site

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

With no annotations, the description carries the full burden and does surface a genuinely important behavioral trait: this is a signature, not a transaction, with no fee and no asset movement. That reassures the agent about side effects. It omits other relevant behaviors such as message expiry, single-use semantics, or what the returned message contains.

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

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

Three compact sentences, front-loaded with the action and result, then the safety caveat, then the follow-up call. No filler or repetition.

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, no-annotation, no-output-schema tool, it explains both the input and the general nature of the return value ('the exact message to sign') and the chaining step. Only minor operational details (session lifetime, signed-message contents) are absent.

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 0% and the single parameter has no description, so the description must compensate; it establishes that the input is a Solana address, giving the parameter clear meaning. Length bounds (32-44 chars) are left to the schema, which is acceptable since the semantic role is covered.

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 concrete input-output contract ('Give a Solana address; get the exact message to sign'), which is a specific verb+resource rather than a restatement. It also names the sibling agent_session_verify as the next step, letting an agent distinguish the two endpoints without reading either schema.

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?

Clearly positions this as the first step of the sign-in flow and tells the agent to follow with agent_session_verify using the base64 signature, which is actionable sequencing. It doesn't state any exclusions or when-not-to-use cases, so it stops short of 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?

With no annotations, the description carries the full behavioral burden: it does disclose token lifetime (30 days), revocation ('revocable from the account page'), the base64 Ed25519 signature requirement, and the exactness constraint on the message, which are meaningful traits. It stops short of stating the side effect (creating a session), what happens on signature/address mismatch, or any rate/permission constraints, leaving notable gaps for an auth-mutating tool.

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 compact sentences with the required inputs front-loaded ahead of the return value, and no padding. The opening is a verbless fragment, which slightly reduces readability, but nothing is wasted.

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

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

There is no output schema, so the description correctly describes the return value (a session token to pass as `session`), plus its lifetime and revocability — the essentials for an agent to proceed. It omits failure behavior and the precise meaning of `address`, but for a three-parameter step in a known sequence it is largely sufficient.

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 0%, so the description must compensate, and it does document the meaning of all three parameters: the message provenance ('exact message from agent_session_start') and the signature encoding ('base64 Ed25519'). The 'address' parameter is named but not explained (presumably the wallet address), and no format/length constraints from the schema are echoed, so it stops just short of full 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 title supplies the verb ('Finish the wallet sign-in') and the body confirms the outcome ('Returns a session token'), and it explicitly distinguishes itself from agent_session_start, whose message output it consumes. The body sentence itself is a noun-phrase list of inputs rather than a stated verb+resource, so an agent must lean on the title for the action, but the combined definition is unambiguous.

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

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

It implies the correct sequence by requiring 'the exact message from agent_session_start' and by telling the agent to pass the returned token to 'every later call', which is genuine workflow guidance. However, it never states when this tool should not be used, what to do if the message is missing/expired, or any alternative path, so usage is implied rather than explicit.

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?

No annotations are provided, so the description carries the full behavioral burden. It does disclose one genuinely useful trait — that claimant identity is never returned — plus the fields it does report (proof, timestamp). But it omits that the operation is a read, what happens for unclaimed entries, and anything about permissions or rate limits.

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 tightly written sentence with zero padding, and the most distinguishing clause ('never by whom') is placed at the end as a natural caveat. It is efficient, though brevity here edges toward under-specification rather than economy.

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

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

There is no output schema and no annotations, so the description must do more work. It partially describes the return contents, but leaves both input parameters and the read-only nature unexplained, making it only minimally adequate given the tool's role in a larger claim workflow.

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 0% and the description says nothing about 'scheme' or 'value'. These two required, undocumented parameters are the core of the call, and the agent is left to guess the intended identifier format; the description does not compensate for the coverage gap.

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

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

The description conveys the resource and the shape of the answer (whether a claim exists, by which proof, when, but not by whom), which is more informative than a bare name. However, it is phrased as a question with no verb (lookup/check/report), and it does nothing to distinguish itself from the sibling claim_status, which sounds like the same job. An agent cannot confidently route between the two.

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

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

There is no statement of when to use this tool versus claim_status, claim_verify, or entity_lookup. Only the incidental phrase 'never by whom' hints at a privacy condition, but that is not framed as usage guidance or an exclusion that would steer tool 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?

With no annotations, the description carries the full burden. It does disclose meaningful output behavior (returns the proof domain and a token, plus the three placement methods: TXT record, well-known file, or verified email), but says nothing about auth beyond session, idempotency, rate limits, or what happens on failure.

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 dense sentence with the input and output front-loaded and no filler. Slightly awkward phrasing ('proof domain the register lists') but appropriately sized.

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 no annotations and no output schema, the description is the only source of behavioral info. It covers inputs and outputs well enough, but omits the multi-step claim lifecycle (why a token, how claim_verify follows) an agent needs to use it correctly within the sibling set.

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 33% and only the session parameter is documented in the schema. The description adds partial meaning by explaining that the entry is identified by scheme + value (e.g. 'lei'), but gives no format, constraints, or distinctions for the scheme and value fields themselves.

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 (naming a register entry) and its result (the proof domain and the token to place), which tells an agent this initiates a domain-ownership claim. It is clear enough to identify the resource, but it never explicitly differentiates this from the closely named siblings claim_public, claim_verify, and claim_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?

There is no statement of when to call this versus claim_public or claim_verify, nor any prerequisite (the session token only being referenced via the schema). The description implies a first step in a flow but never says so, leaving the agent to infer the ordering.

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 no annotations, the description carries the full burden, and it does disclose a useful behavioral trait: instructions are returned conditionally, only while a claim is pending. It says nothing about permissions, session requirements, or whether the result is scoped or exhaustive beyond 'this account.'

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 tight sentence with the resource front-loaded and no filler. The parenthetical 'while pending' clause is slightly tangled but earns its place by signaling conditional 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?

No output schema exists, so the description must cover return values, and it does name what comes back (claims, statuses, pending instructions). For a one-parameter read tool this is nearly sufficient, though it omits collection shape and any result limits.

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 is a single parameter and schema description coverage is 100% — the session token is fully documented as coming from agent_session_verify. The description adds no parameter detail, 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 the resource (every claim of this account) and the payload (status and, while pending, instructions), so an agent can tell it retrieves claim state. It does not explicitly distinguish itself from siblings such as claim_start, claim_verify, claim_public, or listing_status, leaving differentiation 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?

There is no when-to-use statement, no prerequisites, and no named alternative. The agent must infer that this is the read-side companion to the claim_* mutation tools; nothing in the text guides that choice.

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?

No annotations are provided, so the description carries the full burden. It does disclose a useful behavioral trait — that verification involves reading DNS, a .well-known file, and a verified email — and that verified claims become badges on the profile, which hints at a lasting side effect. However it omits whether the call is idempotent, what permissions are needed, and what a partial/failed verification returns.

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 a single compact sentence with no filler, but it is not front-loaded around the action and reads as an aside about server internals rather than a task statement. Adequate but not efficiently framed.

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 no annotations, no output schema, and only 50% parameter coverage, the description should explain the verification outcome (does it mutate badge state? what does the caller get back?) and the required session flow. It leaves the most decision-relevant information 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 description coverage is 50%: the session parameter is documented in the schema, but the id parameter (10-60 chars) is not described anywhere, and the description adds no meaning about what the id identifies (claim, profile, or entity). The description does not compensate for the coverage gap.

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

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

The name and title make the action clear (verify a claim's proof), but the description itself only describes the server-side mechanism — reading DNS, a well-known file and email — without stating the verb+resource directly. It also does not distinguish this tool from close siblings such as claim_start or claim_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?

There is no guidance on when to call this versus claim_start, claim_status, or claim_public, and no stated prerequisites such as the session token requirement beyond what the schema already says. The agent must infer the workflow ordering.

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 no annotations, the description carries the behavioral burden and does so reasonably: it enumerates the returned elements and frames the call as a schema-discovery step. It never explicitly declares the operation read-only, but nothing about the described output implies mutation, and there are no parameters to cause side effects.

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, zero filler: the return contents lead and the recommended usage order follows. Every clause earns its place and the actionable instruction 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 zero-parameter introspection tool with no output schema, the description covers both what comes back and when to call it. The only gap is disambiguation from the overlapping row-count/provenance siblings.

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. There is nothing parameter-related for the description to clarify, and the empty schema is fully consistent with the description.

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 resource (the Wen Receipts dataset) and enumerates exactly what it returns: columns, numeric flags, row count, provenance banner. It is clear on its own, though it does not explicitly distinguish itself from siblings like dataset_stats or dataset_provenance that appear to overlap on row count and provenance.

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?

"Call this first to learn the schema" gives explicit ordering guidance for a pipeline of dataset tools. It stops short of naming alternatives or exclusions (e.g., when to prefer dataset_stats or dataset_provenance instead), so it is strong but not fully routing.

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

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

With no annotations, the description carries the full burden, and it does disclose one genuinely useful behavioral trait: results follow the order of the supplied values rather than dataset order. It is silent on what happens if some values match nothing, or on result limits, though the read-only nature of the call keeps the risk modest.

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

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

A single compact sentence with the resource and selection rule front-loaded and no filler. The only cost is the fragmentary phrasing, which makes it slightly less immediately parseable than a full clause.

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 2-parameter read tool with no output schema, an agent still lacks the shape of the returned rows and the behavior when a value is absent. The core selection and ordering semantics are covered, but the definition is only minimally complete for confident 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 coverage is 0%, so the description must compensate, and it does: 'any of the given values' communicates OR-style matching for the values array and 'in the order given' communicates that sequence is preserved. It effectively explains the semantics of both parameters, though it doesn't name them or mention the 2-10 item bound.

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?

Names a specific resource (rows of the Wen Receipts dataset) and a precise selection rule ('whose column is any of the given values'), and the 'X vs Y' framing hints at the comparison use case. It reads as a fragment without an explicit verb like 'Returns', but the operation is unambiguous.

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

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

It gives a trigger scenario ('for X vs Y questions'), which implies when to reach for it over a plain row fetch. However, it never names alternatives such as dataset_search or dataset_row, nor states any when-not conditions, leaving routing largely 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?

No annotations are provided, so the description carries the burden. "Read this" implies a pure read with no side effects, and with zero parameters there is nothing to mutate, so risk is inherently low. However, it does not state whether the data is static, cached, or what the response shape looks like beyond the field list.

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?

One sentence listing the returned fields, followed by one sentence of usage guidance. Front-loaded and every clause earns its place 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?

With no output schema, the description must convey what comes back, and it does so by enumerating source, date, licence and citation. It is complete enough to call the tool; only the exact response structure and citation format are left unspecified.

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

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

The tool takes no parameters at all, so there is no parameter semantics to explain. Per the baseline for zero-param tools, a 4 is appropriate; the description correctly spends its words on returned content instead.

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 the resource (the Wen Receipts dataset) and enumerates exactly what it returns: source, computation date, licence, and citation. That is far more specific than a restatement of the title, and it is easily distinguished from siblings like dataset_columns or dataset_stats. It stops short of naming an explicit verb+resource pair, but the intent is unambiguous.

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

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

"Read this to attribute a figure correctly" gives a clear triggering condition for the tool. There are no exclusions or named alternatives, but for a zero-argument metadata tool the use case is narrow enough that explicit alternatives are unnecessary.

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 no annotations, the description carries the full behavioral burden. It usefully discloses case-insensitive matching semantics, but says nothing about result limits, ordering, behavior when the column name is invalid, or whether the dataset/column must be pre-existing.

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 with the dataset named first and no wasted words. It is a verbless fragment ('The rows of...where...'), which is terse but slightly awkward as a standalone instruction.

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 two-parameter lookup with no annotations, no output schema, and 0% schema coverage, the description is thin — it omits return shape beyond 'rows', ordering, empty-result behavior, and column-name validity, all of which an agent needs to call it correctly.

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

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

Schema description coverage is 0%, so the description must compensate, and it only partly does: 'column equals a value' tells the agent the two required params are a column identifier and a comparison value, but not that 'column' must be an existing Wen Receipts column name nor what happens on mismatch.

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 resource (rows of the Wen Receipts dataset) and the precise retrieval condition (column equals value exactly, case-insensitive). It is clear what the tool returns, though it never names a sibling such as dataset_search to contrast exact-match against fuzzy retrieval.

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

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

Usage is implied: the emphasis on 'exact' and 'case-insensitive' signals this is for lookups when the key value is already known, in contrast to a search-style tool. However, no alternative tool is named and no conditions for when-not-to-use are given.

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?

No annotations exist, so the description carries the full burden; it does disclose useful traits: case-insensitive matching, the 50-row cap, and the target dataset. It omits return format, no-match behavior, pagination, and any permission requirements, so the behavioral picture is only partial.

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 with no filler; the resource scope and matching rule come before the cap. It is efficient, though its extreme terseness is part of why other gaps go unfilled.

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 two-parameter search with no output schema and no annotations, the description covers the essentials of scope and cap but says nothing about result shape, ordering, or behavior on zero matches, leaving the no-annotation burden only partly met.

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 50%: query is documented as 'text to look for in any cell' but limit is bare. The description compensates for limit's ceiling ('up to 50') and reinforces that the query matches cells rather than a field, so it adds some value but leaves the limit's default and floor unaddressed.

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

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

The description states a specific verb+resource: it returns rows of the Wen Receipts dataset matching a query. That is clear and concrete, but it never differentiates itself from the many dataset_* siblings (dataset_row, dataset_top, dataset_stats), so an agent must infer the distinction.

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

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

There is no explicit when-to-use guidance and no named alternative. The agent gets the mechanics of the search but nothing about when this beats dataset_top, dataset_row, or entities_search.

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 no annotations provided, the description carries the full burden, and it does disclose real behavior: grouping commas and currency formatting are handled, and non-numeric rows are excluded and counted. That is meaningful data-cleaning context an agent could not guess. It still omits error behavior for an invalid or non-existent column name.

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

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

A single sentence that front-loads the six statistics before qualifying details in a compact parenthetical. Nothing is wasted, though the parenthetical packs three distinct behaviors into one clause.

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 no output schema, the description usefully enumerates the returned statistics and states the dataset scope, so an agent knows what it gets back. It falls short only on failure modes (bad column name) and on how to discover valid column names.

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 0% for the single 'column' parameter, so the description must compensate. It clarifies that the column must be numeric and belong to the Wen Receipts dataset, which adds genuine meaning, but gives no naming convention, examples, or pointer to dataset_columns for discovering valid values.

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

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

The description names the exact resource (a numeric column of the Wen Receipts dataset) and enumerates the six statistics computed (count, min, max, mean, median, sum), so an agent knows precisely what it returns. It does not explicitly contrast itself with siblings like dataset_top, dataset_row, or dataset_compare, which keeps it from a 5.

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

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

There is no statement of when to use this tool versus alternatives, nor any prerequisites or exclusions. Usage is only inferable from the fact that it operates on a single numeric column; nothing routes the agent between this and sibling dataset_* tools.

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?

No annotations are provided, so the description must carry the behavioral burden. It implies a read-only ranking query by describing returned 'rows', but does not explicitly confirm it is non-mutating, does not mention pagination, ordering ties, or what an empty result means. For a pure read/rank tool the gap is modest but real.

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

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

A single sentence leads with the operation and resource, then adds a clarifying intent phrase. Nothing is wasted and the most important information 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?

With no annotations and no output schema, the description must define behavior on its own. It covers the core operation adequately for a simple tool, but omits default-limit behavior, tie-breaking, and return shape, which an agent would want before invoking.

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

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

Schema coverage is only 33% (only 'ascending' is documented), so the description needs to compensate. It does add meaning for 'column' by specifying the column must be numeric, and 'highest (or lowest)' reinforces the ascending flag's direction. But 'limit' is never mentioned — neither its default nor the max of 50 — leaving a third of the parameters undocumented in both places.

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 operation (returning the highest/lowest rows), the resource (the Wen Receipts dataset), and the mechanism (ranking by a numeric column), plus a plain-language framing of the use case ('which is the most/least X'). This clearly separates it from sibling tools like dataset_stats (aggregation), dataset_search (filtering), and dataset_row (single-row fetch).

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

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

The description implies the use case via 'which is the most/least X', which suggests ranking/top-N retrieval rather than filtering or aggregation. However, it never states when to prefer this over dataset_stats or dataset_search, nor any prerequisites or 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?

With no annotations, the description carries the full burden and does reasonably well: it discloses that nothing is bought, ordered or paid, that it is free, that no quote is guaranteed, and that it returns consent wording and confirmation mechanics. It effectively communicates a no-side-effect, informational read tool, though it never explicitly says it is read-only or lists permissions.

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 'Read first.' then a compact four-clause explanation of what the enquiry means and what is returned. Every sentence carries information, though the phrasing is slightly conversational and could be trimmed. No wasted boilerplate.

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 informational tool with no output schema and no annotations, the description supplies the semantic meaning of the enquiry flow, the consent context, and the absence of cost or guarantee. Given the low complexity, this is close to sufficient; only an explicit statement of its own read-only nature 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 input schema has zero parameters and 100% coverage, so there is nothing for the description to document; the baseline for a no-parameter tool is 4. The description correctly implies no inputs are 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 names a specific function: it explains what submit_enquiry does, stating the enquiry is with human providers who quote directly, and that the tool returns consent wording and confirmation details. The verb 'describe' plus the enquiry subject is clear, and it implicitly distinguishes itself from the sibling submit_enquiry (one explains, one acts). It stops short of a crisp one-line statement of its own purpose, opening instead with a directive.

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?

'Read first' gives a sequencing hint that this should be consulted before acting on an enquiry, which is genuine but thin. No sibling alternative is named (e.g., enquiry_fields or listing_describe), and no explicit when-not condition is given, so the agent must infer the boundary.

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?

No annotations are supplied, so the description carries the full disclosure burden. It does describe the returned content in useful detail, but says nothing about access requirements, whether the enquiry must exist first, or the response wrapper shape. Adequate context, but not full behavioral coverage for an unannotated tool.

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 with zero filler. The content of the response is front-loaded ahead of the routing advice, so the most important information arrives first.

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 no output schema and no annotations, the description sensibly compensates by enumerating the returned field attributes. It omits access/prerequisite details and the exact response structure, but an agent has enough to call it and interpret the result.

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 no parameters, so there is nothing to document and the baseline is high. The mention of keying answers 'by field key' gives useful semantic linkage to the companion tool's input, though it describes submit_enquiry rather than this tool's inputs.

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 exactly what is returned: the key, label, type, required flag, help text and allowed options for every field of the Wen Receipts enquiry. The verb is implicit (a read), but the resource and payload are unambiguous and clearly distinct from the write-oriented submit_enquiry sibling.

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 establishes the workflow: read the field definitions here, then 'pass answers to submit_enquiry keyed by field key.' That names the companion tool and how data flows between them. It stops short of explicit when/when-not conditions, but for a zero-parameter reference tool that is a minor gap.

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 no annotations the description carries the full load and does well: it discloses the auth scheme, that pages are metered per key per day (rate/quota behavior), and that a keyless call returns guidance rather than an error. It does not state whether the export ends at a known page count or whether ordering is stable, which a bulk-dump tool would benefit from.

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, front-loaded with what the tool returns, followed by the access precondition and the keyless fallback. No filler; each clause adds 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 two-parameter, no-output-schema bulk export, the description covers scope, page size, auth, quota, and failure behavior. The main omission is the return shape and whether pagination terminates, which the agent must discover at runtime.

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 0%, so the two parameters carry no documentation. The description compensates partially by stating '200 a page' (pageSize cap/default) but never explains the 'page' parameter's indexing or behavior. This is adequate but leaves real meaning unstated against a low-coverage 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 specific verb (export) and resource (every entity of the Wen Receipts register), plus scope (the whole register, not a query) and pagination granularity. This clearly separates it from query-oriented siblings like entities_search and entity_lookup without needing to name them.

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 explicit preconditions (needs an access key via Authorization: Bearer) and the default page size, which frames when it's usable. It stops short of naming an alternative for filtered lookups (e.g. entities_search), so an agent must infer the when-not from the 'every entity' scope.

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?

No annotations are provided, so the description carries the full burden. It does disclose two real behavioral traits: results are exhaustive for the region and pagination is '50 a page', which pairs with the pageSize maximum of 50. It says nothing about permissions, rate limits, or whether the operation is purely read-only, leaving meaningful gaps for a tool with zero annotation coverage.

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?

One dense sentence with the resource, scope, filter, and page size front-loaded; no filler. The awkward internal phrasing keeps it short of a 5.

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

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

For a 4-parameter tool with 0% schema coverage, no annotations, and no output schema, the description covers region and service but omits the page parameter and any return-shape expectations. It is adequate to attempt a call but leaves the paging mechanics partly unresolved.

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 0%, so the description must compensate. It usefully clarifies that 'region' accepts an id or a name and describes the optional service filter, which the schema cannot convey. It leaves the 'page' parameter entirely undocumented and does not resolve whether 50 is a default page size or a hard cap.

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 conveys that it returns entities from the 'Wen Receipts register' constrained to one region, and the title reinforces 'Every entity in a region, paged'. However, the sentence is grammatically tangled ('register entities in one region') and it never distinguishes itself from close siblings like entities_search, entity_lookup, or entities_export, so an agent must guess which listing tool to pick.

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

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

The only usage signal is 'optionally for one service', which hints at an optional filter. There is no when-to-use statement, no exclusion of alternatives, and no guidance on when to reach for this over entities_search or entity_lookup.

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?

No annotations are supplied, so the description carries the full behavioral burden. It does disclose the returned content (fields, counts, regions, services, identifier schemes, citation), which implies a safe read-only call, but it never states side effects, caching, or response shape explicitly.

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?

One dense sentence plus a two-word directive, which is appropriately sized. However, the imperative 'Call this first' is buried at the end rather than front-loaded, and the repeated 'register register' reduces polish.

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 no output schema and no annotations, the description substitutes by enumerating the payload contents and asserting calling order, which is nearly everything an agent needs for a zero-arg metadata tool. Minor omissions remain around format and whether counts are global or filtered.

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 declares zero parameters at 100% coverage, so the parameter baseline of 4 applies. There is nothing for the description to clarify or compensate for.

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?

Names the specific resource (the Wen Receipts register) and enumerates exactly what the tool surfaces: field list, entity counts, regions, services, identifier schemes, and citation guidance. The only blemish is the duplicated 'register register' typo, and it never explicitly contrasts itself with metadata-ish siblings like dataset_columns or enquiry_fields.

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 closing 'Call this first.' is an explicit, actionable ordering instruction that tells an agent this is the entry-point discovery call. It stops short of naming when NOT to call it or which sibling supersedes it for a narrower question.

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?

No annotations are provided, so the description carries the full burden. It discloses one behavioral trait ('Up to 50 rows') but omits whether the operation is read-only, authentication requirements, pagination behavior, or error handling. This is thin for a search endpoint with zero annotation coverage.

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 well-formed sentence that front-loads the purpose, then lists filters and the row cap. Every clause carries information and there is no redundancy.

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

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

For a search tool with no output schema and four undocumented parameters, the description covers the core input semantics adequately. However, it does not describe the return format, pagination, or the relationship to sibling tools like entities_schema, leaving some gaps an agent may need to resolve elsewhere.

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 0%, so the description must compensate. It does so by explaining that 'q' searches across five entity fields and that 'region' accepts an id or name and 'service' accepts a slug or name—meaningful value-format details absent from the schema. Only the 'limit' parameter is left to be inferred from 'Up to 50 rows'.

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

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

The description states a specific verb ('Search') and resource ('Entities of Wen Receipts register'), and enumerates which fields are matched (name, commercial name, website, address, authority). It is clear what the tool does, but it does not explicitly differentiate itself from sibling tools such as entity_lookup or entities_in.

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 mentions optional region and service filters but gives no explicit guidance on when to use this tool versus alternatives like entity_lookup. There are no when-not conditions or prerequisites, leaving the agent to infer usage.

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 no annotations, the description carries the full behavioral burden and does add useful traits: exact-match semantics and that it returns the whole record plus its page. It omits error/not-found behavior, auth or rate-limit constraints, and the priority when both slug and scheme+value are supplied. Useful but incomplete for a zero-annotation tool.

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-loaded with the resource and identifier mechanics. No filler, though the trailing 'returns the whole record with its page' could be folded more cleanly.

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-param lookup with no annotations and no output schema, the description usefully covers both how to address the entity and what comes back. The remaining gap is the mutual-exclusivity/priority of slug vs scheme+value and not-found behavior, but the core need is met.

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

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

Schema coverage is only 33% (solely 'scheme'), so the description must compensate, and it partially does by explaining that 'scheme + value' form the register identifier and that 'slug' is an alternative route (e.g. 'lei'). It does not clarify that none of the three are schema-required while effectively one mode or the other must be supplied, nor address the length constraints.

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

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

States a specific verb+resource ('register entry for a firm') and clearly scopes it to a single entity, with the 'Exact match' qualifier implicitly separating it from the search-oriented siblings like entities_search. The two accepted access paths (register identifier or page slug) are named. It doesn't explicitly call out the sibling it is not, so it falls just short of a 5.

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

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

'Exact match' hints that this is for when you already hold a precise identifier rather than for discovery, which implies entities_search is the alternative. However, it never states when to use this vs. the sibling search/list tools, nor prerequisites. Usage is implied rather than stated.

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 no annotations, the description carries the full burden and does add real behavioral context: verification happens server-side, a short or wrong-token transfer is reported by name and not credited, and success transitions the listing to review. It still omits failure/error semantics, idempotency, auth requirements, and where the 'reference' originates, leaving meaningful gaps for a state-changing 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?

Two sentences with no filler; the server-side mechanics are front-loaded and the outcome sentence is short. The first sentence is dense with clauses but every clause carries 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 2-parameter state-changing tool with no annotations and no output schema, the description should ideally cover prerequisites and the call outcome/return. It explains the success and short-transfer cases but leaves the caller without guidance on preconditions, error responses, or how to obtain the required reference.

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 50%: session is documented in the schema, while id is undocumented there. The description partially compensates by implying the id is the transfer 'reference' used to locate the payment, but it does not define format or origin of that reference, so the coverage gap is only half closed.

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 activity — the server finding a USDC transfer by reference, reading the treasury balance change, and moving the listing into review — so an agent understands this is the settlement/confirmation step of a USDC payment. It is clear but never names the sibling (e.g. listing_pay_usdc) it follows, so differentiation relies on the reader inferring the payment lifecycle.

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

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

There is no explicit when-to-use guidance, no stated prerequisite (that a USDC payment must first be initiated and a reference obtained), and no alternative named. The agent must infer that this is called after listing_pay_usdc, which is not stated anywhere in the text.

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?

No annotations are provided, so the description carries the full behavioral burden. It discloses the content covered and implies a non-mutating informational role, but it does not explicitly state that it has no side effects or explain the return format.

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 informational scope and followed by a direct usage instruction. Every phrase contributes without redundancy.

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

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

For a zero-parameter explainer with no output schema and no annotations, the description is mostly complete: it tells the agent what topics are covered and to present it to the person first. It could do slightly more to distinguish itself from nearby siblings such as listing_terms.

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 schema coverage is 100%, so there is no parameter documentation burden. The baseline for a no-parameter tool is 4; the description's mention of 'every profile field it takes' refers to listing content, not tool inputs.

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 the informational scope precisely: what a Wen Receipts listing is, its cost, payment, publisher, and profile fields. It is clearly an explainer tool rather than a mutation or lookup tool, though it does not explicitly name a sibling alternative.

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

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

It gives a clear usage instruction: 'Read this to the person first.' This indicates when the agent should invoke it relative to other listing actions. It does not list exclusions or name alternatives, but the context is clear.

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

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

With no annotations, the description carries the full burden and does disclose meaningful behavior: validation refuses scam-shaped or off-list fields by name, and the call returns a listing id plus awaiting_payment status. It omits auth/session requirements, idempotency, and whether a draft can be edited or withdrawn, which keeps it short of a 5.

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 that lead with what the tool does, then the input instruction, then the refusal behavior and return value. No filler, though the deferral to listing_describe is doing work the description arguably should do itself.

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 13-parameter mutation tool with no annotations and no output schema, the description covers purpose, validation behavior, and the returned status, which is solid. It remains incomplete on required-parameter meaning (terms/consent flags, session) and authorization, so an agent still needs listing_describe and the schema to call it correctly.

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

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

Schema description coverage is only 15% across 13 parameters (7 required), so the description must compensate. Instead it delegates wholesale to listing_describe ("lists the fields") and says nothing about the semantics of required fields like termsVersion, termsAccepted, authorised, or session, leaving most parameters unexplained in both places.

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+resource ("Creates a listing draft on Wen Receipts") and signals that this is the pre-payment stage, which separates it from listing_confirm_usdc and the listing_pay_* siblings. It is clear and specific, though the sibling separation is implied (draft vs payment) 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?

It directs the agent to listing_describe for the field list and implies the next step via "status awaiting_payment", but never explicitly states when to call this versus listing_confirm_usdc or the payment tools, nor any prerequisites beyond sending the fullest profile.

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 no annotations, the description carries full behavioral burden. It does disclose the useful trust model — payment is learned from Stripe's verified event, never from the browser — which tells the agent not to treat browser return as confirmation. But it omits URL expiry/reuse, whether the call is idempotent, and what the agent should do next (e.g., poll listing_status).

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 dense sentences with zero filler; the return value is front-loaded and the trust-model caveat follows immediately. Every clause earns its place.

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

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

No output schema or annotations exist, so the description must be self-sufficient. It covers the return shape and confirmation semantics well, but leaves the id parameter and post-payment agent workflow unexplained for a payment-flow tool.

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

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

Schema coverage is only 50%: session is documented as coming from agent_session_verify, but id is a bare string with no description. The description never says what id refers to (presumably a listing identifier) — "at the site's price" only vaguely implies it, so it fails to compensate for the coverage gap.

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

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

Concrete verb and resource: returns a Stripe Checkout URL for a listing payment, and the title disambiguates it as a human-completed hosted checkout. However, it never distinguishes itself from the similarly named sibling listing_pay_stripe, which an agent could easily confuse with this tool.

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?

"A human completes it in a browser" implies the condition under which this tool applies (human-in-the-loop card payment) versus programmatic payment siblings. But no alternative is named and there is no explicit when-not-to-use guidance, so the agent must infer the routing.

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

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

With no annotations, the description carries the full behavioral burden and does well: it discloses that the server determines the amount (never the caller's named amount), charges off-session, and returns either 'succeeded' (listing enters review) or 'requires_action'. It omits auth prerequisites, idempotency, and failure handling, keeping it short of a 5.

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 dense sentence front-loads the action and the charging behavior with no filler. It is slightly crammed with multiple clauses (entitlement, off-session charge, two outcomes, fallback tool), but every clause earns its place.

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

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

For a payment mutation tool with no annotations and no output schema, the description supplies the outcomes an agent needs. The remaining gap is the unexplained 'id' parameter and absent failure/auth behavior, but the core call contract is 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 coverage is only 33%: the 'session' param is documented in the schema, but 'id' and 'paymentMethod' are not. The description compensates for 'paymentMethod' (explaining it is a pm_... id the agent is entitled to use) but leaves 'id' entirely unexplained, so the coverage gap is only partially bridged.

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 action (send a Stripe payment method id) and effect (the server charges the SITE's price off-session), naming the resource unambiguously. It explicitly distinguishes itself from sibling listing_pay_card by routing 'requires_action' outcomes there, so an agent can separate the two without opening either schema.

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 clear context for use (a Stripe payment method the agent is entitled to use) and names listing_pay_card as the fallback when a human is needed. It stops short of contrastive guidance against listing_pay_usdc or listing_confirm_usdc, so the alternative selection is only partially covered.

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 no annotations, the description carries the full burden. It usefully discloses that the response is a transfer request to be signed externally and that a confirmation step follows, but says nothing about request expiry, idempotency, whether the listing is reserved, or what happens if the transfer is not confirmed.

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-loaded with what the call returns and followed by the required next action. No filler, though the parenthetical about the read-only key is dense and could be split for clarity.

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 no output schema, the description compensates well by enumerating the returned fields and the mandatory follow-up call. Still, it omits the meaning of the id parameter and any failure/expiry semantics an agent would want before paying.

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

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

Schema coverage is only 50% and the description adds no meaning for either parameter — neither the id nor the session token is explained in the description (only the schema notes session comes from agent_session_verify). It does explain the returned reference field, but not the inputs.

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?

Specific verb and resource: it 'Returns the Solana Pay transfer request' and enumerates the payload (recipient, amount, USDC mint, unique reference). The USDC/Solana framing plus the named follow-up tool listing_confirm_usdc cleanly separates it from the listing_pay_card and listing_pay_stripe siblings.

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

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

It gives clear procedural context: pay the request from the wallet with the reference as a read-only key, then call listing_confirm_usdc. That tells the agent exactly where this fits in the flow, though it never explicitly contrasts with the card/stripe payment siblings for choosing a rail.

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 no annotations, the description carries the full behavioral burden. It discloses that only published rows are returned and that results can be scoped to one register entry, but it omits whether the operation is read-only, what permissions are needed, pagination behavior, or return shape. This is too thin for a read tool with zero annotation coverage.

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 definition is a single compact sentence with no filler, and the published-rows constraint is placed prominently. It is appropriately sized for a simple lookup tool, though the phrasing is slightly cryptic and could be clearer about the operation.

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

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

For a tool with no annotations, no output schema, and fully undocumented parameters, the description is not complete enough for reliable invocation. It conveys the broad concept but leaves key operational and parameter details to inference. An agent would need external context to call it correctly.

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

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

The schema has two parameters, 'value' and 'scheme', both with 0% description coverage. The description's phrase 'optionally for one register entry' vaguely suggests a filter but does not explain what 'value' or 'scheme' mean or how they combine to identify a register entry. It compensates only minimally for the missing schema documentation.

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 the resource ('firms added on top of the register'), the scope ('published rows only'), and an optional filter ('for one register entry'). However, it never uses a clear operation verb such as list or get, and it does not differentiate itself from sibling listing_* tools. The purpose is inferable but not sharply stated.

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 mentions an optional filter but gives no guidance on when to use this tool versus alternatives like listing_describe or dataset_search. No prerequisites, exclusions, or use contexts are provided. The optional filtering hint is the only usage clue.

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?

No annotations are provided, so the description carries the full burden. It does add real behavioral value by enumerating the possible status values, which the schema does not expose as an enum. However, it says nothing about permissions/auth beyond the session token, ordering, pagination, or whether access is read-only, which an agent would want to know.

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?

One sentence, front-loaded with the scope and immediately followed by the returned status vocabulary. Zero padding and nothing that fails to earn 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?

With no output schema, the description does the work of saying what comes back (all listings plus status) and enumerating the status values, which is the key missing structure. It omits ordering and pagination behavior for what could be a long list of listings, a minor remaining 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?

There is a single 'session' parameter, and schema_description_coverage is 100%, so the schema already explains where the token comes from and its length bounds. The description adds no parameter-level detail, which matches the baseline 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?

States a clear resource and scope: 'Every listing of this account' plus the status field it returns. The verb is implicit ('list'), but the intent is unambiguous. It doesn't explicitly name the sibling it differs from (e.g. listings_published, which returns only a subset), so it stops short of full sibling differentiation.

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

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

Usage is implied by the word 'Every' – a broad personal-listing view – which naturally contrasts with listings_published, but that contrast is left for the agent to infer. There is no explicit when-to-use, when-not-to-use, or named alternative.

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?

No annotations are provided, so the description carries the full burden. It does disclose one useful contract detail (the returned version must be echoed back as termsVersion), but says nothing about whether this is a read-only call, what the return shape or size is, or any auth/rate constraints.

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 tight sentence with no filler, and the round-trip hint is embedded rather than buried. It is slightly cryptic as an unverbed fragment, which keeps it out of the top band.

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 no output schema and no annotations, the description should explain what actually comes back (clause list, version identifier, profile field inventory) and how to use it. Instead it gestures at the contents in one ambiguous clause, leaving the agent to guess at the return structure and the intended call sequence.

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 and the schema is empty, so there is nothing for the description to clarify. Baseline for a no-argument tool.

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 the resource (listing terms/clauses plus profile fields) but is a noun phrase with no verb, so the agent must infer it is a retrieval tool. It is roughly distinguishable from siblings like listing_describe or listing_draft, but the phrasing 'the clauses a listing is judged by' is indirect enough that an agent could confuse it with a schema/validation endpoint.

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 parenthetical 'send it back as termsVersion' hints at a workflow, but there is no explicit when-to-use statement, no prerequisites, and no named alternative among the many sibling tools. The agent has to reconstruct the calling context 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?

With no annotations, the description carries the full behavioral burden, yet it only says the listing is "taken down." It doesn't disclose whether the action is reversible, what happens to the listing's data or state afterward, whether confirmation or specific permissions are required, or what the response contains — all material for a destructive mutation.

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 short, front-loaded sentence with no filler or repetition. It is efficient, though its brevity edges toward under-specification rather than true conciseness.

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 destructive mutation with zero annotations, no output schema, and an undocumented required parameter, the description is far too thin. An agent cannot determine side effects, recoverability, or success/failure signalling from what is provided.

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 50%: the session token is documented in the schema, but the required `id` parameter (length 10-60) has no description anywhere, and the description adds no clarification such as whose listing id is expected. With no enum or format hints, the agent gets no help identifying the id's origin or constraints.

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

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

States a specific action ("takes down") on a specific resource ("listing of this account"), which clearly separates it from read/creation siblings like listing_draft, listing_status, and listings_published. It stops short of naming what makes withdrawal distinct (e.g., irreversible removal vs. unpublishing), so it lacks explicit sibling differentiation.

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

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

There is no when-to-use guidance, no prerequisites, and no mention of the related tools (listing_confirm_usdc, listing_status, listings_published) an agent might weigh instead. The agent must infer that withdrawal is the terminal step in the listing lifecycle.

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?

No annotations are provided, so the description carries the full behavioral burden, and it discloses very little. "Labelled as sponsored in the answer" is a useful output-transparency cue (the response flags sponsored content), but nothing is said about read-only vs mutating nature, permissions, caching/freshness, or what 'active' means.

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 with no padding. The parenthetical enum inline is compact, though the phrasing ("The Sponsored slot's contents") is slightly oblique as an opener.

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

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

With no annotations, no output schema, and three parameters at 0% schema coverage, the description should explain return shape, what makes a placement 'active', and how region/leaf interact with page. None of that is present, so an agent cannot call it confidently beyond the simplest home case.

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 0%, so the description must compensate. It restates the `page` enum values (already in the schema) and implies region/leaf are used with those page types, but never explains what `region` or `leaf` should contain or their length limits, leaving the remaining parameters undocumented in both places.

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?

Names the resource (the Sponsored slot's contents for a page) and its scope (home | region | leaf), so an agent knows it fetches sponsored placements rather than doing anything else. The verb is only implied ("contents"), but the resource and scope are specific enough to distinguish it from any sibling.

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

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

There is no statement of when to reach for this tool versus alternatives, nor any prerequisite (auth, sponsor-account requirement, freshness). The parenthetical enum hints at input shape but not at invocation context.

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 no annotations, the description carries the full burden and does so well: it discloses the two-phase write, that step 1 validates and returns a summary/consent line/token, that the enquiry is only submitted at step 2, and that the person must click an email link before any provider sees it. It omits error/idempotency behavior and any permission or rate-limit constraints, which keeps it from a 5.

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?

Relatively long, but front-loaded with the critical 'NOT a purchase' framing and organized strictly by step, so no sentence is filler. The embedded consent sentence is verbatim text that must be reproduced, which justifies its length.

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

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

No output schema exists, so the description must describe returns, and it does: step 1 returns a summary, the consent line and a confirmation token. Combined with the gated email-verification flow, an agent has everything needed to drive both calls correctly.

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

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

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning beyond the schema: it ties 'answers' to field keys from enquiry_fields and explains that 'confirmation' is the token produced by step 1 rather than an arbitrary string. The consent=true spelling of the boolean is also made operational.

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 ('Submits an enquiry to Wen Receipts') and immediately scopes it against the obvious misreadings ('NOT a purchase, NOT a guaranteed quote'). This distinguishes it from the listing_pay_* and claim_* siblings without needing to open their schemas.

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

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

Gives explicit step-by-step when-to-use: step 1 with answers + consent, then step 2 only 'if the person agrees' with the token. It names the exact conditions that gate each call and what must be shown to the person in between, which is more than most definitions provide.

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