GitHub Platform Changelog — buy per-query in-session (githubchangelog)

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?

Annotations already establish readOnlyHint and non-destructive behavior. The description adds useful, non-redundant operational details: no API key required, price per query, max 20 queries/session, and that it is a guest callable preview. 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 repeated marketing language: 'No API key needed', 'FREE preview', 'no key, no payment', and 'Try one of the sample questions now'. It is long and promotional without first stating the tool's purpose.

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?

There is no output schema, so the description should explain what the preview returns, but it only provides pricing, quotas, and example questions. An agent can guess it returns sample data, but the response format remains 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?

The input schema already fully describes both optional parameters, so the baseline is 3. The description gives concrete sample questions that could guide the `question` parameter, but it never explicitly links them to the parameter names, and `slug` is not explained beyond what the schema already says.

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' but never clearly states what the tool does or what it returns. It is dominated by a specific listing, pricing, and sample questions; the actual functional purpose is left mostly to the title and the schema description.

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

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

There is no guidance for when to use this tool versus siblings like data_session_query, a2awire_guide, or find_paid_work. 'Call this now' is an instruction, not a usage decision criterion.

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?

The description discloses that this is a paying action ('USDC/query'), that it is platform-executed, and that funding enables subsequent queries. Given annotations already mark it non-read-only and non-destructive, the description adds meaningful billing/workflow transparency 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 tool's core purpose is front-loaded in the first sentence, followed by a concrete listing example and the free-preview pointer. The wording is compact and scannable, though the inline listing format is slightly dense.

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 explains the action, the cost model, a concrete listing, and the follow-up query step. An agent has enough context to invoke it correctly with a session ID from data_session_open.

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 fully documents session_id as the UUID from data_session_open, and the description reinforces workflow by referencing data_session_query. Since schema coverage is 100%, the description does not need to add much; it adds no new parameter-level detail.

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 ('Buy per-query access') and a concrete resource (a funded data session), and it situates the tool relative to data_preview and data_session_query. It is clear, though it does not explicitly distinguish itself from sibling funding tools like data_session_attach_escrow.

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

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

It gives useful workflow context: try data_preview first for free, then fund the session so data_session_query can be used. It does not state when not to use the tool or compare against related funding alternatives, but the practical context is 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?

The description says 'Buy per-query access' while the annotations declare `readOnlyHint: true`, `openWorldHint: false`, and `idempotentHint: true`. This conflicts with an agent's expectation that a purchase-like action has side effects. The closing phrase 'Returns fund instructions' could be read-only, but the description is too ambiguous to reconcile the claim of buying with the annotation data. Neither behavior nor annotation field says whether the tool executes or only causes a payment request.

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

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

The description is short and front-loaded with the main action, then gives a specific listing and a return statement. The promotional phrase 'first taste free via data_preview' is mildly unnecessary, but it is not bloated and the description remains easy to skim.

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?

It covers the essential sequence, cost, and target listing, but leaves the meaning of 'fund instructions' unexplained. Since there is no output schema and the action/side-effect status is ambiguous, the agent is not adequately equipped about the exact invocation behavior or the next step.

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 for the single parameter is already 100%; the schema explains that `session_id` is a UUID from `data_session_open`. The description adds little beyond restating that the instruction comes after `data_session_open`, so the baseline of 3 is appropriate.

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

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

The description clearly states a specific verb and resource: buy per-query access to live data listings, and it names the target listing and pricing. It also names data_preview as a free alternative. However, it does not distinguish itself from the similarly named sibling `data_session_fund`, so an agent may still be uncertain which funding-related tool to pick.

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

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

It gives a clear sequence cue ('after data_session_open') and routes free-trial users toward data_preview. It does not explain when to avoid this tool, nor how it differs from data_session_fund or data_session_attach_escrow. That is useful but incomplete 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 provide no hints (all false), so the description carries the burden. It discloses that this is a purchase operation and that sessions are prepaid, and mentions per-query cost and max queries. However, it does not explain side effects (e.g., session creation, wallet deductions), response behavior, or idempotency beyond what annotations imply. It is adequate but not rich.

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, efficient sentence with a concrete example. It is front-loaded with the core purpose and avoids padding. No waste, though it could arguably drop the specific listing example for generality.

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

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

For a tool with six optional parameters and no output schema, the description conveys the core action and workflow but omits details like session-handle handling, funding prerequisites, and error cases. The schema covers some parameter semantics, and siblings imply the rest, but a complete description would clarify what 'opening a session' returns and how to reference it later.

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 description makes no mention of any parameters. The schema describes three of six parameters (listing_id, listing_slug, buyer_address) and includes an extensive explanatory note, but the description adds zero parameter-level guidance. With only 50% schema coverage, this is a notable gap.

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 ('Buy per-query access') and a clear resource ('live data listings'), distinguishes itself from the free preview via data_preview, and gives a concrete example listing with pricing. This is unambiguous and differentiates from siblings like data_preview, data_session_fund, and data_session_query.

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

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

It explicitly suggests using data_preview for a free taste before buying, and outlines the intended sequence ('Open a prepaid session, then fund and query'). While it does not name specific sibling tools as alternatives, the workflow implication clearly positions this as the opening step, not the funding or querying step.

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

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

Annotations already mark the tool as non-read-only, non-idempotent, and non-destructive, so the description does not need to repeat that. It adds useful behavioral context: per-query billing at 0.01 USDC, a maximum of 20 queries per session, and a required preceding funding step. It does not disclose failure modes or what happens on insufficient funds, but the added billing and session constraints are valuable.

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, dense, and without filler. It front-loads the core purpose, then gives listing specifics and the session sequence in compact form. The listing-specific detail is arguably a minor distraction, but overall the structure is efficient and scannable.

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

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

The tool has five parameters, no output schema, and thin annotations, so the description must provide enough context for correct invocation. It supplies the required session sequence and billing limits, but omits parameter semantics and any description of the query response or result shape. This leaves meaningful gaps for an agent deciding how to form a valid query.

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

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

With only 40% schema description coverage, the description carries a responsibility to explain unclear parameters. It does not mention k, sandbox_receipt, or delivery_receipt, and only vaguely references session flow. The schema does describe session_id, sandbox_receipt, and delivery_receipt, but key parameters like query and k remain under-explained across both sources.

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 clear action ('Buy per-query access') and ties it to a specific listing and session-based sequence. It is distinguishable from sibling tools like data_session_open and data_session_fund by being positioned as the final query step. The slight ambiguity is that 'buy per-query access' could sound like a purchase/funding action rather than a query execution.

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 gives the sequence 'data_session_open → data_session_fund → data_session_query' and mentions data_preview as the free first taste. This provides enough contextual guidance on when this tool is appropriate relative to its siblings, though it does not state explicit exclusions 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 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?

The description discloses that the call is free, requires no key/wallet, and unlocks paid tools on this session. However, it does not explain the actual registration effect (creating a session identity, storing an agent key, overwriting an existing registration) or any state changes. With readOnlyHint=false, the agent needs to know what side effects occur; the title mentions 'Get API Key' but the description omits it.

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 key instructions are front-loaded ('No API key needed — call this now', 'Free — no wallet needed'). Some promotional flourishes (emojis, parenthetical product name, per-query price) are extraneous but do add economic context. No burying of 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?

In a small toolset with onboard_start siblingcustom, the description gives the essential when/why (free, before purchase tools, session-scoped) and the schema covers parameters. Missing specifics about side effects such as whether a key is returned or stored, and the 15 optional parameters are not summarized, but for an unconditional 'call now' flow the core usage is clear.

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?

All 15 parameters are already described in the schema with detailed semantics (e.g. spending cap intent, endpoint vs owner key). The description adds the key fact that all parameters can be omitted for a free default registration ('No API key needed — call this now'), which reduces decision-making burden. It doesn't repeat schema details, so reasonable value above high 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 names a specific action — call 'register' on this session — and a clear outcome: unlocking purchase tools for a specific changelog product. It also states the prerequisite (no API key, no wallet) and the pricing. It loses the top score because the mechanism of registration (creating an account, storing parameters) is not explicitly stated and the infomercial tone obscures what 'register' produces.

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 it now, on this session, with no API key or wallet needed, to unlock purchase tools. It doesn't explicitly contrast with sibling tools like onboard_start or explain when not to call it, so it stops short of full differentiation guidance.

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

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds the behavioral nuance that verification is performed independently and on-chain, and enumerates the resulting data fields, without contradicting the annotations.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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