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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety bar is low; the description still adds real context beyond them by stating no API key is required and by disclosing that the optional tour is a network download gated on user approval. The audit-first framing (fail-closed && chain, verify digest, inspect the saved file, run only after explicit approval) is genuine behavioral disclosure rather than restated annotation. It stops short of describing what the returned catalog/sequence actually contains, but that is covered by the output 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?

The first three sentences are tight, front-loaded, and carry everything an agent needs to choose and call the tool. The remaining majority of the text is a multi-line curl/shasum/less shell snippet with embedded comments, which is bulky for a tool description and pushes the payload well past its useful size. The core guidance survives, but the tour block is disproportionate.

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 and a single optional parameter, the description only needs to explain routing and call behavior, and it does that fully — including how to invoke the tools the catalog returns. The only gap is that it never says what the catalog entries or sequences look like, which the output schema presumably covers, so this is close to complete for a low-complexity navigator.

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

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

Schema description coverage is 100% and the single optional topic parameter is fully documented there, including that omission yields the full catalog and a keyword yields a call sequence. The description's keyword list is largely a duplicate and even drifts slightly (adds sell/buy/benchmark, omits sell's placement consistency), so it adds little meaning beyond the schema. 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 concrete verb and resource — a navigator that returns either a categorized catalog of callable tools or a recommended call sequence for a named flow. It also distinguishes itself from the sibling-facing surface by explaining that tools/list only exposes always-on essentials, so an agent knows why this tool exists alongside the others.

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 explicit branching instructions: call with no topic to get the catalog, or pass one of the listed keywords to get a flow sequence. It also states the cross-tool rule that every listed tool is callable via tools/call by name, which resolves the otherwise obvious 'these tools aren't in tools/list' confusion — that is when-to-use guidance no sibling provides.

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

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

Annotations already declare readOnly, idempotent, and non-destructive, and the description reinforces "Read-only." It adds genuine context beyond the annotations: where earnings settle on release (owner withdrawal address) and the special case of rooms-register-minted agents whose funds go to a platform-custodied testnet wallet tagged payout_custody: platform_testnet. That settlement/custody nuance is exactly the kind of behavioral detail an agent cannot get from 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?

Purpose is front-loaded in the first clause, with the return inventory and settlement caveat following. The long enumeration of returned values is somewhat redundant with the output schema, but it is dense rather than padded.

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, the description need not explain return values, yet it usefully flags the payout_custody edge case that affects interpretation of results. Combined with the read-only annotation set, an agent has enough to call and interpret this correctly; only the when-to-use guidance is thin.

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 takes zero parameters, so the baseline is 4. The description correctly says nothing about arguments, and the schema itself explains that the owner is derived from the authenticated principal.

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?

Opens with a specific verb and resource — "Check how much I have earned and what is pending" — then enumerates exactly what the response covers (lifetime USDC earned, pending amounts, unclaimed rewards, payout balance, buyer spend, reputation). No sibling tool in the list overlaps with this scope, so an agent can select it unambiguously.

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

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

Usage is only implied by the verb "check" — there is no explicit statement of when to call this versus anything else, nor any prerequisite or exclusion. In practice no sibling is a close alternative, so the risk is low, but the description does not do the routing work itself.

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, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds useful operational facts (no API key, no payment, max 20 queries/session), but the embedded 'Price 0.01 USDC/query' line sits ambiguously next to 'FREE preview' and can leave an agent unsure whether this specific call incurs cost.

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 text is marketing copy rather than a tool spec: emoji, a duplicated no-key/no-payment claim, a call-to-action, and pricing/rate-limit details interleaved with a single-listing example. The actual purpose is not front-loaded and the reader must parse past promotional filler to learn what the call does.

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 zero required parameters and a fully described schema this is a simple tool, but there is no output schema, so the description should say what a preview returns (the schema blurb's 'public metadata only' never appears in the description). An agent knows it is free and safe but not what payload to expect.

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

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

Schema coverage is 100%, so both optional parameters (slug, question) are already documented, including the routing default for slug. The sample questions give a flavor of what 'question' accepts, but no additional semantics or constraints are added beyond the schema, so the baseline of 3 applies.

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

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

The description names a concrete data source ('ghtrend: fast-growing new GitHub repositories') and calls itself a 'FREE preview', but it never states the verb clearly — that this tool returns a sample of a listing's public metadata. The single-listing example also muddies whether the tool is generic or specific to ghtrend, making it hard to distinguish from siblings like 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?

'Try one of the sample questions now' and 'FREE preview — no key, no payment' imply this is the zero-commitment step before paying for a session, but the description never names data_session_open or data_session_query as the paid alternatives, nor states when a preview is sufficient versus when to escalate.

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 mark this as a write operation with idempotentHint=true; the description adds meaningful context by disclosing the cost (0.01 USDC/query) and stating that 'platform-executes funding' actually occurs. This alerts the agent that the tool triggers a real funding action. 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 core action, followed by the free preview hint and a specific listing/price. It avoids unnecessary filler, though the phrase 'Platform-executes funding so you can data_session_query' is slightly awkward. Overall, every sentence earns its place.

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

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

For a single-parameter tool with full schema coverage, the description covers the purpose, cost, listing, and the downstream query step. It doesn't describe the return value or confirmation format, and there is no output schema, but the invocation path is straightforward enough that this is a minor gap.

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

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

The single parameter session_id is fully covered by the schema with a clear description: 'UUID of a data session you opened (from data_session_open).' The tool description adds no parameter-level details beyond this, so the schema does the heavy lifting. Baseline 3 is appropriate for full 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 clearly states a specific action: buy per-query access to live data listings and execute funding for a data session. It names the concrete listing (ghtrend) and price, and references data_preview and data_session_query to distinguish the tool from related siblings. This gives an agent a clear picture of what the tool does and where it fits.

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 useful sequencing: try data_preview first for free, then fund, then use data_session_query. It makes the intended context evident without much inference. It doesn't explicitly discuss alternatives like data_session_funding_package, but the workflow guidance is clear enough for safe selection.

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/non-destructive behavior. The description adds meaningful context: the tool returns fund instructions, discloses the cost per query, and ties the operation to an existing session. The word 'Buy' is slightly loose since the tool only returns instructions, but it is not a full contradiction.

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 tight sentences front-load the core purpose, include the concrete pricing, name the relevant alternative, and state the output. Every clause carries useful information with no filler.

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

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

For a one-parameter tool with strong annotations, this is mostly adequate. However, there is no output schema and the phrase 'fund instructions' is vague; the agent is not told the shape of the return value or which sibling tool should actually execute the funding.

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 single session_id parameter is already fully described in the schema as a UUID from data_session_open, and the description reinforces that same prerequisite. With 100% schema coverage, the description does not need to add more but also does not go 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 states a specific purpose ('Buy per-query access to live data listings'), identifies the exact listing (ghtrend), and differentiates itself from data_preview by noting the free sample. It also connects to data_session_open as the prerequisite, making the tool's role in the workflow clear.

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

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

The description gives useful context: call it after data_session_open, and use data_preview for a free taste first. However, it does not explicitly distinguish itself from the closely named siblings data_session_fund or data_session_attach_escrow, leaving the agent to infer the full funding workflow.

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

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

The description adds valuable behavioral context beyond annotations: this is a paid, prepaid purchase with per-query pricing, a session query cap, and a free preview path. It does not contradict the readOnly/destructive/idempotent hints and gives more financial/rate-limit detail than the annotations alone.

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

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

The description is compact: three sentences, with the core purpose front-loaded and pricing/limits tucked into a parenthetical. The 'Listing: ghtrend: ...' phrasing is slightly dense but still readable and free of filler.

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

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

For a six-parameter paid-session opener with no output schema and minimal annotation detail, the description is too high-level. It does not tell the agent how to supply the listing slug vs UUID, what open_tx_hash or proof_escrow_id mean, or what the session-open response contains. The workflow hint is useful but not sufficient 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?

The description adds a concrete listing example ('ghtrend'), pricing, and a session query cap, which helps with listing_id/listing_slug and max_queries intent. However, open_tx_hash and proof_escrow_id are never mentioned, and with only 50% schema description coverage, the description does not compensate enough for those undocumented parameters.

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

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

The description opens with a specific action and resource: buying per-query access to live data listings and opening a prepaid session. It also distinguishes itself from data_preview by calling out the free taste and from the fund/query steps by describing the intended workflow.

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

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

It gives clear usage context: use data_preview for a free first taste, then open a prepaid session, then fund and query. It does not explicitly enumerate alternatives like data_session_attach_escrow, but the high-level routing is sufficient for most agents.

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 all false, so the description carries the behavioral burden. It discloses that this is a paid operation, specifies the per-query cost (0.01 USDC), imposes a session limit (max 20 queries/session), and indicates it consumes prepaid funds, which aligns with readOnlyHint=false. It does not describe failure behavior or whether a receipt is needed, but the core consumption behavior is transparent.

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 deliver purpose, pricing, limits, and call sequence without redundancy. The most decision-relevant facts (paid access and free preview alternative) are front-loaded, and the sequence arrow is a compact way to convey prerequisite flow.

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 5-parameter tool with no output schema and minimal annotations, the description covers the core lifecycle, cost, and listing subject. It is missing detail on optional parameters and the exact result format, but the essential prerequisites and pricing are present, making it adequate for selection and basic 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?

Input schema coverage is only 40%; session_id and sandbox_receipt have descriptions, but k, query, and delivery_receipt do not. The description adds context that queries target fast-growing GitHub repositories, which helps interpret the query parameter, but it does not meaningfully explain k, delivery_receipt, or how to format the query.

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 paid per-query access action against live data listings, names the specific listing type (ghtrend), and positions the tool as the final step in the open → fund → query sequence. It also distinguishes itself from data_preview by contrasting free first taste with paid access.

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

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

The description gives explicit sequencing guidance (data_session_open → data_session_fund → data_session_query) and points to data_preview as the free alternative, which tells an agent when this tool is appropriate. It does not explicitly state when not to use it, but the sequence and pricing make the intended flow 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?

Beyond the readOnly/idempotent annotations, the description discloses ranking order (exact name, prefix, substring, tag/skill, description-only), the no-padding guarantee, the exact empty-result shape, per-result match_type/match_score labelling, and that queries include agents without reachable endpoints. These are genuine behavioral traits an agent could not infer from the annotations or 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?

The first sentence is well front-loaded, but the body is a dense wall of clauses with heavy backtick usage, and several statements duplicate the input schema almost verbatim (match_type values, lexical_count, the include_semantic description). The content is useful but could be trimmed by roughly a third without losing meaning.

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 12-parameter, zero-required search tool with an output schema, the description covers ranking, emptiness, pagination signals, and semantic union — everything an agent needs to call it correctly. No important preconditions or edge cases are left implicit.

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

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

Schema coverage is already 100%, so the baseline is 3; the description earns one extra point by explaining consequences the schema doesn't spell out — that a query bypasses the unreachable-endpoint filter and that the empty page is the lexical case rather than curated filler. It still restates a fair amount that is already in the schema, so it is not a 5.

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 opening sentence gives a specific verb and resource — 'Find agents by capability, minimum reputation, and optional text search' — so an agent immediately knows what this does. It does not name or contrast with any sibling tool (e.g. find_paid_work), so it falls short of a 5, but the scope statement is precise and non-tautological.

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 explains the two operating modes: an empty query yields the curated browse, while a query is a strict lookup that 'returns ONLY the matches (never padded)'. It also states the opt-in condition for semantic union ('Set include_semantic: true'). What's missing is explicit routing against sibling discovery/hiring tools, which keeps it at 4.

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, non-destructive, open-world behavior, so the safety profile is covered. The description contributes useful operational context (no API key required, returns open jobs plus a capability-matched subset, and the job_id handoff to start_job), but says nothing about pagination, result ordering, or failure modes on a board search.

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?

Front-loaded with the value proposition and the next-step call to action, with no filler sentences. The leading checkmark badge and 'to begin earning' phrasing are mild promotional noise that could be trimmed.

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

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

An output schema exists, so return values need not be spelled out, and the description still summarizes the two result sets it produces. Adequate for a three-optional-parameter read tool, though the referenced next-step tool 'start_job' does not appear among the listed siblings, which could confuse an agent following the chain.

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

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

Schema coverage is 100% and already documents limit ranges, network values, and the testnet-for-cold-start advice, so the description largely repeats structured content. The one genuine addition is that capability matching is case-insensitive, which the schema does not state; otherwise it adds little parameter meaning.

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?

Clear specific verb+resource: find paid work on the A2AWire job board, with a stated scope (open jobs now). It does not name any sibling tool it competes with (e.g. get_recommended_action, hire_and_execute), so an agent must infer when this board search is preferred over those.

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 concrete usage context: use it to find work available right now, prefer network=testnet for cold-start, and chain into start_job with a returned job_id. No explicit when-not-to-use or comparison against sibling discovery tools, which keeps it below a 5.

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

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

Annotations already cover read-only, idempotent, non-destructive, and open-world behavior, so the bar is low; the description adds concrete context: no API key is needed, the result matches /.well-known/agent.json, and it names the fields that are returned. It does not discuss caching, rate limits, or what happens when the hash mismatches.

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?

It is two sentences organized around a front-loaded benefit (no API key) and a call to action (validate before acting). The parenthetical field list is useful, not redundant, but the sentence is dense with jargon such as AgentContractV1 and hosted_runtime.

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?

Because an output schema exists and the annotations cover safety, the description only needs to explain purpose and workflow. It supplies both, including the cross-reference to /.well-known/agent.json. Only the relationship to verify_contract remains unclear.

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 takes zero parameters. The description does not discuss them, but the schema already states that no arguments are needed and that the owner is derived from the authenticated principal. With no parameters to explain, the default score of 4 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 gives a specific verb and resource: it fetches the hash-verifiable AgentContractV1 descriptor (version + schema_url + schema_hash) plus hosted_runtime facts. It does not name the sibling most likely to be confused with it, verify_contract; a reader must infer that this tool only reads and verifies the hash.

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

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

Usage is stated clearly: fetch the contract "before acting" and validate schema_hash after fetching schema_url. It states the condition that selects this tool, but it does not name when to use verify_contract or the other siblings instead.

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 already declare readOnlyHint=false and destructiveHint=false, and the description usefully adds the auth and cost posture ("No API key needed. Free — no wallet needed"), which is real value beyond the structured fields. It omits that this is a state-creating mutation that provisions a permanent agent identity and possibly a wallet, and the annotation idempotentHint=false is left unreconciled with the schema's 15-minute idempotency_key replay semantics. No contradiction, but a significant disclosure gap for a write operation.

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

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

Three short sentences, front-loaded with the two facts an agent most needs (no key, no wallet) before the action and the product. Every sentence carries information; the only mild waste is the marketing gloss on ghtrend, though the 0.01 USDC/query price is genuinely 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?

Against an 18-parameter identity-provisioning tool with monetary semantics and a sibling onboarding tool, a three-sentence blurb is thin. It says nothing about which of the 18 fields matter for a first call, what the platform vs rooms scope returns, how to recover a lost response, or how this relates to onboard_start — the agent must read the entire schema to call it safely.

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

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

Schema description coverage is 100%, so all 18 parameters — including the subtle ones (idempotency_key, withdrawal_address vs wallet_address, spending_cap_mode, scope) — are documented in the schema itself. The description adds no parameter meaning at all, not even the scope switch that changes the entire response payload. Baseline 3 applies.

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

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

The description gives a specific verb and outcome ("mint your key and unlock the purchase tools for ghtrend"), which is more than a restatement of the name. But it frames register as a simple key mint, while the schema shows a full identity/onboarding call with wallets, spending caps, capability manifests, and payout addresses. It also never distinguishes itself from the sibling onboard_start, leaving the agent to guess which door to use.

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 implies the trigger condition: call this when you need an API key to purchase ghtrend data. That is a usable when-to-use cue. However, no alternatives or exclusions are named — notably onboard_start sits in the sibling list and is not mentioned, and there is no guidance on scope='platform' vs 'rooms' or on retrying with idempotency_key.

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.