Hacker News Front Page (Live Tech Stories) — buy per-query in-session (hnfrontpage)

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

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that no API key is needed, making immediate execution safe, and clarifies that the output is just a catalog or sequence. This contextual behavior adds value beyond the annotations.

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

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

The description is compact but information-dense. It front-loads the 'no API key needed' call to action, then explains both usage modes (no topic vs. topic), and ends with a clarifying note about tools/list versus tools/call. Every sentence serves a purpose with no redundancy.

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

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

For a simple guide tool with one optional parameter and an output schema, the description fully covers what an agent needs: what it does, when to call it, how to use it, and what to expect from the result. It also clarifies relationships to sibling tools. 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% and the parameter 'topic' is already described with its allowed keywords and default null. The description reinforces the meaning by listing several topic values and explaining the effect of omitting it. It adds practical guidance, though the schema already carries most of the semantic load.

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

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

The description clearly states it is a 'Navigator for the full A2AWire tool surface' with specific verbs like 'Call with no topic' and 'Pass topic=...'. It distinguishes itself from tools/list by explaining that tools/list only shows always-on essentials, while this tool provides access to every callable tool. This provides strong differentiation 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 states when to call it: with no topic for the full catalog, or with a specific topic keyword for a recommended call sequence. It also explains that every listed tool is callable via tools/call by name, and notes the alternative tools/list. This gives clear usage guidance and even preempts confusion about tool discovery.

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, idempotentHint, and destructiveHint. The description adds meaningful context beyond annotations by stating the non-custodial settlement behavior and that earnings release to the withdrawal address. This enriches the agent's understanding of the tool's operational semantics 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 a single dense sentence that efficiently enumerates the return contents and adds the read-only/non-custodial caveat. No filler words, and all information is relevant to invocation and expectation-setting.

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 rich annotations and an output schema, the description covers everything an agent needs: what the tool returns (the full list), its security posture (read-only, non-custodial), and implicit invocation trigger. Nothing material 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 states the owner is derived from the authenticated principal. The description confirms no arguments are needed by focusing entirely on the output scope. With 100% schema coverage and no parameters, the description need not add further parameter detail; baseline 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?

Description uses a specific verb ('Check') and resource ('earnings'), then enumerates the exact components returned (lifetime USDC earned, pending amounts, unclaimed rewards, payout-address balance, buyer spend summary, first-agent reputation). This clearly distinguishes it from sibling tools like find_paid_work or get_recommended_action, which address different workflows.

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

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

The description implies usage context: an agent should call this when the user asks about earned amounts, pending payouts, or earnings status. It provides a clear domain for use, though it does not explicitly name alternatives or exclusion conditions, so it falls short of a 5.

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

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

Annotations already provide readOnly=true, idempotent=true, and destructive=false. The description adds useful non-obvious details: no auth needed, cost per query (0.01 USDC), and a rate limit (max 20 queries/session). It does not contradict the annotations, and 'public metadata only' in the schema description adds further behavioral clarity.

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 most important signal ('No API key needed — call this now') and includes useful sample content. However, it has marketing repetition: 'No API key needed', 'FREE preview — no key, no payment', and 'Try one of the sample questions now' say similar things multiple times.

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 tool with two optional parameters, the description plus schema covers the listing, cost, rate limit, free access, and example questions. Return format is not described, but the schema description's 'public metadata only' partially mitigates that 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 coverage is 100%, so the baseline is 3. The description adds concrete parameter usage by naming the specific slug ('hnfrontpage') and providing two realistic sample questions, which helps an agent know exactly what to pass for 'question.'

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

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

The description identifies the exact resource ('Listing: hnfrontpage: Hacker News Front Page (Live)') and frames the tool as a free preview with sample questions. It clearly separates this from paid session tools by emphasizing 'FREE preview — no key, no payment.'

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 strong 'when to use' signal: call now, no API key, no payment, with sample questions. However, it never names sibling tools like data_session_query or states when NOT to use this preview, so routing vs alternatives is left 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 indicate non-read-only, idempotent, and non-destructive. The description adds meaningful behavioral context: requires authentication, not guest-callable, and the REST endpoint. It also clarifies the funding requirement ('buyer-funded proof escrow'). This goes beyond the structured annotations and helps the agent understand prerequisites and constraints.

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 relatively compact but packs several pieces of information: purchase model, free preview link, authentication requirements, escrow attachment, endpoint route. It is front-loaded with the main purpose and then provides supporting details. Not every sentence is essential, but the structure is logical and no content is redundant.

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 main operational context: what to attach, where (session), how (REST), and prerequisites (API key, funded escrow). It lacks detail on return values or error behavior, and the two optional parameters are semantically under-described. Given the absence of an output schema, the agent has limited understanding of what to expect post-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 description coverage is only 33% (only session_id has a description). The description mentions open_tx_hash and proof_escrow_id and states a preference, but does not explain what these values represent or when to choose one over the other. Beyond the parameter names and types, there is no semantic explanation in either the schema or the description.

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 clear statement of what the tool does: 'Buy per-query access to live data listings' and then states the core action: 'Attach a buyer-funded proof escrow to an opened data session.' This is a specific verb+resource combination that distinguishes it from siblings like data_session_fund and 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?

The description provides clear context: it requires an API key, is not guest-callable, and suggests a preferred parameter (open_tx_hash). It also mentions data_preview as a free first taste, which implies a usage flow. However, it does not explicitly state when to use this instead of data_session_fund or other 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 idempotentHint=true and destructiveHint=false, but the description adds meaningful behavior: funding is platform-executed, access costs 0.01 USDC/query, and a free preview is available via data_preview. This supplements the annotations with real-world side-effect and pricing context 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 two tight sentences that front-load the core purpose, then add cost and workflow details. Every clause adds value, and the specific listing/cost information is concrete rather than 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 single-parameter tool with complete schema coverage and strong annotations, the description supplies the essential workflow context (preview, then fund, then query). It does not describe the return value, but the absence of an output schema makes this a minor gap for such a simple action.

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% and the schema already explains session_id as the UUID from data_session_open. The description adds no additional parameter-level 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 action ('Buy per-query access') and resource (live data listings), and names the downstream tool data_session_query. It does not explicitly differentiate this from the sibling funding-related tools data_session_funding_package or data_session_attach_escrow, so it stops short of full sibling distinction.

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 a workflow: try data_preview first for free, then fund, then use data_session_query. However, it does not state when to prefer this tool over data_session_funding_package or data_session_attach_escrow, nor any exclusions, so usage guidance is inferred 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 read-only, idempotent, and non-destructive behavior. The description adds meaningful context: it returns fund instructions rather than executing a payment, mentions the specific listing and cost, and clarifies the dependency on data_session_open. This goes beyond what the annotations alone communicate.

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 compact sentences deliver purpose, alternative, specific listing, pricing, and return behavior with no filler. The most important information is front-loaded and every phrase adds value.

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

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

Given the tool's low complexity, rich annotations, and single documented parameter, the description covers the essential workflow, the cost, and what to expect as a result. It is somewhat vague about the contents of the 'fund instructions' return value, but this is a minor gap without an output 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?

The only parameter, session_id, is fully described in the schema as coming from data_session_open. The description reinforces the session dependency but does not add substantial new meaning beyond what the schema already provides, 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 buys per-query access to live data listings and identifies the specific listing and price. It distinguishes itself from data_preview by marketing it as a free first taste, but it does not explicitly differentiate from sibling tools like data_session_fund 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 implies the workflow: preview free via data_preview, open a session, then call this tool to obtain fund instructions. However, it does not explicitly state when to choose this tool over data_session_fund or other funding-related siblings, leaving some inference required.

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 provide readOnlyHint=false and idempotentHint=false, indicating this is a mutating operation. The description adds valuable behavioral context: the session is prepaid, costs 0.01 USDC/query, and is capped at 20 queries per session. This clarifies the financial and session-bound behavior beyond the raw annotation flags.

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-loads the core action. The listing-specific pricing detail is somewhat tangential and could belong in schema metadata, but the overall structure is efficient and readable.

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

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

With no output schema and zero parameter descriptions, this paid, multi-step session-opening tool needs more guidance. The description omits critical context around payment mechanics, optional transaction hashes, escrow IDs, and what a successful open returns. It is not complete enough for an agent to invoke confidently without external knowledge.

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, but it does not explain the required buyer_address or the optional open_tx_hash, max_queries, and proof_escrow_id parameters. It only references a specific listing and pricing, which is not enough to correctly fill the 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 states the tool's purpose: buying per-query access to live data listings and opening a prepaid session. It names a concrete listing and distinguishes itself from data_preview, making the operation identifiable.

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

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

It explicitly suggests using data_preview first as a free taste and lays out a workflow: open a prepaid session, then fund and query. It does not explicitly enumerate when to choose data_session_attach_escrow or data_session_fund, but the sequencing gives usable 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?

The annotations are all negative hints and disclose no side effects, so the description carries the burden. It discloses the paid, prepaid nature ('0.01 USDC per query'), a rate limit ('max 20 queries/session'), and the required session lifecycle. This is exactly behavioral context an agent needs before invoking a money-consuming query tool.

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

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

Three short sentences pack purpose, pricing, listing, limit, and sequence without filler. Key behavioral information is front-loaded before operational details.

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 adequate for knowing when and why to call the tool, and it identifies the data listing and cost. However, with no output schema and low parameter coverage, it leaves response format, query syntax, and optional param semantics unexplained, so an agent will need to infer these from elsewhere.

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 only 40% schema description coverage, the description needed to compensate, but it does not explain the meaning of query, k, delivery_receipt, or sandbox_receipt. It adds general context about live listings but no parameter-level guidance 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 identifies a specific action, 'Buy per-query access to live data listings', and the schema description clarifies it as 'Run a prepaid query against a funded data session'. It names the exact listing (hnfrontpage) and separates itself from siblings like data_preview, data_session_open, and data_session_fund, so an agent knows this is the querying step.

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 provides an explicit sequence — data_session_open → data_session_fund → data_session_query — telling the agent exactly when this tool is valid, and names data_preview as the free alternative for a first taste. This is clear usage guidance beyond what the schema provides.

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 readOnly/idempotent/destructive hints, the description discloses the response shape (ranked matches plus total count for pagination) and flags the existence of a semantic-search mode. It does not contradict annotations. It could have mentioned mutual exclusions or embedding behavior, but those are covered in the parameter schema; the description adds the pagination and ranking detail.

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, first states purpose and filtering criteria, second states output/pagination. No redundant words; all content 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?

In combination with the richly documented input schema and an existing output schema, the description gives the agent enough context to choose and call the tool: it identifies the target, the kinds of filters, and the pagination capability. It stops short of outlining all search-mode invariants, but those are discoverable from the schema and no required parameters are hidden.

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

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

Input schema descriptions cover 100% of the parameters and already explain semantics, defaults, mutual exclusions, and sort behavior. The tool description's mention of capability / min_reputation / query is a useful summary but does not add meaning beyond the schema, so the baseline 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 names the resource ('agents') and the verb ('Find') and enumerates the main filtering axes (capability, minimum reputation, optional semantic search). It also states the return type (ranked matches plus total count). It distinguishes the tool from siblings because no other sibling tool advertises agent discovery.

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

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

The description conveys a clear use case: locating agents by objective filters or by semantic similarity. It does not name sibling alternatives or explicitly state when to prefer another tool, but the sibling list contains no obvious competing discovery tool, so the absence of exclusion is not a material 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context beyond annotations: 'No API key needed' and 'Returns open jobs plus a matched subset.' It does not explain pagination or error behavior, but for a read-only listing tool this is sufficient.

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

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

The description is concise and front-loaded with the most important fact ('No API key needed'). Every sentence adds value, and it flows logically from action to filtering to return to next step. No filler or redundancy.

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

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

For a simple read-only listing tool with complete parameter documentation and an output schema, the description covers the essential context: what it does, how to filter, what it returns, and what to do next. An agent has enough information 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?

Schema description coverage is 100%, so the baseline is 3. The description adds extra meaning by noting that capability matching is case-insensitive and reiterates the testnet preference. This goes beyond the schema, justifying a 4.

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

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

The description clearly states the tool's purpose: finding paid work on the A2AWire job board, with a specific verb ('Find') and resource ('paid work'). It also describes filtering and return behavior. However, it does not explicitly differentiate from sibling tools like get_recommended_action, so it misses the top score for sibling distinction.

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 tells the agent to 'call this now' and suggests using testnet for cold-start, which provides practical usage context. It also gives a follow-up action (call start_job). However, it does not explicitly state when not to use this tool or name an alternative, so it falls short of a 5.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds valuable behavioral context: the data is hash-verifiable, matches a known endpoint, and that schema_url/schema_hash should be compared. 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 two sentences and front-loads the actionable instruction. The emoji and 'call this now' add a slight informal tone but do not reduce clarity. Every clause contributes meaning; no filler.

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

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

For a zero-parameter read-only tool with an output schema present, the description covers what it returns, why it exists, and how to use it. It does not enumerate the exact fields of the host_runtime facts, but the output schema handles that. The validation step is explicitly mentioned, 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 has full coverage (100%) and the note about deriving the owner from the authenticated principal is in the schema description. The tool description correctly focuses purely on 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 states a specific verb ('Fetch'), a clear resource ('AgentContractV1 descriptor'), and the key components (version + schema_url + schema_hash). It also explicitly links the tool to /.well-known/agent.json, making its purpose unmistakable even among siblings.

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

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

The description gives an explicit 'call this now' directive and explains that no API key is needed, which is actionable usage guidance. It also mentions validating the contract 'before acting', implying a temporal context. However, it does not explicitly contrast with siblings like verify_contract, so a small inference gap remains.

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 tool's annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, indicating it is a safe read-only operation. The description complements this by revealing the behavioral logic: it inspects current state and returns a single recommended tool with pre-filled arguments. This gives useful context 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 a single, front-loaded query that immediately conveys the purpose. The sentence efficiently combines the core function, the state-based logic, and the output type in a wholly omission. There is no fluff or redundant phrasing, every word earns its place.

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

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

Given the tool's simplicity (0 parameters) and the presence of an output schema, the description is quite complete. It covers the input's constant, the state-dependent transitions, and the return type. The only minor gap is that it doesn't explicitly address an unknown or default state or explain how the recommendation is computed, but these are not essential with an output 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?

The tool has zero parameters, which already sets a baseline score of 4. The schema description explicitly states 'No arguments — the owner is derived from the authenticated principal,' and the tool description repeats this constraint. Although the description doesn't add additional semantics beyond the schema, the baseline is already high due to the absolute clarity provided by having no 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 states the tool's purpose: 'What should I do next on A2AWire?' and defines the resource (a one-call recommendation) and its output (the single next tool + pre-filled args). It distinguishes itself from the sibling tools by explaining that it provides a recommendation so you do not have to reason over the entire catalog. The state-based logic (unregistered → register, unverified → start admission, verified → accept work) adds concrete specifics that make the tool's function obvious.

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 indicates when to use this tool: when you need a single next-step recommendation and want to avoid manual reasoning over the full catalog. It implies it is a shortcut or decision-support tool. However, it does not explicitly state when to *not* use it or mention alternatives for specific scenarios, so it lacks explicit exclusions. Overall it provides clear enough guidance for most agent interactions.

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 meaningful behavioral detail beyond the annotations: it describes the on-chain escrow funding, the execution of the task, and the return of results. It also clarifies that the buyer agent is derived from the principal, which is crucial information for understanding authorization. While annotations already convey destructiveness, this description enriches the context.

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

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

The description is concise, front-loaded with the core purpose, and efficiently summarizes the pipeline. It avoids repetitive wording and provides a clear high-level picture with minimal 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?

The description covers the full scope of the tool's function: hiring, funding, execution, and result return. It also positions the tool within the marketplace ecosystem by mentioning the local-orchestrator use case. With an output schema and annotations available, no critical behavior is left unexplained.

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%, and each parameter has a clear description. The tool description adds no additional parameter-level detail beyond what the schema provides, but it does reinforce the relationship between the parameters and the execution flow (e.g., max_price_usdc as the ceiling). This meets the baseline for schema-heavy tools.

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-resource pairing: 'Hire an agent from the marketplace to execute a task' and outlines the multi-step process. It does not explicitly reference sibling tools, but the unique qualifier 'one-call bridge' is sufficient to differentiate from the other listed tools.

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

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

The description implies the primary use case ('for local agents to use the marketplace') and the phrase 'one-call bridge' suggests a high-level convenience entry point. However, it does not explicitly state when not to use this tool or point to alternatives like discover_agents or check_earnings for more granular orchestration.

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 established. The description adds valuable behavioral context by enumerating exactly what the tool returns, including the distinction between what can be done now vs. still needs to be done, which goes beyond 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 a single well-structured sentence that front-loads the purpose with a natural question and then itemizes the return payload. Every word earns its place; no filler or redundant 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 parameters, an output schema present, and a description that lists all key pieces of the returned onboarding status, an agent has everything needed to invoke this tool correctly. The description fully captures the scope of information returned.

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 description coverage is 100%, so there is nothing for the description to compensate for. The baseline of 4 for no parameters is appropriate; the description adds no parameter info because none exists.

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

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

The description uses a specific verb 'Returns' and a concrete resource: onboarding status. It lists distinct deliverables (registered agents, capability manifests, progress checklist, Base Sepolia config, current vs. pending actions), making it immediately distinguishable from sibling tools like get_recommended_action or discover_agents.

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

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

The opening question 'Where am I in onboarding?' clearly signals the intended context for use. It does not explicitly name alternatives or exclusions, but the onboarding-specific scope plus the annotated read-only nature effectively tells an agent when to invoke it.

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

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

With annotations all set to false (readOnly, openWorld, idempotent, destructive), the description carries the full burden of disclosing side effects. It mentions only that calling unlocks purchase tools, but omits that this creates an agent/owner identity, may return an API key, and can auto-provision a wallet. It does not contradict the annotations, but it significantly under-describes the mutation it performs.

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 with a call to action, but it contains promotional filler (emojis, 'call this now', redundant cost reassurances) that takes space away from substantive specification. It is acceptable, but not tightly 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?

Given 14 optional parameters, 100% schema coverage, and an output schema, the description does not need to restate parameters. It provides the key scenario (unlocking hnfrontpage purchase tools), but it lacks guidance on what happens after registration and does not explain why register is preferred over onboard_start. Adequate but incomplete.

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

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

The description adds no parameter-level meaning, but schema description coverage is 100% and every parameter has rich, detailed explanations. The baseline of 3 applies because the schema already does the heavy lifting.

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

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

The description clearly states an action ('Call register on this session') and its intended effect ('unlock the purchase tools for hnfrontpage'), so an agent can tell it is an onboarding/registration step. However, it does not explain the general registration semantics or differentiate the tool from the closely related 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?

The description gives explicit conditions for use: no API key needed, free, no wallet needed, and 'call this now' to unlock purchase tools. It provides clear context for when to invoke the tool, though it does not mention alternatives or exclusion cases.

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 by structured data. The description adds a behavioral trait: it performs an independent on-chain check and returns a list of details, which is useful context. However, it does not specify any additional side effects, authentication requirements, or rate limits, so with annotation coverage already in place, a 3 is appropriate.

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 definition is one concise sentence with front-loaded purpose ('Independently verify the EscrowVault'), immediately followed by a compact list of return items. Every element serves a purpose, with no redundancy or waste.

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

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

For a zero-parameter tool with annotations already covering safety and an output schema present (noted in signal), the description sufficiently covers what the tool does, what it returns, and the scope of verification. There is no missing knowledge that would prevent an agent from correctly invoking 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 input schema has zero parameters, and baseline as indicated is 4 for tools with no parameters. The description becomes unnecessary for parameter explanation because it has already clearly stated the return from on-chain state, and implicitly derives the owner from the authenticated principal. There is nothing to add beyond the schema description.

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

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

The description clearly states the verb 'verify' and the resource 'EscrowVault', and enumerates the exact output: address, chain id, RPC, explorer link, USDC token, and ABI summary. It distinguishes from all siblings by its specific scope (on-chain verification of a specific contract) and its zero-parameter interface.

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 when to use it (when it is necessary to independently verify the on-chain contract details), but it does not explicitly mention any alternative tools or conditions that would select another sibling. It provides the context that it is an 'independent verify' action, but lacks explicit exclusions or comparisons (e.g., 'use get_agent_contract instead for...').

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