nsgoods-workbench-mcp

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

With no annotations provided, the description carries the full behavioral burden. The phrase 'as of the latest full scan' is a genuine disclosure — the data is a snapshot and may be stale relative to real-time operations. However, it does not state whether the tool triggers a new scan, any latency/cost expectations, or confirm it is strictly read-only.

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 core purpose ('Size and health of the x402 catalogue'), followed by a compact enumeration of the four metric groups. No filler; the trailing 'per network' adds useful grouping context.

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 stats tool with no annotations and no output schema, the description names the content areas (resources, hosts, verdicts, payable endpoints per network) and adds the staleness caveat. The exact return shape is not specified, but an agent has enough to invoke it and interpret the result at a glance.

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 is nothing for the description to clarify beyond what the schema shows. The baseline of 4 applies since no parameter ambiguity 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 what the tool reports — size and health of the x402 catalogue — and enumerates the covered data: resources, hosts, verdict counts, and payable endpoints per network. This is specific enough to distinguish it from per-host (host_summary), per-endpoint (payability_verdict), and status (drift_status, x401_status) siblings, though it never names a sibling 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 guidance on when to choose this tool over the seven siblings. An agent must infer that catalogue_stats is the aggregate overview while host_summary and payability_verdict go deeper, and nothing warns against using it when a specific verdict or drift check is needed.

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 discloses one behavioral trait—the result shape changes based on whether a host is supplied—and 'watch' weakly implies a read-only status operation. It does not clarify error behavior, what the summary contains, or whether any side effects occur.

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 two-sentence description is tight and front-loads the host-scoping behavior without fluff. The phrasing is a bit fragmented ('drift watch' is not a full verb phrase), but every clause contributes.

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-optional-parameter tool, the host-versus-summary rule is the central call-time knowledge and it is present. But the description does not define 'declared-model drift', the returned summary, or the overall response shape, and with no output schema those details 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?

The schema only lists an optional string 'host' with an empty default, so the description's 'With a host, that host's tracked resources; otherwise a summary' adds the key semantic. It explains both modes of the parameter, though it does not specify the expected host format or possible values.

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

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

The description identifies a specific resource ('declared-model drift') and hints at host-scoped versus summary output, but it is written as a noun phrase rather than an explicit actionable statement. 'Tracked resources' and 'summary' are left unexplained, and the tool is not differentiated from siblings such as x401_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?

It provides a clear conditional rule: pass a host for that host's tracked resources, or omit it for a summary. However, it gives no guidance on when to prefer this tool over similar siblings like host_summary or x401_status, and no exclusions or prerequisites 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?

Since no annotations are provided, the description carries the full burden of behavioral transparency. It discloses that the tool returns matching endpoints with latest verdicts and a count, which is useful. However, it does not mention behavior under no matches, pagination, performance implications, or the meaning of the sort and limit parameters. It gives a basic but not comprehensive behavioral picture.

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

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

The description is compact, front-loading the core action and then providing key details in a single sentence. It avoids extraneous information and is easy to parse. The usage hint is appended efficiently without bloat.

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's moderate complexity (search functionality, multiple outputs, parameters), the description covers the essential purpose and one behavioral outcome (returns up to limit endpoints). However, it lacks details on sort functionality, error behavior, and result structure, which might be important for an agent to use it correctly. It is adequate for basic calls but leaves gaps for sophisticated usage.

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 description coverage is 0%, so the description must compensate for parameter meaning. The description mentions 'limit' and 'query' in context (returns up to limit endpoints, search by host or URL substring), which adds some meaning. However, it does not explain the 'sort' parameter (values, format). It partially compensates but not fully for three parameters.

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

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

Description clearly states the tool's function: searching the catalogue via host or URL substring and returning matching endpoints. It indicates key outputs (latest verdict, total match count) and provides a hint about its intended use case. However, it doesn't explicitly mention that search is by string matching, which is implied but could be clearer. It is distinct from siblings as it focuses on endpoints rather than statuses or reports.

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

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

Provides a clear usage suggestion: 'Use this first when you do not know the exact resource URL.' This gives the agent a strategy for tool selection. It doesn't explicitly mention when not to use it or name alternatives, but the guidance implies that if you know the exact URL, other tools may be more direct. This is adequate but not exhaustive.

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 behavioral disclosure burden. It clearly lists the output fields, including the conditional 'gone_since if absent from the latest full scan', giving a solid model of what the tool does. It does not address errors, permissions, or data freshness, but for a read-style summary the disclosed behavior is reasonably complete.

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 one compact sentence with the core purpose front-loaded and the content fields enumerated efficiently. Every clause adds useful information without redundancy.

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

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

For a low-complexity, single-parameter tool, the description provides a strong list of return contents and a conditional field. The main omissions are the host parameter format and exact response shape, but the description is largely sufficient for basic invocation.

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

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

The schema has a single 'host' string with 0% description coverage. The description only repeats that this is for a host and does not clarify the expected format (hostname, IP, ID) or provide examples, so it fails to compensate for the schema 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 clearly identifies the tool as a host-level summary and enumerates the contents returned. The parenthetical 'no time series' helps distinguish it from time-series or trend tools, though it lacks an explicit verb like 'get' or 'retrieve' and does not name sibling alternatives.

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 'no time series' implies this is for a current-state snapshot rather than historical analysis, giving some context. However, there is no explicit guidance on when to use this tool versus siblings like reports or x401_status, and no exclusion criteria 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 burden. It conveys that this is an observational read ('observation', 'seen') and describes the response content, but it does not disclose failure behavior, freshness limits, or whether any external network call is made.

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

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

The description is a single dense sentence with no filler. It front-loads the core purpose and then lists the response components, though it could be slightly clearer with an explicit leading verb like 'Returns'.

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

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

For a simple one-parameter lookup with no output schema, the description covers purpose, parameter semantics, and return content. It lacks edge-case behavior (e.g., missing observations, exact URL normalization) but is otherwise minimally 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 coverage is 0%, so the description must compensate. It adds meaningful semantics to the url parameter by specifying 'exact resource URL (path and query included)', which is valuable beyond the schema's bare string type.

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 specific resource ('payability observation'), the scope ('one exact resource URL'), and the return contents (verdict meaning, remediation, per-network options). This distinguishes it from siblings like catalogue_stats or x401_status, which cover different concerns.

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 context is clear: use this when you need the latest payability observation for a specific exact URL. It does not explicitly name alternatives or give when-not-to-use guidance, but the exact-URL scope implies the applicable situation.

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, and the description does not disclose any behavioral traits such as side effects, permissions, or return behavior. It is a bare statement with no additional context beyond the name, so the agent has no idea what calling this tool will do.

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 extremely short and to the point, but it sacrifices substance for brevity. It lacks structured details about the tool's operation. While it is not verbose, it is under-specified rather than efficiently concise.

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 parameters, no output schema, and no annotations, the description is the sole source of context, and it is inadequate. It does not explain what the tool returns, how to interpret results, or any operational details, leaving an agent unable to use it reliably.

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 the input schema is trivially complete. The description does not need to explain parameters, and the baseline for no parameters is 4. No additional semantic value is required.

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 'Published weekly payability reports' but the verb is ambiguous—does it mean the tool retrieves, lists, or creates these reports? The phrase 'from the signed manifest' adds context but does not clarify the action. It does not distinguish it from sibling tools like 'payability_verdict' or 'verify_signature', which likely relate to payability.

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

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

No guidance is provided on when to use this tool versus alternatives. The description gives no context about the intended workflow or prerequisites, leaving an agent to guess based solely on the name.

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

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

No annotations exist, so the description carries the disclosure burden. It goes beyond a one-line summary by exposing non-obvious processing details: stripping preview/demo post-sign fields, JCS canonicalisation with both ASCII escaping modes, signer recovery, and checking against manifest signers. It does not disclose failure/return behavior, but the core behavior is transparent.

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

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

A single dense sentence front-loads the operation name, scope, and method, with no filler. Every clause adds meaningful detail about canonicalisation, signer recovery, and manifest comparison.

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

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

The description gives a thorough algorithm but omits the return/result semantics and failure behavior. Since there is no output schema, an agent is left to infer whether the tool returns a boolean, a report, or throws on mismatch. This is a notable gap for a verification 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 schema gives only the parameter name and a generic 'string' type. The description compensates by identifying the input as a signed nsgoods response and explaining what happens to it. It lacks an explicit example or formal schema, but it conveys the essential meaning of response_json.

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

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

The description opens with a precise verb and resource: 'Offline EIP-191 verify of a signed nsgoods response.' It also details the verification pipeline, making the purpose unmistakable and clearly distinct from the sibling statistics and status tools.

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

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

The intended use is implied: when one needs to cryptographically verify a signed nsgoods response offline. However, no explicit when-to-use guidance or comparison against alternatives is provided, though the sibling tools are sufficiently different that confusion is unlikely.

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

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

No annotations are provided, so the description carries the burden. It discloses the data source ('from the daily watcher') and scope, which is useful, but doesn't describe staleness, refresh timing, or whether the value is a snapshot vs. computed on demand.

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, information-dense sentence that front-loads the metric and scope. No wasted 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 zero-parameter status tool with no output schema, the description is mostly complete: it names the metric, scope, and data source. It could add a note about the output format or freshness, but nothing critical is missing for an agent to invoke it.

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

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

There are zero parameters, so the description doesn't need to explain parameter meaning. The baseline for 0 params is 4, and the description appropriately focuses on what the tool reports rather than inputs.

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

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

The description states a specific resource ('x401 emitter adoption') and a clear scope ('across the scanned catalogue'), sourced from the daily watcher. It distinguishes itself from generic stats tools by naming the exact metric, though it doesn't explicitly contrast with siblings like catalogue_stats.

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

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

The description implies this is a status/read-only tool for checking adoption metrics, and the zero-parameter schema makes usage trivial. However, it doesn't explicitly state when to prefer this over catalogue_stats or drift_status, leaving some routing ambiguity.

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