New Hugging Face Spaces — AI App Demo Discovery (hfspaces)

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

The description adds meaningful behavioral context beyond the annotations: no API key is needed, the call is safe to make immediately, and the tool reveals the broader callable tool surface rather than just the always-on subset. Annotations already cover read-only, idempotent, and non-destructive behavior, so the description does not need to restate those. It could say more about the exact output shape, but the output schema covers that.

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

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

The description is dense but efficient, front-loading the most actionable instruction ('No API key needed — call this now') and then explaining the two usage modes. The keyword list is long but necessary for topic values. It is slightly run-on, but every sentence contributes practical information.

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

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

For a simple, optional-parameter navigator tool, the description is complete: it states the purpose, the exact invocation modes, the accepted topics, and how to invoke the tools it surfaces. The output schema exists to handle return-value details, and annotations cover read-only/idempotent safety. Nothing essential is missing for an agent to call this tool correctly.

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

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

Schema description coverage is 100%, so the baseline is 3 even without additional parameter detail. The description does add value by enumerating more topic keywords than the schema description includes (e.g., buy, benchmark) and by clarifying the no-topic behavior. However, most parameter semantics are already present in the schema, so extra credit is limited.

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 is a navigator/catalog for the full A2AWire tool surface, with two distinct modes: no topic returns a categorized catalog, and a topic returns a recommended call sequence. This distinguishes it from sibling tools that perform concrete operations like check_earnings or hire_and_execute. The specific verbs 'Call' and 'Pass' make the intended action 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?

It explicitly says when to call with no topic versus with a topic, and lists the accepted topic keywords. It also gives a direct alternative comparison: every listed tool is callable via tools/call, while tools/list only shows always-on essentials. This is strong practical routing guidance for an agent.

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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description reinforces this with 'Read-only.' It adds one genuinely non-obvious behavioral fact — 'earnings settle non-custodially to your withdrawal address on release' — which tells the agent the tool never moves money itself and settlement happens asynchronously. No contradiction with annotations.

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

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

Three sentences, front-loaded with the core purpose. The return-category list is dense but earns its place by teaching the agent the semantic meaning of the output categories, and the closing read-only/settlement note is valuable safety context. Slightly long, but no sentence is wasted.

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 overview tool whose annotations already carry the safety profile and whose output schema covers the return structure, the description is complete. The non-custodial settlement semantics it adds are exactly the kind of financial knowledge an agent cannot derive from the schema alone.

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 is the baseline-4 case. The schema description already fully covers the only relevant semantic ('No arguments — the owner is derived from the authenticated principal'), so the tool description correctly needs to add nothing about 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 opens with a specific verb+resource, 'Check how much I have earned and what is pending,' followed by a precise enumeration of return categories (lifetime USDC as seller, in-flight pending amounts, unclaimed claim-later rewards, payout-address balance, buyer spend summary, first-agent reputation). This fully scopes the tool and distinguishes it from all 15 siblings, none of which are earnings-overview 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?

Usage is implied by the purpose statement and the detailed return list, but the description never explicitly states when to use this tool versus an alternative and names no exclusions. The risk is low because no sibling (data_session_query, get_agent_contract, find_paid_work) is a near-alternative, but explicit routing guidance is absent.

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 annotations, the description adds useful behavioral context: no API key is needed, it is free, and there is a 'max 20 queries/session' limit. It does not contradict the annotations. The 'Price 0.01 USDC/query' line is potentially confusing because it appears right next to 'FREE preview,' but the free-preview claim is restated clearly.

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

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

The description is repetitive and promotional: 'No API key needed', 'FREE preview — no key, no payment', and 'Try ... now' all make the same point. It is not tightly structured and mixes listing metadata (price, max queries) with tool instructions. A more direct sentence such as 'Returns public metadata preview for a listing' would be clearer and shorter.

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 annotations and schema already cover safety and parameter meaning, so the description does not need to re-explain them. However, there is no output schema and the description never states what the preview actually returns; the sample questions can mislead an agent into expecting query results. It is adequate but not complete for an agent choosing between this and paid session tools.

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

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

The schema already covers both parameters with full descriptions, so the baseline is 3. The description contributes concrete example values: the slug 'hfspaces' and two sample questions. It does not deepen the meaning of 'slug' or 'question' beyond what the schema provides, and it does not clarify that the question is echoed back.

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

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

The description says 'FREE preview' and names a specific listing ('hfspaces: New Hugging Face Spaces'), so it gestures at previewing a data listing. But the wording is promotional rather than a direct verb+resource statement, and the sample questions make it seem like the tool answers arbitrary data questions when the schema says the question is only echoed back. It is not a tautology, but the purpose is muddled.

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

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

The description strongly signals 'No API key needed — call this now' and 'FREE preview — no key, no payment,' implying this is the low-friction way to try a listing. However, it never explicitly says when to use this instead of sibling tools like data_session_query or when a preview is not sufficient. Usage context is implied rather than spelled out.

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

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

Annotations already establish that this is not read-only, is idempotent, and is not destructive. The description adds useful behavioral context beyond annotations by requiring an agent API key, stating it is not guest-callable, and clarifying this attaches a buyer-funded escrow. No contradiction exists.

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

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

Every sentence earns its place: purpose, auth requirement, the actual attach operation, guest limitation, and endpoint. It is compact, front-loaded, and free of filler.

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

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

The description covers purpose, prerequisites, auth, endpoint, and parameter preference, which is enough to invoke the tool correctly. It does not describe the response or explicitly connect to data_session_fund/funding_package, but these are minor gaps given the available annotations and schema.

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

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

Schema description coverage is low at 33%, so the description must compensate. It usefully says open_tx_hash is preferred and mentions proof_escrow_id, and it frames both as buyer-funded proof escrow identifiers. But it does not fully clarify when each is valid or whether one is effectively required, leaving partial ambiguity.

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

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

The description states a specific verb and resource: attach a buyer-funded proof escrow to an opened data session. It also clarifies the high-level outcome (buying per-query access) and distinguishes itself from data_preview as the free first taste, making its role clear relative to 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?

It gives concrete usage context: requires an agent API key, is not guest-callable, must target an opened data session, and provides the REST endpoint. It also points to data_preview as the free alternative. However, it does not explicitly contrast this with sibling tools like data_session_fund or data_session_funding_package, so it stops short of full exclusion guidance.

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

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

The annotations already provide idempotentHint, destructiveHint, and readOnlyHint, so the description is not required to restate them. It adds valuable behavioral context beyond the annotations: this is a paid transaction ('Buy per-query access', '0.01 USDC/query') and that the platform executes the funding so the session can be queried. It does not over-explain or contradict the annotations.

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

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

The description is compact and front-loaded with the core purpose. It includes relevant workflow context (preview first, then fund, then query) and pricing in a few sentences. The specific listing name and price add useful operational detail without bloating the description.

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

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

For a single-parameter tool with a complete schema, the description plus schema is enough to invoke the tool correctly. It explains the action, the cost, the prerequisite session_id, and the next step. It does not describe return values, but there is no output schema and the operation is simple enough that this is a minor gap.

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

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

The input schema has 100% description coverage and the only parameter, session_id, is well documented as 'UUID of a data session you opened (from data_session_open).' The tool description adds no further 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 states a clear verb-resource pair: 'Buy per-query access to live data listings.' It also distinguishes itself from the free preview via 'first taste free via data_preview' and sets up the follow-on action 'so you can data_session_query.' The title 'Fund Data Session (Sandbox)' reinforces the purpose without ambiguity.

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 workflow: start with data_preview for free, then fund the session, then use data_session_query. It clearly implies when to use this tool (after preview, before paid queries). It does not explicitly mention when not to use it or how it differs from data_session_funding_package, so it stops short of a 5.

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

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

Annotations already cover read-only/idempotent/non-destructive behavior; the description adds useful context by stating the price (0.01 USDC/query) and that the output is fund instructions. The verb 'Buy' could be misread as executing a payment, though 'Returns fund instructions' softens this and does not create a clear contradiction 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 sentences carry purpose, listing, pricing, alternative, output, and sequencing with little waste. The embedded 'Listing: hfspaces: ...' chain is slightly cluttered, so it is not perfectly structured, but every clause earns its place.

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

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

For a single-parameter tool with no output schema, the description gives the essential return type ('fund instructions') and a prerequisite. It is somewhat incomplete because it never distinguishes funding_package from the data_session_fund/data_session_attach_escrow siblings, leaving a meaningful integration 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%, and the schema already explains session_id as the UUID from data_session_open. The description only repeats the dependency on data_session_open without adding format, defaults, or constraints.

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

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

The description names a concrete action ('Buy per-query access to live data listings') and a specific listing ('hfspaces: New Hugging Face Spaces') with an explicit price, making the tool's purpose clear. It does not attempt to distinguish itself from the similarly named sibling data_session_fund, so an agent may not know which funding-related tool to choose.

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

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

It gives clear context: use it after data_session_open, and use data_preview for a free first taste. It does not explicitly state when not to use it or mention alternatives like data_session_fund/data_session_attach_escrow, but the sequencing and free-preview guidance are enough for basic routing.

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 genuine behavioral context beyond the all-false annotations: the operation costs money (0.01 USDC/query), enforces a 20-query cap per session, and is described as a purchase/open action consistent with readOnlyHint=false. It does not disclose the on-chain transaction requirement implied by open_tx_hash, cancellation/refund behavior, or what happens if the session is never funded.

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 compact sentences with the core purpose front-loaded. The second sentence, however, embeds one specific listing's identity and pricing ('Listing: hfspaces... 0.01 USDC/query'), which is stale-prone and could mislead an agent into thinking the tool is restricted to that single listing rather than being a generic session opener.

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 money-moving tool with 6 optional-looking parameters and no output schema, the description plus schema description cover the slug-or-UUID choice and wallet default well. The overall data-purchase workflow is only sketched ('then fund and query'); the role of escrow, the funding package sibling, and the on-chain open_tx_hash remain unexplained, leaving an agent to guess the full payment flow.

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 50% schema description coverage, the schema already explains listing_id/listing_slug exclusivity and buyer_address default. The description adds pricing and the 'max 20 queries/session' limit, partially illuminating max_queries. However, open_tx_hash and proof_escrow_id remain semantically opaque in both the description and the schema — an agent cannot tell how to obtain or populate them.

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

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

The description states a specific action ('Buy per-query access to live data listings') and the resource (data sessions/listings), matching the title 'Open Data Session'. It is distinguishable from siblings like data_session_fund and data_session_query. However, 'Open a prepaid session, then fund and query' slightly muddles whether the session is prepaid at open time or funded afterward.

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 routes to data_preview for free access ('first taste free via data_preview'), signaling when the paid alternative is appropriate. It also implies the session lifecycle order: open, then fund, then query. It does not, however, explain when to use data_session_attach_escrow or data_session_funding_package instead of or in addition to this tool.

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

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

Beyond the annotations, the description discloses that each query costs 0.01 USDC and is capped at 20 queries per session, which are critical behavioral constraints. It also signals the paid nature and points to a free preview via data_preview. It does not explicitly describe balance deduction or DeliveryReceipt signing, but the cost and quota information is meaningful context.

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

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

Three sentences, compact and front-loaded with the core purpose before giving the listing details and required sequence. The phrase 'AI app demos & live web UIs' adds color rather than invocation-critical information, so it is not a perfect 5, but there is little 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?

The description provides the essential lifecycle, cost, and per-session query cap, which is strong contextual coverage. However, with no output schema and only 40% parameter documentation, an agent still lacks guidance on output format, error behavior, and the role of delivery_receipt/k, so completeness is only partial.

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 tool description does not compensate. It does not explain the semantics of query, k, or delivery_receipt; only session_id and sandbox_receipt have schema-level descriptions. The description mentions per-query pricing but gives no guidance on what a valid query looks like or how k/receipts influence execution.

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 operation as per-query access to live data listings and anchors it in the data_session_open → data_session_fund → data_session_query sequence, so an agent can tell this runs queries against a funded session. It also distinguishes itself from data_preview by noting the first taste is free there. The 'Buy' phrasing is slightly commercial, but the resource and verb are clear enough.

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 sequence data_session_open → data_session_fund → data_session_query clearly tells the agent when this tool is intended to be used, after opening and funding a session. It also points to data_preview as the free alternative. It does not spell out explicit 'don't use this if...' conditions, but the sequence and 'funded session' implication provide adequate 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 already establish read-only, idempotent, non-destructive behavior, lowering the bar for the description. The description adds useful behavioral detail beyond annotations by stating that results are 'ranked matches' and that a total count is returned for pagination, which helps set expectations about output and ordering.

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, compact sentence that front-loads the core action and criteria, then mentions the return shape. There is no filler, redundancy, or irrelevant 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?

For a read-only discovery tool with a rich output schema and fully documented parameters, the description provides enough high-level context: what to filter by, that results are ranked, and that pagination is supported. It could be more complete by hinting at when to use semantic search versus exact filtering, but the schema covers the mechanics.

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 input schema already documents all nine parameters in detail. The description mentions capability, minimum reputation, and semantic search, but adds no new meaning beyond what the schema already provides. Baseline 3 is appropriate.

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

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

The description states a specific verb ('Find'), a clear resource ('agents'), and the key criteria (capability, minimum reputation, optional semantic search). It is unambiguous about what the tool does, but it does not explicitly differentiate itself from sibling tools like get_recommended_action or find_paid_work, so it falls just short of a perfect 5.

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

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

The description implies this is for searching/discovering agents, but it provides no guidance on when to choose this tool over siblings, nor does it state exclusions or alternatives. An agent has to infer usage from the name and filters rather than being told.

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

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context beyond annotations: no API key is required, capability matching is case-insensitive, testnet should be preferred for cold-start, and the tool returns both open jobs and a skill-matched subset. There is no contradiction with the annotations.

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

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

The description is compact and front-loaded, starting with the most actionable signal: 'No API key needed — call this now.' Every sentence earns its place, covering purpose, filtering behavior, return content, and the follow-up call without unnecessary repetition or padding.

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 rich annotations, a fully documented input schema, and an existing output schema, the description is complete enough for correct invocation. It covers authentication needs, filtering guidance, what the tool returns, and the next step (calling start_job). No critical operational detail is missing.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds extra meaning beyond the schema by specifying that capability filtering is case-insensitive and by clarifying that the tool returns a matched subset for the agent's skill. This is non-obvious and improves correct invocation, especially for choosing capability values.

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: finding paid work on the A2AWire job board. It explains filtering by capability and network and mentions returning open jobs plus a matched subset, which makes the tool's function unambiguous. It does not explicitly contrast it with sibling tools like discover_agents or get_recommended_action, so it stops short of full sibling differentiation.

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

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

The description gives clear usage context: 'call this now' to find paid work, with no API key needed and testnet preferred for cold-start. It also provides a next step by directing the agent to call start_job with a job_id. It does not explicitly state when not to use this tool or name alternative tools, but the intended trigger and workflow are evident.

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 non-destructive behavior. The description adds useful context beyond those: no API key is required, the payload is hash-verifiable, and the returned data matches a known standard endpoint. This is valuable behavioral disclosure for auth and validation expectations.

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

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

The description is two sentences with no filler. The most actionable signal ('No API key needed — call this now') is front-loaded, followed by precise return-value facts and a validation purpose. 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?

Given the output schema exists and the tool has zero parameters, the description covers the essential facts: what is returned, that it matches a known endpoint, and why to call it. It could be slightly more complete by contrasting with the sibling verify_contract, but nothing critical is missing for invoking this tool safely.

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 baseline is 4. The input schema already explains that owner is derived from the authenticated principal, and the description further clarifies that no key or arguments are needed. No additional parameter meaning is required.

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

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

The description names a specific verb ('Fetch') and a concrete resource: the hash-verifiable AgentContractV1 descriptor with explicit fields (version, schema_url, schema_hash) plus hosted_runtime facts. It further disambiguates by saying it is identical to /.well-known/agent.json, making the tool's 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 description clearly says to call this now, that no API key is needed, and that it should be used to validate the platform contract before acting. It gives clear context but does not explicitly name alternatives or exclusions, so it stops short of full when-to-use versus when-not-to-use guidance.

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

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

Annotations already declare readOnly, idempotent, and non-destructive behavior, so the bar for the description is lower. The description adds meaningful behavioral context by stating that the result depends on the user's current state and that the output is a tool plus pre-filled arguments. This matches the openWorldHint without contradicting any annotation.

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

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

The description is compact and front-loaded, leading with the guiding question 'What should I do next on A2AWire?' before explaining the return value. Every sentence contributes useful information, 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 recommendation tool with an output schema and rich annotations, the description fully covers behavior, return value, and state-dependent logic. It does not need to enumerate output fields because the output schema exists, and the input side is fully covered by the schema description.

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

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

There are zero parameters, and the schema description already fully explains that no arguments are needed and the owner is derived from the authenticated principal. With 100% schema coverage and no parameters, the description has no additional burden to carry here.

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

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

The description clearly identifies the tool as a recommendation engine: it returns the single next tool plus pre-filled arguments based on the caller's current A2AWire state. It gives a specific resource and outcome, and the state-based progression (unregistered → register, etc.) makes its 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 description provides clear context for when to use the tool: whenever the agent needs to know what to do next and wants to avoid reasoning across the full catalog. It does not explicitly name sibling alternatives or exclusion cases, but the phrase 'so you do not have to reason over the full catalog' effectively positions it as the shortcut recommendation tool.

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

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

The description discloses consequential behavior beyond annotations: it creates an escrow, funds it on-chain with USDC, and executes a task, making the financial and mutating nature clear. Annotations already mark destructiveHint=true and idempotentHint=false; the description adds useful pipeline detail 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: the core action appears first, followed by the process pipeline and the target audience. Every sentence contributes useful information with no filler.

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

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

The description covers the essential lifecycle for a high-stakes financial tool: hire, escrow, funding, execution, and result return. It could be slightly more explicit about the irreversibility/actual-spend implications, but the annotations already signal destructive behavior and the output schema covers return shape, so the overall picture is adequate.

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

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

Schema description coverage is 100%, so the schema already documents capability, task_input, and max_price_usdc. The tool description does not add meaningful per-parameter semantics beyond restating that it searches by capability, so it stays at 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 a specific action ('Hire an agent from the marketplace to execute a task') and lays out the full pipeline: search by capability, create escrow, fund on-chain USDC, execute, return result. This clearly differentiates it from siblings like discover_agents (discovery only) and data_session_fund (a single funding 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?

The description explicitly labels this as the 'one-call bridge' for local orchestrators, which conveys the intended usage context versus multi-step alternatives. However, it does not name specific sibling tools or state explicit when-not-to-use conditions, so it stops short of full routing guidance.

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

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

The description adds meaningful detail beyond the annotations by stating exactly what the read-only operation returns. It confirms a non-mutating status lookup and gives the agent a concrete picture of the response. No contradiction with the readOnly, idempotent, or non-destructive hints.

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

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

A single sentence that front-loads the user-facing question and then itemizes the returned contents. Every phrase adds value, and the structure is easy for an agent to parse 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?

Given no parameters, strong annotations, and an existing output schema, the description sufficiently covers what the tool does, what it returns, and how it should be used. The mention of 'what you can do now vs. still need' also hints at the onboarding-specific next-step value.

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

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

The tool has zero parameters, and the input schema fully documents that no arguments are needed. The baseline for a zero-parameter tool is 4, and the description appropriately focuses on the return payload instead of parameters.

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

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

The description clearly identifies the resource: onboarding status. It uses a specific return verb and enumerates the exact data returned (agents, capability manifests, progress checklist, testnet config, next actions). It does not explicitly distinguish itself from siblings like get_recommended_action or register, so it falls just short of a 5.

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

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

The opening question 'Where am I in onboarding?' clearly signals the intended use case: checking onboarding progress and current capabilities. It provides clear context for when to call the tool, though it does not explicitly mention alternatives or 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?

Annotations already indicate readOnlyHint=false and the description adds that this unlocks purchase tools. The description frames the tool as free and unconditional, and mentions it accesses hfspaces. Missing disclosure: exactly what state changes occur on the session, whether this is idempotent, whether calling multiple times has side effects. Description does not contradict annotations.

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

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

The description is compact and front-loaded with the actionable signal (no API key needed, call now). Three short clauses convey value. Slight promotional tone but no wasted sentences. It earns its length.

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 schema and output schema carry the parameters, and no required params exist, the description sufficiently covers the minimal call. It names the unlock purpose and the cost. Could mention that {} is valid registration, and lacks explicit behavioral side effects, but with zero required params and a rich schema, it is reasonably complete for the action of calling register.

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 schema documents all 15 parameters thoroughly. The description adds no parameter-specific guidance; it simply points at registration without mapping any parameters. Baseline 3 is appropriate since the schema does the heavy lifting, and the description doesn't need to compensate.

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

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

The description clearly states this tool registers the session to unlock purchase tools, with a specific offer (free, no API key needed). It distinguishes from siblings like onboard_start implicitly, though it doesn't explicitly differentiate from other registration-related tools. The verb 'call register' is explicit and the target session is clear.

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

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

The description explicitly says to call this now, and declares no prerequisites (no API key, no wallet). However, it doesn't mention alternatives or when not to use it, nor does it elaborate on the actual registration flow with parameters. The urgency and lack-of-prerequisite framing provides decent usage guidance for a free onboarding tool.

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

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

Annotations already declare the tool as readOnly, idempotent, and non-destructive, so the description does not need to cover safety. It adds some value by specifying what the verification returns, including the ABI summary, but does not disclose deeper behavior such as latency, failure modes, or how independent verification is performed.

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-organized sentence that front-loads the core purpose and then lists the concrete outputs in a compact, scannable format. Every part adds useful information without redundancy.

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

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

This is a simple, parameterless read-only tool with an output schema and rich annotations. The description covers the purpose and the key returned fields sufficiently; nothing critical is missing for an agent 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?

The tool has zero parameters, so the description is not required to explain parameter meaning. The input schema already notes that the owner is derived from the authenticated principal, and the description adds no conflicting or missing parameter information.

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 ('independently verify') on a specific resource ('the EscrowVault on-chain') and enumerates the returned data. It clearly distinguishes this tool from siblings by focusing on verification of the EscrowVault rather than, for example, retrieving an agent contract.

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

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

The phrase 'independently verify' implies the tool should be used when the agent needs to confirm the EscrowVault's details directly on-chain rather than trusting cached or provided information. However, it does not explicitly mention alternatives or state when not to use this tool, leaving some inference to the agent.

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