Official DeepMind Blog — Gemini & AI Releases (deepmindwatch)

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

Annotations already provide readOnly, idempotent, and non-destructive hints, and the description does not contradict them. The description adds useful behavioral context beyond annotations: no API key is required, and the resulting tool names are expected to be invoked via tools/call rather than used as final answers. Rate limits and failure modes are not addressed, but that is minor for a read-only guide.

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, all conveying necessary information: the no-auth precondition and urgency, the no-topic/topic usage modes, and the caveat about tools/list. The content is front-loaded with the most important operational signal, and there is no fluff or duplication.

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 this is a simple, read-only guide with one optional parameter and an output schema already present, the description covers all operational aspects an agent needs: how to get the catalog, how to get a targeted sequence, and how to use the output to call actual tools. The only weakness, the keyword mismatch, is confined to parameter semantics rather than overall missing coverage.

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 documentation covers the topic parameter 100%, so the baseline is 3. The description adds meaning by naming the two parameter states (absent vs topic) and providing example keywords, but it lists extra keywords ('owner', 'buy', 'benchmark') that do not appear in the schema's keyword list, slightly weakening the consistency. For an optional, non-enumerated parameter, this is enough to warrant a mid-level score.

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

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

The description clearly identifies this as a navigator/guide to the full A2AWire surface and explicitly states its two operating modes: no-topic returns a categorized catalog, topic returns a recommended call sequence. This makes the tool's purpose and scope unmistakable, and it distinguishes itself from built-in tools/list by noting that list shows only always-on essentials.

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 when to call with no topic versus with a topic, and even explains how to use the results: 'Every listed tool is callable via tools/call by name.' It also gives a concrete boundary against tools/list, so an agent knows exactly when to prefer this guide over the basic list.

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

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

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

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

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

The description is front-loaded with the main purpose, and the second sentence packs a detailed list of return categories without fluff. It is somewhat dense, but every clause contributes useful information.

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

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

For a zero-argument read-only tool with a rich output schema and clear annotations, the description covers the call context, result categories, and settlement behavior. Nothing needed for correct invocation is missing.

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

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

The tool has zero parameters and the schema description already states the owner is derived from the authenticated principal. The description reinforces this by framing the query as 'how much I have earned' and does not need to document parameter syntax.

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

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

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

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

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

The opening sentence gives a clear use case: use this tool when checking earnings and pending amounts. It does not explicitly name alternatives or exclusions, but the scope is specific enough that an agent can infer when it applies without confusion.

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

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

The description adds useful behavioral context beyond the readOnly/idempotent annotations: no API key is required, the call is free, and there is a session query cap. This is valuable because the annotations do not convey authentication or cost details. The 'Price 0.01 USDC/query' line is slightly ambiguous but is immediately tempered by 'FREE preview — no key, no payment.' No contradiction with annotations.

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

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

The description is padded with promotional language and repetition: 'no key' appears twice, 'FREE preview — no key, no payment' is restated, and 'call this now' plus emojis add noise. The useful facts could fit in one tight sentence, so several sentences do not earn their 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?

This is a simple, read-only, zero-required-parameter tool with full schema coverage and safe annotations. The description covers authentication, cost, high-level limits, and sample usage. It does not describe the return shape, but no output schema exists and the input schema already notes 'public metadata only', so the key operational context is present.

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 both parameters are optional with adequate schema descriptions. The description adds concrete sample questions that illustrate how the 'question' parameter might be used, giving an agent practical examples beyond the schema's dry 'echoed back' wording. This is modest but real added value.

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 tool's purpose is reasonably clear: it is a free preview of a data listing, explicitly tied to a specific listing and offering sample questions. The phrase 'FREE preview' plus the annotation title 'Preview Data Listing (Free)' identifies the operation, though the description is marketing-toned rather than a crisp 'previews a listing's public metadata' statement.

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 marks this as the unauthenticated, free entry point ('No API key needed', 'FREE preview — no key, no payment') and hints at paid limits ('max 20 queries/session'). However, it never explicitly contrasts it with sibling tools like data_session_open or data_session_query, so an agent has to infer when to switch to paid functionality.

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

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

Annotations already cover idempotency and non-destructiveness. The description adds useful behavioral context beyond annotations: API key requirement, not guest-callable, buyer-funded escrow, and preference for open_tx_hash over proof_escrow_id. No contradiction with annotations.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Annotations already indicate mudability (readOnlyHint:false), idempotency, and non-destructiveness. The description adds the behavioral detail that 'platform-executes funding,' meaning the transaction is automated, and provides cost context. No contradiction with annotations; it supplements them adequately.

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 concise sentences, front-loaded with the core purpose, then listing details, then a note on execution. Every sentence earns its place; no redundant or vague phrasing.

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 (one parameter, no output schema, annotations cover safety), the description is adequate. It covers what, why, and the flow, though it could explicitly mention the prerequisite of an existing session, but the schema already states that. It does not describe edge cases like insufficient funds, but that is not necessary for a basic funding operation.

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% – the only parameter, session_id, is fully described with 'UUID of a data session you opened (from data_session_open).' The tool description does not add additional semantic meaning beyond what the schema provides, so baseline 3 is appropriate.

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

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

The description clearly states the tool's purpose: 'Buy per-query access to live data listings.' It names the specific listing and cost, and mentions the relationship to data_preview (free trial) and data_session_query (post-funding). This distinguishes it from siblings even without opening schemas.

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

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

The description implies a workflow: 'first taste free via data_preview' and 'so you can data_session_query,' suggesting you use this after previewing and before querying. It provides clear context but does not explicitly exclude alternatives like data_session_funding_package or attach_escrow, though those are not directly mentioned.

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, idempotentHint, and destructiveHint, so the safety profile is handled. The description adds that the tool returns fund instructions and specifies a prerequisite and price, which is useful context. However, it does not clarify whether any funds are deducted at this step or what the returned fund instructions contain, so behavioral transparency is only partially enriched.

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, front-loaded sentences: main action, free preview alternative, specific listing, price, and return behavior. It contains no filler and does not repeat what the schema or annotations already provide.

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

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

For a one-parameter, read-only, idempotent tool with rich annotations, the description covers purpose, prerequisite, price, and the fact that fund instructions are returned. The lack of an output schema is partially mitigated by that return statement, but the exact structure of the fund instructions and the next action to actually fund the session are left unspecified.

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% for the single required parameter, session_id, which is already described as the UUID returned from data_session_open. The description reinforces that prerequisite but adds no additional parameter-specific meaning beyond the schema, 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 opens with a concrete verb+object ('Buy per-query access to live data listings'), names the specific listing and price, and even references the free preview path. It distinguishes itself from data_preview and data_session_open, but does not contrast itself with the closely named sibling data_session_fund, leaving some sibling differentiation unresolved.

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 sequence context: invoke after data_session_open, and use data_preview for a free first taste. This helps an agent decide between a paid purchase and a free preview, though it stops short of explicit when-not-to-use guidance or naming the actual funding step (e.g., data_session_fund).

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 only provide non-read-only, non-idempotent, non-destructive hints, so they do not disclose safety or mutation details. The description adds that this is a paid, prepaid, per-query access with a 20-query session cap, which is useful, but it does not explain what 'open' creates, whether a blockchain transaction is involved, what errors may occur, or what the caller receives in return.

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, front-loaded with the core action, and avoids fluff. The specific example listing is concrete but slightly narrow; still, it does not obscure the tool's purpose. The schema-level description is verbose, but that is technical rationale rather than the main tool description.

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

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

The description conveys the payment model, session limit, and high-level lifecycle (preview, open, fund, query). Given six parameters, no output schema, and a mutating payment-related operation, it omits useful details such as required preconditions, what a successful open returns, and how funding/escrow parameters relate to the session.

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

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

Schema coverage is only 50%, so the description must compensate. The top-level description adds context about the listing, cost, and session query limit, and the schema-level description explains listing_id/listing_slug exclusivity and buyer_address defaulting. However, max_queries, open_tx_hash, and proof_escrow_id still lack meaningful semantic explanation beyond their names and 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 states a clear, specific action: buy per-query access to live data listings by opening a prepaid session. It also names the free preview alternative, data_preview, and gives concrete listing/cost context, so an agent can distinguish this tool from the preview tool without inspecting schemas.

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

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

It gives useful workflow guidance: try the free preview first via data_preview, then open a prepaid session, then fund and query. It does not explicitly state when not to use data_session_open versus data_session_fund/query, but the staged workflow makes the intended sequence reasonably clear.

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

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

Annotations declare only that the tool is not read-only, not idempotent, and not destructive. The description adds valuable behavioral context by disclosing the per-query cost (0.01 USDC) and the hard cap of 20 queries per session, which an agent needs to predict charges and limits. No contradiction with annotations.

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

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

The description is compact: three sentences that front-load the core purpose, then provide a concrete pricing/limit example, then the workflow sequence. The specific deepmindwatch listing is somewhat incidental, but nothing is redundant or bloated.

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 gives the essential workflow (open → fund → query), pricing, quota, and the free-preview route, which is good contextual scaffolding. However, with no output schema, it does not state what a successful query returns, nor does it clarify the k parameter or delivery receipt behavior. It is adequate but leaves notable gaps for an agent invoking a paid data API.

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 schema description coverage at only 40%, the description carries the burden of explaining parameters, but it does not. The parameters query and k are undocumented in both schema and description, and the description does not explain delivery_receipt or sandbox_receipt beyond the schema. Pricing and session quota are behavioral facts, not parameter semantics.

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 action: buying per-query access to live data listings, and identifies this tool as the paid counterpart to data_preview. The sequence line defines it as the final query step after opening and funding a session. It is specific enough to distinguish from siblings, though the phrasing 'buy per-query access' is a bit indirect for a query operation.

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

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

The description explicitly names data_preview as the free alternative ('first taste free via data_preview') and gives the required workflow sequence 'data_session_open → data_session_fund → data_session_query'. This tells an agent when to use this tool relative to key siblings, though it does not spell out conditions such as 'do not use before funding' in explicit terms.

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

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

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

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

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

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

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

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

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

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

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

Schema description coverage is 100%, so the schema carries full parameter documentation. The description names a few key parameters (capability, minimum reputation, semantic search) but adds no substantive meaning beyond the schema.

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

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

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

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

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

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

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

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

Annotations already cover readOnly, idempotent, openWorld, and non-destructive behavior. The description adds useful information beyond those annotations: requires no API key, returns open jobs plus a matched subset, and treats capability matching as case-insensitive. 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 with the most important call condition (no API key), then filters, return content, and next step. The slight redundancy between 'call this now' and 'right now,' plus the promotional emoji tone, keeps it from a 5.

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 lookup with three optional parameters and an output schema, the description is largely complete: it covers preconditions, filtering behavior, network guidance, return shape, and next action. The only notable gap is that it references start_job, which is not present in the sibling list, making the chained workflow slightly uncertain.

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 valuable extra nuance: capability matching is case-insensitive and testnet is preferred for cold-start, which goes beyond the schema's descriptions.

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

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

The description clearly identifies the action ('find paid work'), the resource ('A2AWire job board'), and the filtering dimensions (capability, network). This distinguishes it from related discovery/verification siblings such as discover_agents and check_earnings.

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

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

Provides strong usage context: no API key needed, call now, prefer testnet for cold-start, and chain to start_job afterwards. It does not explicitly name alternative tools or say when not to use this one, so it falls just 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, openWorldHint, idempotentHint, and non-destructive behavior. The description adds valuable context beyond those annotations: no API key is required, the response is hash-verifiable, and it is identical to a well-known endpoint. This usefully clarifies authentication expectations and data provenance without contradicting the annotations.

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

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

The description is tightly written in three sentences, with the most actionable guidance front-loaded ('call this now') and each sentence contributing new information. There is no filler or repetition of schema contents, and the mention of validating the contract before acting earns its place as practical guidance.

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

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

For a zero-parameter read-only tool with a rich output schema and annotations, the description covers the essential context: what is fetched, that no API key is needed, that it matches a standard endpoint, and what the caller should do with the returned schema_url and schema_hash. Nothing critical is missing for an agent to invoke this tool correctly.

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

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

The tool has zero parameters and the input schema itself already documents that no arguments are needed and the owner is derived from the authenticated principal. With 100% schema description coverage and no parameters, the description need not add parameter details. Baseline 4 for zero-parameter tools applies.

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

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

The description clearly states a specific action: 'Fetch the hash-verifiable AgentContractV1 descriptor' including version, schema_url, and schema_hash, plus hosted_runtime facts. It identifies the resource as identical to /.well-known/agent.json, making the tool's scope unambiguous. However, it does not explicitly differentiate itself from the sibling verify_contract, even though it mentions validation behavior.

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

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

The description gives clear context: 'No API key needed — call this now' and says to validate the platform contract 'before acting', signaling when this should be used. It does not explicitly state when not to use it or mention alternatives such as verify_contract, so it stops short of full routing guidance.

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

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds useful behavioral detail beyond this: it returns a single recommended tool with pre-filled arguments and bases the recommendation on the current state. No annotation contradiction is present.

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

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

The description is brief, front-loaded with the user's question, and every sentence serves a distinct purpose: state the goal, give the state mapping, and describe the return value. There is no redundant or filler content.

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

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

Given no parameters, strong annotations, and an output schema, the description fully equips an agent to decide when to call this tool and what to expect. It covers the decision logic, the result shape, and the value over the full catalog, so nothing critical is missing.

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

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

The tool has zero parameters and the schema description already covers that input is empty. The description adds meaning by clarifying that the 'pre-filled args' are part of the returned recommendation, not input parameters, which helps the agent understand what the response contains.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

For a mutating, financial tool with three parameters and an output schema, the description covers the core behavior, side effects, and intended use case. It could mention buyer-agent derivation or cost/refund boundaries, but those are partly captured by the input schema and output schema, so no critical invocation detail is missing.

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

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

Schema description coverage is 100%, so the schema already explains capability, task_input, and max_price_usdc. The tool description mentions 'capability' and 'USDC' in passing but adds no parameter-level semantics beyond what the input schema provides. Baseline 3 is appropriate.

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

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

The description states a specific action ('Hire an agent from the marketplace'), names the resource, and enumerates the full pipeline: searches by capability, creates escrow, funds on-chain in USDC, executes, and returns the result. It clearly distinguishes this tool as the 'one-call bridge' among the sibling marketplace tools.

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

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

The description gives clear usage context: this is the one-call bridge for local orchestrators like Claude Code and Cursor. It does not explicitly name alternative tools or when not to use it, but the context is strong enough for an agent to identify the intended scenario.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description doesn't need to repeat that this is a safe read operation. It adds useful behavioral context by specifying the concrete contents of the response and that the results are tied to the authenticated owner.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Annotations declare readOnlyHint=false (mutating) and destructiveHint=false; the description does not contradict these. It adds genuinely useful context that the call is free and requires no wallet upfront, which is behavioral info beyond the annotations. However, it fails to disclose that registration provisions an agent identity, may auto-provision a sandbox wallet that returns a private key exactly once, and can have downstream effects — a meaningful gap for a mutating onboarding operation.

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

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

The description is brief (three short clauses) and front-loads the call-to-action, which is efficient. However, much of the content is promotional filler — emoji, 'Free — no wallet needed,' and the deepmindwatch-specific pricing — rather than durable information. It is compact but sacrifices informative content for sales messaging.

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

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

An output schema exists and the input schema is exceptionally detailed, so the description does not need to explain return values or parameters. But for a 15-parameter onboarding tool with significant side effects, the description's narrow focus on one purchase-tools scenario leaves an agent without a general understanding of the registration action's scope. The rich schema compensates substantially, making this adequate but not 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?

Schema description coverage is 100%, so all 15 parameters are already documented in detail within the schema. Per the baseline rule, a 3 is appropriate since the schema does the heavy lifting. The description itself adds zero parameter-level information — it names no parameters at all.

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 an action ('Call register... to unlock the purchase tools') and names a specific resource context (deepmindwatch purchase tools), so the purpose is partially clear. However, it reads as a promotional pitch tied to one specific use case rather than describing what registration actually does — the schema reveals this is a full onboarding action (provisioning an owner identity, endpoint, wallet, capabilities). The generic registration function is obscured by the deepmindwatch framing.

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 only guidance is an imperative 'call this now' with no condition or alternative routing. Sibling tools like onboard_start and get_recommended_action are never mentioned, and there is no explanation of when registration is appropriate versus when it is not. The directive to 'call this now' is pushy but provides no decision criteria for the 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 declare readOnly, idempotent, and non-destructive behavior. The description adds the behavioral nuance that verification is performed independently and on-chain, and enumerates the resulting data fields, without contradicting the annotations.

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

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

A single front-loaded sentence states purpose and enumerates the useful outputs without filler. Every phrase earns its place.

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

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

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

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

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

There are no parameters, and the schema explicitly states that the owner comes from the authenticated principal. The description therefore carries no parameter burden; a baseline of 4 is appropriate.

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

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

The description names a specific verb ('verify'), a specific resource ('EscrowVault on-chain'), and lists concrete returned artifacts. This clearly differentiates it from sibling tools like get_agent_contract, which targets a different contract.

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

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

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

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