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?

No annotations are provided, so the description carries the full burden. It discloses the return contents (columns, numeric status, row count, provenance banner), which is useful, but does not state that the operation is read-only, side-effect-free, or otherwise describe its safety or permission profile. For a simple introspection tool, the output disclosure is helpful but leaves behavioral assurances implicit.

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 efficient sentences: the first enumerates the return payload, the second gives the primary usage instruction. It is front-loaded with what the agent receives and wastes no words.

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 must carry the return-value burden, and it lists the major outputs. It stops short of describing the exact shape or format (e.g., how numeric columns are flagged), so a small gap remains, but it is sufficient for an agent to call and understand the 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?

The tool takes zero parameters, so the baseline is 4. There is no parameter semantics for the description to clarify, and the empty schema requires no additional explanation.

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

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

The description clearly states the resource (Bags That Pay dataset columns and shape) and enumerates the returned items: columns, numeric flags, row count, and provenance banner. It does not explicitly differentiate itself from the many sibling dataset_* tools, but the specific content and 'Call this first to learn the schema' scoping make its purpose 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 an explicit first-use instruction: 'Call this first to learn the schema.' This tells an agent when to invoke it relative to other dataset operations. However, it does not name alternative tools or state when not to use it, so it falls short of full when/when-not guidance.

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

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

No annotations are provided, so the description carries the full behavioral burden. It discloses one useful trait—output order follows the given values—but omits read-only nature, error behavior for unmatched values, pagination, and any permission or rate-limit context.

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

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

The single sentence is front-loaded with the resource and scope, and the em-dash use-case is compact. It is slightly awkward as a verbless fragment, but it wastes no words.

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 filter tool with no output schema, the description covers the basic retrieval operation. It omits column format, output shape, read-only assurance, and value-count limits, leaving some gaps an agent would need filled.

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. It partially does by explaining that values are matched against a column and that result order follows the values, but it leaves column format (name vs. ID), matching semantics (case sensitivity, exactness), and the max-10-values constraint 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 names the resource (rows of the Bags That Pay dataset) and the filter condition (column matches any of the given values) plus output ordering. It is clear but does not explicitly distinguish this tool from siblings like dataset_search or dataset_row, so it falls 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?

It gives an implied use case with 'for "X vs Y" questions' but never states when to use this over dataset_search or dataset_row, nor any exclusions. The guidance is minimal and inferred 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 supplied, so the description carries the disclosure burden. It implies a read-only lookup and enumerates the returned fields, but never states read-only status, permission requirements, or whether the provenance is static or can change over time. For a zero-argument metadata tool the risk is low, so a minimal-but-adequate 3 is appropriate.

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 return contents before the usage hint. Efficient, though the second sentence slightly restates the first's implication that this is read for attribution purposes.

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 usefully enumerates the returned fields (source, date computed, licence, citation), which is the main completeness gap it must fill. Small details such as licence format or citation style remain unspecified but are not essential to calling the tool correctly.

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

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

The tool takes no parameters and the schema is an empty object, so there is nothing for the description to clarify or compensate for. Baseline 4 applies.

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

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

The description names a specific resource (the Bags That Pay dataset) and enumerates what it returns: source, computation date, licence and citation. It is clearly distinguishable in spirit from data-reading siblings such as dataset_columns or dataset_stats, though it never names an alternative to sharpen the boundary.

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 concrete trigger condition for when to reach for this tool rather than a data-access sibling. It stops short of stating exclusions or explicitly naming the alternative tools for non-attribution needs.

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 one real behavioral trait — matching is case-insensitive — but says nothing about whether this is a read-only lookup, how many rows can be returned, pagination, or what happens if the column name is invalid.

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 selection semantics front-loaded. It is efficient, though the phrasing is slightly roundabout ('The rows of the ... dataset where ...') rather than leading with the action.

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

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

For a two-parameter lookup with no annotations and no output schema, the description covers the matching rule but leaves the return shape, row limits, and error cases unaddressed. Adequate for a simple lookup, but with clear gaps an agent would hit in practice.

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. It conveys that 'column' is a column name and 'value' is compared with exact, case-insensitive equality, which gives the two parameters real meaning, but it does not state constraints such as valid column names or that value is a string.

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 Bags That Pay dataset) and the exact selection semantics (column equals value, case-insensitive). It clearly distinguishes itself from a fuzzy search sibling like dataset_search through the word 'exactly', though it never names that sibling outright.

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 mention of alternatives. The only implied routing signal is 'exactly', which suggests dataset_search for non-exact matching, but the agent must infer this 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 provided, the description carries the full burden, and it does disclose two real behaviors: matching is case-insensitive and results are capped at 50 rows. It omits other traits an agent would want, such as result ordering, pagination beyond the cap, and error behavior on no matches.

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 that front-loads the resource ('Rows of the Bags That Pay dataset') and folds in the match semantics and result cap with zero filler.

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

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

For a tool with no annotations, no output schema, and only 50% parameter coverage, the description covers the essentials (what matches, how many rows) but says nothing about what a returned row looks like or how the 50-row truncation should be interpreted. Adequate but with clear gaps.

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, limit is not). The description adds meaning for both: it clarifies query matches against 'cells' case-insensitively and confirms the 50-row cap that limit's maximum already encodes, but adds no syntax or format detail beyond that.

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

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

The description gives a specific verb+resource: fetching rows of the 'Bags That Pay' dataset that match a query, with an explicit cap of 50. An agent can tell it apart from dataset_top or dataset_row by the text-matching semantics, though no sibling is named explicitly to contrast against entities_search or dataset_compare.

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 and no mention of alternatives such as entities_search or dataset_top. The usage context (a text query against cells) is only implied by the wording, leaving the agent to infer when this tool is the right 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?

With no annotations, the description carries the full burden. It does disclose useful behavior: commas and currency groupings are handled and non-numeric rows are excluded and counted, which materially affects results. However, it says nothing about permissions, empty/all-non-numeric edge cases, or result shape.

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 that front-loads the returned statistics before the caveats. Nearly every clause earns its place, though the parenthetical could be slightly cleaner.

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 the description does list the returned statistics, which partially covers the return contract. But for a stats tool with no annotations it omits error behavior, empty-data handling, and when to prefer this over sibling tools.

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% (only a bare string with minLength 1), so the description must compensate. It adds the crucial semantic that the column must be numeric, which the schema does not convey, but offers no naming examples or case/format expectations for the column value.

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

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

The description names a specific operation (compute count, min, max, mean, median, sum) on a specific resource (a numeric column of the Bags That Pay dataset). An agent can tell it apart from dataset_row or dataset_top by the enumerated statistics, but no sibling is named explicitly, so differentiation is inferential.

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 the many dataset siblings (dataset_compare, dataset_top, dataset_columns). Usage is only implied by the tool's nature, and no prerequisites or exclusions 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 are provided, so the description carries the full behavioral burden, and it delivers little beyond the ranking idea. It does not disclose the default number of rows returned (limit has no schema default), tie-breaking, pagination, or what the returned rows look like.

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 core operation front-loaded, plus a short example phrase that earns its place. No redundancy or filler.

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

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

For a tool with no annotations, no output schema, and only 33% parameter coverage, the description is too thin. An agent still cannot tell how many rows come back by default, how ties or nulls are handled, or how the output is shaped.

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%, so the description must compensate. It usefully implies 'numeric column' (a constraint not stated in the schema, which allows any string) and clarifies the high/low meaning that maps to 'ascending'. The 'limit' parameter is left undocumented in both the schema and 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 operation (return highest/lowest rows ranked by a numeric column) on a named resource (Bags That Pay dataset). An agent can infer the core behavior, but the description never distinguishes itself from nearby siblings like dataset_row, dataset_stats, or dataset_compare, so the boundary is ambiguous.

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 quoted framing 'which is the most/least X' implies the question shape this answers, which is useful implied guidance. However, there is no explicit statement of when to use this versus dataset_stats or dataset_search, and no prerequisites 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?

With no annotations, the description carries the full burden and does well: it states nothing is bought, ordered or paid, no quote is guaranteed, and it is free. It also discloses what is returned (who receives details, consent wording, confirmation method), though it does not enumerate auth or rate-limit behavior.

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

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

The description is front-loaded with 'Read first', then efficiently covers purpose, side effects, and return contents in five short sentences. Every sentence adds relevant information with no repetition or 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?

Given the tool has zero parameters, no output schema, and no annotations, the description is largely complete: it explains the tool's purpose, its non-transactional nature, and the kind of information it returns. A minor gap is the absence of an explicit statement that it is read-only and idempotent, though this is strongly implied.

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 there are no parameter semantics to describe beyond the schema's empty object. Baseline for zero parameters is 4.

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 ('States plainly') and resource ('what submit_enquiry does on Bags That Pay'), and distinguishes this read-only informational tool from the action tool submit_enquiry. It also explicitly rules out purchase, order, payment and guaranteed quote, so an agent can tell it apart from transactional 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?

'Read first' gives a clear usage context, positioning this tool before engaging with submit_enquiry. It references the related action tool but does not explicitly name when not to use it or list alternative tools for different enquiry-related tasks.

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 the exact return payload fields, which compensates for the absent output schema, but it says nothing about whether this is a public/unauthenticated read, caching, or any rate/side-effect characteristics.

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-shape enumeration comes first and the downstream usage note is front-loaded into the second sentence.

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 describing the return object, and it links the result to the consuming tool. It is nearly complete; only the read/authorization context and the distinction from enquiry_describe are missing.

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

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

The tool takes zero parameters, which sets the baseline at 4. The description adds useful cross-tool semantics by explaining that returned field keys are the keys to use when answering submit_enquiry, which is information the empty schema cannot convey.

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 concrete resource — every field of the Bags That Pay enquiry — and enumerates what each field carries (key, label, type, required, help text, options), so an agent knows exactly what it gets back. It does not differentiate itself from the sibling enquiry_describe, which is the main gap.

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?

"Pass answers to submit_enquiry keyed by field key" implies the intended workflow (call this before submit_enquiry to learn the schema), which is genuinely useful routing. However, no explicit when-to-use versus enquiry_describe is given, and no preconditions or exclusions are 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 load and does well: it discloses the auth requirement (Authorization: Bearer), the per-key-per-day metering (rate limit), and the unauthenticated behavior (returns how to get a key). It omits what 'provenance' concretely includes and how pagination terminates, but the auth/rate-limit disclosure is genuinely useful.

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 the resource and scope, then auth/metering details. No filler, though the final sentence about the no-key response is a slight tangent.

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 and no annotations, so the description must supply context, and it covers purpose, auth, rate limits, pagination, and error behavior. It stops short of explaining the 'provenance' payload or how a caller knows it has reached the last page, leaving a small gap for a bulk-export 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 0% for the two params, so the description must compensate. '200 a page' conveys the default/max page size corresponding to pageSize, and 'in pages' hints at the page param, but neither parameter's semantics (defaults, starting page, ceiling behavior) is explained beyond that implication.

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 (every entity of the Bags That Pay register) and a clear scope that distinguishes a full bulk export from the search/lookup siblings (entities_search, entity_lookup). It does not name a sibling explicitly, so differentiation is inferred rather than 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?

Usage is implied by 'Every entity ... in pages,' suggesting a full-register dump rather than a filtered query, but there is no explicit when-to-use, when-not-to-use, or named alternative. The agent must infer that search/lookup siblings exist for targeted retrieval.

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 real behavioral trait — results are paged at 50 per page — but says nothing about ordering, permissions, rate limits, or what fields an entity contains. Read-only is only implied by 'entities in a region'.

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 with no padding, and the key constraint (region) is front-loaded. The phrasing 'The Bags That Pay register entities in one region' is slightly awkward and could be misread on first pass.

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 no annotations and no output schema, the description covers the primary parameter's semantics and the pagination default but leaves paging navigation and return shape unexplained. It is minimally adequate rather than complete.

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

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

Schema description coverage is 0%, so the description has to compensate and only partly does. It clarifies that 'region' accepts a state or jurisdiction by id OR name and that 'service' is optional, but the 'page' and exact 'pageSize' parameters are left to the schema.

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

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

The description states a clear resource and scope: entities within a single region, optionally narrowed to one service. The title reinforces this ('Every entity in a region, paged'). It stops short of distinguishing itself from near-miss siblings such as entities_search, entities_export, or entity_lookup.

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, even though entities_search and entity_lookup overlap heavily in intent. 'Optionally for one service' hints at a narrowing use case but doesn't help an agent choose between this tool and its siblings.

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 the returned content categories (fields, counts, regions, services, identifier schemes, citation), which is useful for a tool with no output schema, but it says nothing about read-only nature, permissions, or freshness/caching of the register.

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 short directive, with no filler. The only defect is the redundant 'register register' phrasing, which slightly muddies the opening.

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 0-param tool with no annotations and no output schema, the description adequately previews what comes back, but it is thin on the actual shape of the response (format of field lists, how counts are scoped) and gives no hint about provenance details despite the title advertising 'provenance'.

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 for the description to disambiguate beyond what the (empty) schema already conveys. Baseline 4 applies.

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

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

The description enumerates the concrete content the tool surfaces: available fields, entity counts, regions and services, identifier schemes, and citation guidance. It is clearly distinct from the entities_search/entities_export/entity_lookup siblings, though it is phrased as a noun list rather than a verb+resource statement and carries a 'register register' duplication.

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' is an explicit sequencing instruction that tells an agent this is the discovery/entry point before the other entities_* tools. It does not name alternatives or state when not to call it, but for a 0-parameter introspection tool the ordering guidance is the guidance that matters.

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 a result cap ('Up to 50 rows'), which is useful, but says nothing about matching semantics (exact/prefix/fuzzy, case sensitivity), ranking, pagination, or auth requirements.

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 covering the query target and optional filters, with the row cap appended. No filler, though the run-on structure slightly reduces scannability.

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-param search tool with no annotations and no output schema, the description covers parameter formats and the result cap but omits matching behavior, default limit, and pagination guidance.

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

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

With 0% schema coverage, the description compensates well by explaining that region accepts an id or name and service accepts a slug or name, and that q matches five named fields. Only limit lacks explicit semantics beyond the implicit 50-row 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?

States a specific verb (search) and resource (entities of the 'Bags That Pay' register) and enumerates which fields the query matches. It is clearly distinct from siblings like entities_export or entity_lookup, though it does not name them explicitly.

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

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

No explicit when-to-use or when-not-to-use guidance and no alternatives referenced. The optional region/service scoping hints at a filtering use case, but the agent must infer which sibling (entity_lookup, entities_in, entities_export) to pick instead.

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

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

No annotations are provided, so the description carries the full burden. It usefully discloses exact-match semantics and that the whole record plus its page is returned, but it says nothing about not-found behavior, precedence when both lookup modes are supplied, or whether an empty argument set errors out.

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 that front-loads the resource and then the two input modes. Nothing is wasted, though the nested parenthetical makes it slightly harder to parse at a glance.

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 does cover both input routes and roughly what is returned, but omits not-found handling, mutual exclusivity of the two modes, and the fact that at least one route must be supplied despite zero required parameters.

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

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

Schema coverage is only 33%, but the description compensates by explaining the two lookup modes and the important relational semantics: scheme + value together form the register identifier, while slug is an alternative page-based lookup. This is meaning the bare schema does not convey.

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: fetching the register entry for a firm by register identifier or page slug. It is clear and unambiguous, though it does not name or contrast itself with the sibling it is most likely confused with, entities_search.

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

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

The phrase 'Exact match' implies this is for exact lookups rather than the query-style retrieval that entities_search presumably offers, so usage is implied but never stated directly. There is no explicit 'use X instead when Y' guidance or mention of prerequisites.

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?

With no annotations, the description must carry the behavioral burden. It discloses the full informational scope and implies a passive, read-aloud operation with no side effects. It does not state permissions or rate limits, but for a zero-parameter describe tool it is sufficiently transparent.

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

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

Two sentences, front-loaded with the content scope and ending with the usage instruction. Every phrase earns its place and there is no redundant filler.

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

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

For a zero-parameter informational tool with no output schema and no annotations, the description is nearly complete. It covers what the tool provides and when to use it, though it could clarify that it does not create or modify a listing.

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, so there are no parameter semantics to document. The description mentions returning 'every profile field it takes,' which adds useful context about the output content even though no input schema exists.

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

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

The description clearly states the resource and content: what a listing on Bags That Pay is, its cost, payment methods, publisher, and profile fields. It does not explicitly distinguish itself from sibling tools such as listing_terms or listing_pay_usdc, but the informational scope 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 clear instruction: 'Read this to the person first,' establishing both ordering and audience. It does not name alternatives or when not to use it, but the primary usage context is 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?

With no annotations, the description carries the full burden and does add real behavioral detail: inputs are validated against terms, off-list or scam-shaped fields are rejected by name, and the call returns an id with status awaiting_payment. It omits auth/consent requirements implied by the session, termsAccepted and authorised parameters, so it is not fully transparent.

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

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

Three tight sentences, front-loaded with the action and outcome, and the parenthetical pointing to listing_describe earns its place. Minor jargon ("scam-shaped") adds slight ambiguity 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, and the description does cover the return shape (listing id + awaiting_payment) as well as the validation behavior, which is the most important part. For a 13-parameter, 7-required mutation with nested objects and no annotations, it still leaves the auth/session expectations and the post-draft payment path unexplained.

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, so the description must compensate and largely does not — no meaning is given for name, about, profile, register, services, languages, enquiryEmail or the terms/authorised flags. Pointing at listing_describe is a useful workaround for discovery, but it is a delegation rather than added parameter semantics.

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

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

States a specific verb and resource ("Creates a listing draft") plus the outcome state ("awaiting_payment"), which cleanly separates it from the payment siblings (listing_pay_*, listing_confirm_usdc) and from listings_published. It is clear about what the tool does, though it never explicitly names those payment siblings as the next step.

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 one concrete directive — call listing_describe to learn the fields and send the fullest profile — which is genuine usage guidance. However it never states when to choose this over the alternatives or what the intended follow-on flow is (confirm/pay/withdraw), so the workflow context is only implied.

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 richly: it discloses the non-purchase/non-quote nature, the validation-then-confirm sequence, what step 1 returns (summary, consent line, token), that the person must click an email link before any provider sees the enquiry, and the exact consent wording.

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?

Dense but front-loaded, opening with the critical 'NOT a purchase' framing before the procedural steps. It is long and repeats the consent sentence already present in the schema, which is mild redundancy rather than waste.

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-phase mutation with no output schema and no annotations, the description covers everything needed: both call shapes, the returned token, the consent requirement, and the downstream email-confirmation gate. Nothing an agent needs to invoke it correctly is missing.

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

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

Schema coverage is 100%, so the baseline is 3. The description goes beyond the schema by explaining that answers are keyed by field key from enquiry_fields and that confirmation is only supplied on the second call after approval — usage context the schema cannot express.

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 (submits) and resource (an enquiry to Bags That Pay), and immediately negates the common confusions — NOT a purchase, NOT a guaranteed quote. It also names a sibling concept (enquiry_fields) as the source of field keys, so an agent can route correctly.

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

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

Explicitly prescribes the two-step flow: step 1 with answers + consent=true to validate, step 2 only after the person agrees, adding the confirmation token from step 1. It states the exact preconditions for each call and what must be shown to the person between them.

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