concrete listing example and unit price earn their place by illustrating cost and offering. Minor jargon like 'platform-executes funding' and the singular listing example slightly reduce clarity but do not bloat the text.

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 funding tool with no output schema, the description plus schema covers the prerequisite session_id and the general outcome (query access). However, with sibling tools like data_session_funding_package and data_session_attach_escrow present, the description does not clarify when this specific funding route is appropriate. The agent may still be unsure about selection among the data_session_* family.

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 the single session_id parameter is already documented as the UUID from data_session_open. The tool description adds no additional parameter-level detail, so it provides no value beyond the schema. 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?

Description opens with a concrete action: 'Buy per-query access to live data listings,' which names a verb, resource, and cost model. It also positions itself between data_preview and data_session_query ('first taste free via data_preview... so you can data_session_query'), making its role readily identifiable. It does not explicitly say 'fund a data session' and does not distinguish from the sibling data_session_funding_package.

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 the intended flow: use data_preview for a free taste, then this tool to buy paid per-query access, then data_session_query to use it. It names two adjacent tools and their sequencing. It does not explain when to choose data_session_fund over data_session_funding_package or data_session_attach_escrow, so exclusions are incomplete.

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 flag the operation as read-only, idempotent, and non-destructive, so the description only needs to add context. It discloses the return behavior (fund instructions), the prerequisite, the listing cadence, and the per-query price. The word 'Buy' could imply a side effect, but 'Returns fund instructions' keeps it consistent with 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?

Two packed sentences with no filler; the core action, prerequisite, alternative, price, and output are all present. It loses a point because 'Buy per-query access' as the opening phrase is slightly ambiguous given the tool only returns instructions.

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 and a schema-described session_id, the description is nearly complete: it states the prerequisite, output type, price, and free alternative. The remaining gap is not explaining the relationship or sequence with data_session_fund or data_session_attach_escrow, which matters in this sibling cluster.

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 100% schema description coverage, the schema already documents session_id as the UUID from data_session_open. The tool description reinforces the prerequisite but adds no new parameter-level meaning beyond the schema, so the baseline of 3 is appropriate.

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

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

The description states a specific action and resource: buying per-query access for a named listing (producthuntwatch) and returning fund instructions. It also points to data_preview as the free alternative, but it does not clearly distinguish this tool from sibling data_session_fund or data_session_attach_escrow, so it is not fully differentiated.

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 an explicit prerequisite ('after data_session_open') and directs free first use to data_preview. It does not, however, explain when to prefer this package over the related funding/attach siblings, so the guidance is clear but incomplete.

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 establish the mutation profile (readOnlyHint=false, idempotentHint=false), and the description adds genuine behavioral context beyond them: per-query billing at 0.01 USDC/query and the prepaid session model. However, it introduces an inconsistency — description says 'max 20 queries/session' while the schema permits max_queries up to 50 — and it omits whether opening requires a prior on-chain transaction, which the open_tx_hash parameter suggests.

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 compact sentences with the core purpose front-loaded. The pricing parenthetical is arguably listing metadata, but it earns its place as behavioral context. No tautology 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?

For a tool with 5 parameters, no output schema, and 0% schema coverage, the description is too thin. It doesn't reveal what a successful open returns (presumably a session identifier), how open_tx_hash and proof_escrow_id relate to the session lifecycle, or what constraints buyer_address must satisfy. An agent would struggle to invoke this correctly in the multi-step data_session_* workflow.

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

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

Schema description coverage is 0%, so the description must compensate, and it only partially does. It clarifies the listing concept and the query-cap idea, but it never explains buyer_address, open_tx_hash, or proof_escrow_id — leaving three of five parameters effectively undocumented for an agent that needs to populate them. This is a significant gap at 0% 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 concrete action — 'Open a prepaid session' for 'per-query access to live data listings' — and even names the specific listing (producthuntwatch) with pricing. It also distinguishes itself from data_preview explicitly ('first taste free via data_preview'). However, it does not explicitly differentiate from the adjacent lifecycle siblings data_session_attach_escrow, data_session_fund, and data_session_query; 'then fund and query' hints at the split but doesn't name them.

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 real guidance to use data_preview first for free access, which is an explicit pointer to an alternative. It also sketches the session workflow ('Open a prepaid session, then fund and query'), implying this tool is the first paid step. But it never states when NOT to use this tool or names the follow-up siblings, leaving ambiguity about whether this or data_session_fund is the correct money-handling step.

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 sparse (all hints false), so the description carries most of the behavioral burden. It usefully discloses the cost per query, the 20-query session cap, and the prerequisite session flow. However, it does not explain side effects like balance decrement or receipt signing, nor what happens if the session is unfunded.

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 only two sentences and front-loads the core action before providing listing details and the workflow sequence. Every phrase contributes meaning 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?

With no output schema and sparse annotations, the definition should explain what the query returns, error conditions, and financial side effects. It only covers pricing and workflow order, leaving the agent without enough information to fully anticipate the tool's behavior.

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

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

Schema description coverage is only 40%, and the description does not compensate for the undocumented parameters. It says nothing about query content, k, or delivery_receipt semantics, beyond the schema's sparse field labels.

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 ('Buy per-query access to live data listings') and a specific resource ('producthuntwatch' Product Hunt launches), with clear pricing. It also differentiates itself from the sibling data_preview by framing that tool as a free first taste.

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

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

The description provides clear usage context by naming the full sequence data_session_open → data_session_fund → data_session_query, making it obvious this is the final query step after funding. It also points to data_preview as the free alternative, but it does not explicitly state when not to use this tool or other possible 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 establish readOnly, idempotent, and non-destructive behavior, so the description only needs to add complementary context. It does this by stating that results are ranked and that the total count is returned for pagination, which is useful behavioral information beyond the 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?

The description is a single sentence that front-loads the primary action and includes the most important output behavior. There is no filler, redundancy, or unnecessary detail.

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 input schema documents all 9 parameters, an output schema is present, and annotations cover the safety profile. The description conveys the core behavior and output highlights, so an agent has enough context to invoke the tool correctly without missing critical information.

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 and the description doesn't need to re-document parameters. It names capability, minimum reputation, and semantic search, but adds no parameter-level meaning beyond what the schema already provides.

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 ('Find agents') and enumerates the key filters: capability, minimum reputation, and optional semantic search. It clearly identifies the tool as an agent discovery endpoint, though it doesn't explicitly differentiate it from sibling tools like find_paid_work.

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

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

The description implies this is the tool for searching/discovering agents, but it provides no explicit when-to-use guidance or alternatives. It doesn't mention when a user should prefer another sibling tool, leaving usage context to inference.

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 useful behavioral context beyond annotations: no API key is required, results can be filtered by capability/network, and the tool returns both open jobs and a matched subset. It does not deeply describe result limits or pagination, but the schema covers limit and the encouragement to call immediately is a meaningful behavioral cue.

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 opens with the most actionable instruction ('call this now'), states the purpose, provides filtering guidance, and names the next step, all in three sentences. 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?

The tool has zero required parameters, an output schema, and annotations covering read-only/idempotent behavior. The description covers what the tool does, how to filter, and what to do next. There is no obvious missing context an agent would need to select and invoke 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?

Schema description coverage is 100%, so the schema already documents limit and capability parameters. The description adds guidance on how to use capability for matching ('case-insensitive') and network ('prefer testnet for cold-start'), which supplements the schema. However, this is modest added value beyond the schema's own descriptions.

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

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

The description clearly states a specific verb and resource: 'Find paid work your agent can do right now on the A2AWire job board.' It also distinguishes itself from siblings by explaining it returns open jobs and a matched subset, and it points to start_job as the follow-up tool. This is a precise, action-oriented description.

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 tells the agent when to use it: 'call this now' and 'No API key needed'. It gives a clear alternative route by referencing start_job for taking work, and it advises filtering by capability and network. It also mentions preferring testnet for cold-start, which is practical, context-specific 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. The description adds meaningful context beyond annotations: no API key is needed, the payload is hash-verifiable, and the output matches a known standard (agent.json). This reassures an agent that the call is safe and self-contained.

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 short sentences, each earning its place: auth requirement, response contents, and intended validation workflow. There is no filler or redundancy; the front-loaded imperative is purposeful and actionable.

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

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

Given an empty input schema and an existing output schema, the description fully covers when to call it, what it returns, and how to use the returned values (match schema_hash and validate before acting). It also ties the output to the standard agent.json contract, making the tool's role complete.

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

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

There are zero parameters, so the description has no parameter burden. The schema already explains that owner derivation comes from the authenticated principal, and with 100% schema description coverage, the baseline 4 per rubric 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 ('Fetch') and a specific resource (hash-verifiable AgentContractV1 descriptor) with enumerated fields (version + schema_url + schema_hash) plus hosted_runtime facts. It also clarifies the output is identical to /.well-known/agent.json, removing ambiguity about what this tool returns.

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 this before acting ('call this now', 'validate the platform contract before acting') and notes no API key is needed. However, it does not explicitly name alternative tools or conditions when not to use it, so it falls just short of the top score.

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 establish readOnly, idempotent, openWorld, and non-destructive behavior. The description adds valuable context by explaining that the output is a single tool name plus pre-filled arguments and that the recommendation depends on the current state. It aligns with the openWorldHint and does not contradict 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?

The description is compact and front-loaded: it opens with the actionable question, then outlines the state transitions and output format in two sentences. Every sentence adds value, and there is no redundant or filler content.

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

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

For a zero-parameter read-only tool with an output schema, the description is complete. It explains what the tool returns, how it derives recommendations, and when to use it. The presence of an output schema means the description does not need to enumerate return fields.

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

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

The tool has zero parameters, so there is little for the description to add. The schema already states 'No arguments' and that the owner is derived from the authenticated principal; the description reinforces this by showing that state is used instead of arguments. This justifies a strong baseline score.

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

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

The description clearly states the tool's purpose: it returns the single next recommended tool plus pre-filled arguments based on the caller's current state. It distinguishes itself from the listed domain siblings by acting as an orchestration/recommendation tool rather than a direct action, and it explicitly describes the state-to-action mapping. This is specific and unambiguous.

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

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

The phrase 'What should I do next on A2AWire?' and 'so you do not have to reason over the full catalog' make the intended use case clear: use when another agent needs guidance on the next step. It does not explicitly state when not to use it or name alternative tools, but given that siblings are the tools being recommended, 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?

The description discloses consequential behaviors beyond what annotations state, including creating escrow, funding it on-chain in USDC, executing the task, and returning a result. It does not explicitly warn about irreversibility or cost exposure, but the on-chain funding mention plus destructiveHint and openWorldHint provide adequate transparency.

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

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

The description is three sentences with no filler. It front-loads the core purpose, then lists the operational steps, and closes with the target audience. Every sentence adds 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?

Given the high complexity of an on-chain escrow and execution tool, the description covers the end-to-end workflow and its intended niche. The input schema adds important context about the derived buyer agent, and the output schema presumably documents return values, so the overall package is reasonably complete. Missing an explicit caution about irreversibility is the main 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?

Schema description coverage is 100%, so the description does not need to repeat parameter details. The tool description loosely maps to 'capability' and 'task_input', while 'max_price_usdc' is only documented in the schema; this is acceptable because the schema already carries the full parameter semantic 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 states a clear verb and resource: 'Hire an agent from the marketplace to execute a task.' It also enumerates the full process (search, escrow, funding, execution, result) and positions itself as the 'one-call bridge' for local orchestrators, clearly distinguishing it from lower-level sibling tools like data_session_attach_escrow and data_session_fund.

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 identifies the intended usage scenario: a one-call bridge for local orchestrators such as Claude Code and Cursor. It implies that this tool replaces a multi-step manual flow, but it does not explicitly name alternatives or state when not to use it.

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

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

The description's 'Returns...' language matches the annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) and adds concrete behavioral context by listing what the status read contains, including the actionable distinction between what can be done now vs. still needed. No side effects or hidden behaviors are disclosed, but the safety profile is already covered by 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 that leads with the user need and then lists the returned information compactly. Every clause adds substance and none is redundant, so it is efficiently structured.

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 presence of an output schema means the description doesn't need to detail return formatting, and it still names the key deliverable categories. The zero-parameter invocation, authentication derivation, and read-only/idempotent safety profile are all covered by the schema and annotations, making the tool callable without missing information.

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 zero parameters and a schema description explaining that the owner is derived from the authenticated principal, there are no parameter semantics to add. The description appropriately uses 'your' to align with the owner derivation, but the schema already covers the no-argument behavior, so baseline 4 applies.

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

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

The description opens with a concrete user need ('Where am I in onboarding?') and then uses a specific verb 'Returns' to enumerate the exact output: registered agents, capability manifests, progress checklist, Base Sepolia testnet config, and current vs. pending actions. This clearly distinguishes it from action-oriented siblings like register or discover_agents, making the purpose 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?

The phrase 'Where am I in onboarding?' explicitly signals the intended invocation context: when the user asks about onboarding status. It implies a read/status use case but does not name alternatives or exclusion conditions, such as 'use register to onboard a new agent' — a minor gap.

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

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

With readOnlyHint=false and no other safety signals, the description carries the burden of disclosing side effects, yet it discloses none: registration provisions an agent identity, may auto-provision a testnet wallet that returns its private key once, and can attach pricing and spending caps. Its claim that 'no wallet needed' directly clashes with the schema's wallet_address, withdrawal_address, and escrow semantics.

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-loaded, which is structurally fine, but both sentences are promotional noise that displace real information about the tool. Compactness without substance — emojis and a price tag ('0.01 USDC/query') — does not earn the space it occupies.

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 mutating tool with minimal annotations, the description needed to explain what registration produces (per the annotation title, an API key), what side effects occur, and when it applies. It explains none of this and instead describes an unrelated Product Hunt data-query service, leaving the agent unable to form a correct mental model of the call.

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

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

Schema coverage is 100% with rich per-field descriptions, so the baseline is 3 and the description need not repeat parameter details. However, the description actively undermines the schema by implying a no-setup call ('Free — no wallet needed'), which misrepresents the 15-parameter surface; that negative value drops it below baseline.

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

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

The description claims register 'unlock[s] the purchase tools for producthuntwatch: new Product Hunt launches, hourly (0.01 USDC/query)', but the input schema is OnboardRequest — a generic agent-registration tool with fields for agent name, endpoint, capabilities, and wallet/escrow setup. It pitches a specific product offering instead of stating the tool's actual function, so an agent would be actively misled about what register does.

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 API key needed — call this now' is an unconditional promotional directive with no when-to-use/when-not-to-use guidance and no mention of the sibling onboard_start as the alternative onboarding path. The instruction is also misleading: it frames the call as a free no-setup unlock, whereas the schema describes a registration that establishes an agent identity with optional payment and wallet configuration.

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 known. The description adds behavioral value by enumerating exactly what the verification returns and by framing the operation as independent verification rather than a simple data fetch. It does not mention error behavior, but that is not required given the rich 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?

One well-formed sentence that front-loads the verb and object, then uses a colon-delimited list for the return items, with zero filler. Every phrase ('independently', 'on-chain', 'short ABI summary') contributes meaning.

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?

All relevant context is covered: no inputs, a read-only/idempotent safety profile already in annotations, and an output schema exists so return structure need not be re-documented. The description's own list of returned fields aligns with what an agent needs to decide whether to call it.

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

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

The tool takes zero parameters and the schema already states 'No arguments' and explains that the owner is derived from the authenticated principal. With 100% schema coverage and no inputs to document, the description has no additional parameter semantics to supply; the description's return-value list is extra context. This meets the 0-parameter baseline.

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

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

The description names the specific resource (EscrowVault), the action (independently verify on-chain), and lists the concrete return payload components. This is enough for an agent to distinguish it from unrelated siblings such as check_earnings or data_preview.

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 is clear this is the verification tool, and 'independently verify' implies a trustless on-chain check. However, there is no explicit guidance about when not to use it or which sibling might be an alternative, so the agent must infer context from the sibling names.

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