MCP Server Discovery — new model-context-protocol repos ($0.01/query)

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is known. The description adds value by stating 'No API key needed' and explaining that listed tools are callable via tools/call by name, which is not in annotations. It does not contradict annotations.

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

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

The description is somewhat long but front-loaded with 'No API key needed — call this now' and every sentence conveys actionable info: modes, examples, and a tour command. No fluff, though it could be tightened slightly.

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

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

With an output schema present, return values are covered. The description covers usage, alternatives, and even an external quickstart tour, making it fully adequate for an agent to invoke correctly without additional 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?

Schema description coverage is 100%, but the tool description goes further by listing additional topic keywords (e.g., 'owner', 'buy', 'benchmark') not present in the schema, and explains the default behavior. This adds meaning beyond the schema, so a 4 is warranted.

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

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

The description clearly states this is a 'Navigator for the full A2AWire tool surface' and explains two distinct modes: returning a catalog (no topic) or a recommended call sequence (with topic). It distinguishes itself from tools/list by noting the difference in scope, so an agent can immediately tell this apart from siblings.

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

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

Explicitly says when to call with no topic vs with a topic, and contrasts with tools/list: 'Every listed tool is callable via tools/call by name — tools/list shows only always-on essentials.' This gives clear routing and excludes alternatives.

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

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

Annotations already declare 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context: no API key required, no payment required, a 20-queries-per-session limit, and the fact that it is a free preview. The 'Price 0.01 USDC/query' line is somewhat ambiguous against 'FREE preview,' but it does not contradict the annotations.

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

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

The description is padded with marketing language, emojis, repeated 'no key/no payment' statements, and a direct call-to-action ('Try one of the sample questions now'). It front-loads the key message but is not tight or information-dense. Several sentences could be removed without losing functional 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 simple, read-only preview tool with no output schema, the description covers access, cost, and usage examples. However, it does not clearly state what the tool returns, and the combined 'Price 0.01 USDC/query' with 'FREE preview' creates ambiguity. The schema's mention of 'public metadata only' helps, but the main description leaves the response semantics under-specified.

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 parameters, so baseline is 3. The description contributes sample questions that illustrate the 'question' parameter's intent, but it does not add meaningful guidance about the 'slug' parameter or how to choose a different listing. It adds some value but does not go beyond the schema meaningfully.

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 free preview of a data listing and even gives sample questions to ask. It implies a read-only preview action, though it never explicitly states 'returns public metadata' in the main description. The 'FREE preview' phrasing helps distinguish it from paid data-session tools, but the distinction is implicit rather than named.

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 direct usage context: no API key is needed, it is free, and the user should try sample questions now. This strongly signals when to call the tool. However, it does not explicitly mention alternatives like data_session_query or state when NOT to use this tool, 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 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 communicate mutability (readOnlyHint=false), idempotency, and non-destructiveness. The description adds some context—'platform-executes funding' and per-query pricing—but does not go deeper into side effects, such as what happens if the same session is funded twice. There is no contradiction with the annotations.

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

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

The description is short, front-loaded with the action, and includes a useful pointer to the free preview alternative. The listing-specific detail about ghmcp and the 0.01 USDC/query pricing is concrete but somewhat narrow for a generic funding tool; still, the overall structure is tight 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?

For a simple one-parameter tool, the description plus annotations provide enough context to invoke it correctly: it explains what the tool does, how it relates to preview and query, and the session_id schema covers the only input. It does not describe the return value, but no output schema exists and the tool's success condition is fairly clear from the funding-to-query flow.

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

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

Schema description coverage is 100%: session_id is fully documented as the UUID of a data session opened via data_session_open. The description adds functional context but does not need to repeat parameter details since the schema already covers them. This matches the baseline for 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 states a specific action: 'Buy per-query access to live data listings' and 'Platform-executes funding so you can data_session_query.' It clearly identifies the resource as a data session and ties into the preview/query workflow. It does not, however, explicitly distinguish itself from data_session_funding_package or data_session_attach_escrow, which appear as siblings.

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

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

The description provides clear sequence guidance: first taste free via data_preview, then fund the session, then use data_session_query. This is useful when-to-use context relative to two sibling tools. It does not explicitly say when not to use this tool or when to prefer data_session_funding_package or data_session_attach_escrow.

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

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

Annotations already declare readOnlyHint/idempotentHint, so the safety profile is covered. The description adds that the tool returns instructions rather than executing a payment, and includes listing specifics. However, the verb 'Buy' may imply a state-changing purchase unless read together with 'Returns fund instructions', creating ambiguity that a clearer description would resolve.

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, each serving a purpose: the value proposition, the specific listing/price, and the postcondition/output. The most important use context is front-loaded.

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 tool, the description is mostly sufficient, but it returns only 'fund instructions' without specifying the instruction format or the next step (e.g., data_session_fund). Since there is no output schema, this vagueness is a gap.

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

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

Schema description covers the single session_id parameter at 100%, explaining it is a UUID from data_session_open. The tool description reinforces the dependency on an opened session but does not add new parameter-level 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?

States a clear action ('Buy per-query access to live data listings') and a concrete output ('Returns fund instructions'), and references related workflow tools (data_preview, data_session_open). However, it does not differentiate from sibling data_session_fund/attach_escrow, so an agent could confuse which purchase-related step this is.

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?

Gives an implicit workflow: try data_preview for free, open a data session, then call this for fund instructions. It does not explicitly state when NOT to use this tool or how it differs from data_session_fund / data_session_attach_escrow, leaving the alternative selection to inference.

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

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

Annotations are sparse, so the description carries the burden. It discloses the paid nature (0.01 USDC/query), the per-session cap (max 20 queries/session), and the prepaid-session model—important behavioral context beyond readOnly/destructive hints. It does not warn about non-idempotency, but no annotation is contradicted.

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 core purpose. The listing example and pricing are compact and useful for a concrete understanding, though the 'ghmcp' product detail is slightly specific noise.

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 paid, multi-step, 6-parameter tool with no output schema, but the description does not reveal what the open-session call returns, how the returned session is used by the fund/query siblings, or that exactly one of listing_id/listing_slug is required. Some of this appears in the schema, but the description alone is incomplete 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?

Schema description coverage is only 50%, and the description does not meaningfully compensate. It adds pricing and a max-query cap, but it does not explain open_tx_hash or proof_escrow_id, and the 'max 20 queries/session' statement can be read as conflicting with the schema's max_queries maximum of 50.

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 to live data listings' and 'Open a prepaid session'—and distinguishes it from the free data_preview path and the later fund/query steps. It is clear, though it relies on implied lifecycle wording rather than explicitly naming the sibling tools it is not.

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 usable context: use data_preview for the first free taste, then open a prepaid session, then fund and query. This communicates the intended lifecycle, but it does not explicitly name data_session_fund or data_session_query or state when NOT to use this tool.

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

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

With all annotations false (no read-only, idempotency, or safety hints), the description carries the disclosure burden. It adds genuinely useful behavioral context: the 0.01 USDC per-query cost and the 20-queries/session cap, which signal that this is a fund-consuming, non-idempotent operation. However, it omits failure/refund behavior and the receipt-signing mechanics tied to sandbox_receipt and delivery_receipt, which matter for a paid call.

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 tight sentences with no filler: the core idea is front-loaded, the listing specifics (ghmcp, price, cap) occupy one sentence, and the workflow sequence another. The only structural weakness is that the 'Buy' framing in sentence one is slightly misleading, so the opening is not as accurate as it could be.

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 paid, non-idempotent tool in a three-step flow with five parameters and no output schema, the description covers the workflow position and cost economics well. But it leaves significant gaps: the meaning of k, the delivery_receipt flow, and any sense of what the query returns or what happens on failure. It is adequate for navigating the sequence but incomplete for invoking the tool correctly with all parameters.

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

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

Schema description coverage is only 40%, below the 50% threshold, so the description must compensate for the undocumented k, query, and delivery_receipt parameters — it does not. The description is entirely about workflow, pricing, and the listing; it adds nothing about what any of the five parameters mean, leaving the agent dependent on a sparse 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 positions the tool via the sequence 'data_session_open → data_session_fund → data_session_query' and references the data_preview sibling, so an agent can roughly place it. However, the opening verb 'Buy per-query access' mischaracterizes the operation — the schema's own description says 'Run a prepaid query against a funded data session,' and purchasing is actually data_session_fund's role. The core action (running a query against a session) is implied by the sequence and name but never stated plainly.

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 explicit three-step sequence tells the agent that this is the final step, to be used only after data_session_open and data_session_fund. The phrase 'first taste free via data_preview' additionally routes the agent to the free alternative before paying. It lacks an explicit 'do not call before funding' exclusion, but the ordered workflow makes that condition strongly inferable.

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 provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds useful behavioral context: no API key required, case-insensitive capability matching, and a matched subset of results for the agent's skill. 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 and front-loaded with the most actionable instruction ('call this now'). It is slightly repetitive with 'right now' appearing twice, but every sentence serves a purpose: prerequisite, purpose, filters, output, and next step.

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 board-search tool with rich annotations, an output schema, and fully documented parameters, the description covers purpose, prerequisites, filtering behavior, result type, and the follow-up action. Nothing essential is missing.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds value by noting capability matching is case-insensitive and reinforcing the testnet cold-start preference, which goes slightly beyond the schema text.

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?

States a specific verb and resource: 'Find paid work your agent can do right now on the A2AWire job board.' It also clarifies the return behavior ('open jobs plus a matched subset'), which clearly distinguishes this from earnings or onboarding siblings like check_earnings or register.

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

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

Explicitly says to call this now and that no API key is needed, and recommends using testnet for cold-start. It names the follow-up tool (start_job) but does not mention alternatives or when not to use it, so it stops short of full exclusion guidance.

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

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

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 only indicate this is not read-only, not idempotent, and not destructive, so the description carries the burden of explaining side effects. It adds 'no API key needed' and 'no wallet needed', but it does not disclose that registration creates an agent, may auto-provision a wallet, or that the registration becomes permanent. The 'unlock' language hints at a state change but never explains what actually happens.

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

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

The description is short and front-loaded with a clear call-to-action, so it is structurally concise. However, it spends its limited space on marketing language ('✅', 'call this now') rather than informative content. It is appropriately sized but not optimally useful.

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?

Despite having an output schema and rich parameter documentation, the description does not explain what register does, what prerequisites exist, or what side effects to expect. For a 15-parameter onboarding tool with no required fields, the description should at least orient the agent to the tool's purpose and typical usage. It is far from 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 the schema already documents all 15 parameters thoroughly. The description adds no parameter-level meaning beyond saying 'no wallet needed', which is consistent with the optional wallet fields. Baseline 3 is appropriate because the schema does the heavy lifting.

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

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

The description is a promotional call-to-action ('call this now', 'unlock the purchase tools') rather than a functional statement of what register does. It never states that this tool registers/onboards an agent or returns an API key, which the title and schema imply. It does name a resource ('purchase tools for ghmcp') but the core action is left to inference.

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 says to call it now to unlock purchase tools, which implies one use case, but it gives no when-to-use versus alternatives. It does not mention onboard_start or any other sibling, nor does it state when register should not be used. The guidance is essentially 'call this now' with no decision framework.

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.