DeltaBot Utility Suite

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

With no annotations, the description must carry the burden of behavioral disclosure. It usefully discloses a $0.15 cost, but it does not state whether the operation has side effects, what 'crawl evidence' should look like, how results are returned, or any rate/access 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?

The description is exceptionally concise: two short sentences with no filler. The key cost detail is included, and the primary purpose is front-loaded. Additional explanation would be welcome but the existing text 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 paid tool with an unstructured input object, no output schema, no annotations, and many sibling tools, the description is far too incomplete. An agent cannot know how to format the crawl evidence, what fields to provide, what the report will look like, or what errors to expect.

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

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

The only parameter is an opaque free-form input object with no declared properties and 0% schema description coverage. The description mentions 'crawl evidence' but gives no structural detail, expected fields, examples, or meaning of the nested input object.

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 the tool as producing a broken-link report from supplied crawl evidence, which names a specific verb and resource. It does not clearly distinguish itself from sibling web-analysis tools like website_health or seo_meta_audit, but the broken-link focus is reasonably specific.

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 about when to use this tool versus the many sibling report tools. The phrase 'from supplied crawl evidence' hints at a precondition but does not explain when this tool is appropriate or when another report would be better.

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 present, so the description must carry the full burden of behavioral transparency. It does disclose the cost of $0.15 Base USDC, which is useful, but it does not mention side effects, required permissions, output format, or whether the input persists. The behavioral profile is largely unknown.

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 very short and front-loaded, with two sentences that each carry information: the core function and the cost. There is no redundancy or fluff. The main deficit is under-specification rather than poor 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 tool with one completely undocumented parameter, no output schema, no annotations, and many sibling report generators, the description is not complete enough for reliable invocation. It gives no input format, no expected output, and no selection context. Only the pricing detail adds a clue beyond the bare purpose.

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 schema description coverage at 0%, the description needed to thoroughly explain the 'input' parameter. It only says the input should contain 'factual changes,' which gives a weak semantic hint but no structure, required fields, formats, or examples. An agent cannot reliably construct a valid input object from this information.

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's purpose: producing a structured changelog from supplied factual changes. It is distinct enough from sibling tools by its changelog-specific noun, though it lacks an explicit verb and does not explicitly contrast itself with related generators.

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

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

No guidance is given about when to use this tool versus alternatives such as code_diff_summary or release_dependency_risk. The phrase 'supplied factual changes' suggests a precondition, but there are no explicit use cases, exclusions, or references to sibling tools.

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

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

With no annotations, the description must disclose behavioral traits itself, but it only adds the cost and 'factual' as a quality cue. It does not mention side effects, permissions, rate limits, or failure 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 short and the cost sentence is useful, but the brevity crosses into under-specification. It provides barely more information than the tool name and lacks input or usage context, so it is not appropriately sized for a tool with this opaque schema.

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 an opaque input schema, no output schema, no annotations, and many siblings, this description is far too minimal. An agent cannot infer expected input, return format, when to use it, or any operational requirements.

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 defines a single required 'input' as an opaque object with no property descriptions and 0% schema coverage. The description does not explain what the input should contain, such as diff text, repo references, or base/head commits, so an agent cannot construct valid input.

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 that the tool produces a factual summary of a code diff, which identifies the resource and general output. It lacks an explicit verb and does not distinguish itself from sibling tools, but the core purpose is reasonably clear.

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

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

No guidance is given about when to use this tool versus alternatives like changelog_generator or repository_change_radar. There are no context clues, exclusions, or conditions that would help an agent select it confidently.

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 of behavioral disclosure. It does disclose the cost ($0.20 Base USDC) and implies the input is ABI snapshots, but it does not explain the report format, expected ABI structure, failure modes, or whether any external calls or 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 description is short and front-loaded: the first sentence defines what the tool produces, and the second sentence adds cost information. No sentence is wasted, though the brevity leaves important invocation details out.

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 opaque input schema, lack of output schema, absence of annotations, and many sibling tools, this description is not complete enough for an agent to invoke the tool correctly. The agent knows a report about API changes is produced and that it costs money, but not how to supply the snapshots or what the response will look like.

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

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

The input schema is an opaque object with additionalProperties allowed and 0% description coverage, so the description must compensate. It only says 'supplied ABI snapshots' at a high level and does not explain how the snapshots should be structured, how many are needed, or which fields denote the old versus new ABI. This is minimal meaningful semantical guidance.

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 deliverable ('Contract ABI change report') and its source data ('supplied ABI snapshots'), which makes the tool's function reasonably clear and distinct from generic change-report siblings. However, it lacks an explicit action verb like 'compare' or 'generate', so the exact operation is somewhat inferred.

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 use this tool versus alternatives such as json_change_report, openapi_difference_report, or code_diff_summary. The only extra directive is the cost, which is not a usage condition or selection criterion.

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 of disclosure. It only mentions a cost, not what inputs are accepted, what the tool returns, whether it mutates anything, whether it accesses remote data, or what 'profile' means operationally. This is a serious transparency gap.

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

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

The description is short, but this is under-specification rather than efficient conciseness. It contains only a name-like phrase and a cost, with no structural organization, examples, or additional context that would help an agent use the tool.

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 tool has a single undocumented nested input object and no output schema, yet the description provides no operational context, parameter hints, or return expectations. The cost note is the only useful detail. This is inadequate for reliable tool selection and invocation.

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

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

Schema description coverage is 0%, and the single required input is an untyped object with additionalProperties: true and no properties. The description adds nothing about how to structure input or what the tool expects, so an agent has no way to correctly construct a call.

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 'CSV structure and completeness profile' is essentially a restatement of the tool name, with only slightly more detail about what aspects are profiled. It does not name a clear verb or action, and it does not differentiate this tool from the sibling data_quality_profile, which likely covers similar ground.

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 use this tool versus csv_to_json, data_quality_profile, or other siblings. The cost note is useful but does not clarify selection criteria, prerequisites, or 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 behavioral disclosure burden. It does disclose a non-obvious $0.10 Base USDC cost and states a transformation behavior, which is useful context. However, it does not mention input transport, validation behavior, error cases, or whether the JSON is returned directly or stored.

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 very concise and front-loaded, with the cost note adding non-redundant information. It is structurally clean, though it sacrifices operational detail for brevity.

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 output schema and a fully unstructured required input object, this description is incomplete. An agent cannot reliably construct the `input` value or understand the expected return shape. The cost disclosure is the only added contextual signal beyond the name.

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

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

The input schema is an opaque object with zero property documentation, and the description does not explain what fields or format the `input` parameter should use. The only hint is that CSV data is somehow converted, leaving the agent to guess whether input is raw CSV text, a file path, a URL, or nested key-value pairs.

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 operation as CSV-to-JSON conversion, which is a specific transformation with an explicit action and resource. It does not explicitly differentiate itself from csv_profile, but the conversion wording is enough to convey the core purpose.

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 about when to choose this tool over siblings like csv_profile or the other report generators. The only usage signal is the implicit meaning of 'conversion,' and there are no prerequisites, alternatives, or exclusions 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 must carry the behavioral disclosure burden. It does disclose the actual checks performed and the $0.10 Base USDC cost, which are useful behavioral traits. However, it does not state whether the operation is read-only, what output or return format to expect, how invalid JSON is handled, 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 description is two short sentences with no filler. It leads with the action and resource, then gives the cost. Every sentence adds necessary information and the structure is highly scannable.

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

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

With no annotations, no output schema, and a generic input schema, the description omits critical context: how to structure the input, what the response looks like, error behavior, and whether payment is required upfront or per-use. The cost disclosure is helpful, but too much operational detail is missing for an agent to confidently invoke this 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 provides no property details for the single 'input' parameter, and schema description coverage is 0%. The description only says 'JSON records' without explaining whether input should be an array, an object, a file path, or a JSON string. This is insufficient to compensate for the schema's silence.

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 JSON data-quality checker with specific verbs and targets: checking for missing fields, data types, duplicates, and data shape. This differentiates it from siblings like csv_profile and json_schema_validator, which are either CSV-specific or schema-oriented.

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 tool is for assessing JSON record quality, but it does not explicitly state when to use it versus alternatives like csv_profile or json_schema_validator. There are no exclusions, prerequisites, or when-not-to-use instructions, so the agent has to infer the appropriate 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?

There are no annotations, so the description carries the full burden of behavioral disclosure. It does disclose the monetary cost of $0.15 USDC, which is useful, but it does not mention whether the operation is read-only, what side effects exist, or what the output format is.

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 two short sentences, front-loads the core purpose, and every sentence adds relevant information. The cost notice is concise and valuable.

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 open-ended input schema, lack of output schema, and absent annotations, the description is too thin. It tells the agent what the tool generally does but not how to format the input, what response to expect, or when to choose it over nearby report 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?

The schema describes only an open 'input' object with no properties, and the description adds only the vague concept of 'supplied metadata'. An agent cannot determine what specific metadata fields are required or what shape the input should take.

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 producing a dependency license inventory from supplied metadata. It distinguishes itself from related siblings like release_dependency_risk by focusing specifically on licenses, though it lacks an explicit action verb.

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

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

No guidance is given about when to use this tool versus alternatives such as release_dependency_risk or when metadata must be supplied. The phrase 'from supplied metadata' implies a prerequisite but never states it explicitly.

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 the $0.15 Base USDC cost, which is a meaningful behavioral detail, but it does not state whether the operation is read-only, whether it makes external network requests, what side effects occur, or what the return behavior is.

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 concise sentence with no filler. The cost disclosure is front-loaded and useful. However, it is so brief that it omits important behavioral and parameter details, so it is not a perfect example of concise completeness.

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 empty input schema, lack of annotations, and absence of an output schema, the description does not provide enough context for an agent to reliably invoke the tool. Key missing information includes the exact input format, expected output, payment handling, and whether this is a live network lookup or a local computation.

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

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

The input schema provides no property definitions and 0% schema coverage, so the description must compensate. 'From supplied public records' gives a general hint about what the input contains, but it does not specify the expected structure, required fields, or format of those records.

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 producing a DNS and domain snapshot from supplied public records, so an agent can grasp the core function. It does not explicitly contrast with sibling tools, but the domain-specific resource is distinct enough to avoid obvious confusion.

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 about when to prefer this tool over alternatives or when to avoid it. The phrase 'from supplied public records' hints at the input source, but no use-case context, prerequisites, or exclusions are provided.

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 concrete cost of $0.15 Base USDC and hints that snapshots are inputs rather than fetched, but it does not explain whether the tool compares two snapshots, what outputs it returns, whether network access is needed, or any authentication 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?

The description is a single front-loaded sentence with no wasted words. It leads with the tool's core function and then provides the important cost detail, which is relevant for agent decision-making.

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 no annotations, an opaque input schema, and no output schema, the description is far too thin to support correct invocation. It conveys the general purpose and cost but leaves essential details about input formatting and expected output unresolved.

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

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

The input schema is essentially opaque: a required nested object with no defined properties and additionalProperties true. With 0% schema description coverage, the description must explain how to provide parameters, but it only vaguely mentions 'supplied snapshots' without specifying keys, formats, or snapshot structure.

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, RSS or Atom feeds, and states the tool produces a change report from supplied snapshots. It is clearly distinguishable from generic sibling tools like json_change_report or changelog_generator by its feed-specific scope, though it lacks an explicit verb and does not name an alternative.

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

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

No guidance is given about when to use this tool versus the many sibling change-report and diff tools. The phrase 'from supplied snapshots' implies a prerequisite, but there is no explicit context, exclusions, or alternative selection 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 burden of behavioral disclosure. It does add a useful behavioral detail—the $0.15 Base USDC cost—and hints that records are supplied rather than fetched. However, it omits whether the tool makes network calls, whether it is read-only, what failure modes exist, or how the digest is returned.

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 compact two-sentence definition with the core purpose first and the cost second. Both sentences add information and there is no filler, though the content is too sparse to fully address the tool's ambiguous input.

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 an opaque free-form input object, no output schema, no annotations, and no usage context, the description is far from complete. An agent cannot confidently determine what to pass in the 'input' property, what fields the digest will contain, or how the cost is applied.

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

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

The single 'input' parameter is an empty object schema with additionalProperties allowed, giving zero structural information, and schema description coverage is 0%. The description only vaguely says 'from supplied public records' and does not explain the expected shape, required fields, formats, or 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 resource ('GitHub issue and pull-request') and the deliverable ('digest'), so an agent can tell what the tool produces. It is not a tautology and it distinguishes itself from sibling report tools by its focus on GitHub issues/PRs, though it lacks an explicit verb 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?

There is no guidance on when to choose this tool over similar siblings like repository_change_radar or changelog_generator. The phrase 'from supplied public records' implies the input is user-provided public data, but it does not explain prerequisites, exclusions, or when not to use the tool.

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

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

With no annotations, the description carries the burden. It discloses cost, which is a useful behavior, but says nothing about input delivery, return structure, error behavior, or side effects. This is too little for an un-annotated 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?

The description is extremely short, no filler, and front-loads the extraction capability before stating cost. However, the brevity leaves out essential behavioral and semantic details, so it is under-specified rather than genuinely 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?

For a tool with one undocumented input parameter and no output schema, the description is far from complete. An agent lacks the information to construct a correct call or interpret the response.

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 only parameter 'input' has no schema properties and 0% schema coverage; description never explains what 'input' should be (HTML content vs. URL). It adds zero meaning beyond the schema.

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

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

States a clear extraction purpose listing concrete outputs (title, metadata, headings, links) and resource (HTML). However, it doesn't differentiate from sibling tools like seo_meta_audit or website_health which may also analyze HTML.

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 use this tool vs the many sibling report and audit tools. No prerequisites or input format stated; an agent cannot determine whether this is for a URL, HTML file, or raw string.

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 a cost of $0.15 Base USDC and constrains input to public snapshots, which are relevant behavioral traits. However, it remains silent on whether the operation is read-only, how data may be handled, or any rate limits or side effects.

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

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

The description is a single sentence that leads with the verb and resource, then appends the cost. It contains no filler or redundant information, making it an excellent example of conciseness and front-loading.

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 tool has one required parameter, but the schema gives no field definitions, there is no output schema, and no annotations exist. The description does not specify the input structure, return value, or invocation workflow, leaving a critical gap for an agent attempting to call the tool correctly. Cost disclosure helps but does not compensate for the missing operational details.

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

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

Schema coverage is 0%: the single required parameter 'input' is an untyped object with additionalProperties true and no property definitions. The description adds only the concept of 'JSON snapshots' but fails to explain how these should be structured, such as whether they are an array, object keys, URLs, or raw JSON strings. An agent cannot construct a valid input from this description alone.

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 ('Find added, removed, and changed fields') on a specific resource ('public JSON snapshots'), making the core purpose clear. It doesn't explicitly differentiate from sibling diff tools like openapi_difference_report or code_diff_summary, but the JSON-snapshot framing provides enough scope distinction.

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

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

The description offers no guidance on when to use this tool versus alternatives. There is no mention of suitable conditions, exclusions, or references to sibling tools. The phrase 'public JSON snapshots' hints at a use case but does not give actionable when-to-use direction.

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 burden of behavioral disclosure. It adds the important cost detail ('Costs $0.10 Base USDC') and implies a read-only inference operation. However, it does not disclose output format, size limits, error behavior, or whether data is transmitted/stored.

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 short sentence plus a cost notice. It is front-loaded and contains no filler or redundant 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?

The tool is simple with a single parameter, and the description covers the basic purpose and cost. However, with no output schema and no param descriptions, it would benefit from explicitly stating the return type and any input constraints. It is adequate for a simple tool but leaves some 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 description coverage is 0%, so the description must compensate, but it only says 'supplied JSON value,' which essentially restates the parameter name 'input.' It does not clarify whether the value must be an object (as the schema requires) or whether arrays/primitives are accepted. Minimal added meaning beyond the empty property schema.

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

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

The description states a specific verb ('inference'), a specific resource ('JSON Schema'), and the required input ('supplied JSON value'). It clearly distinguishes this tool from the sibling json_schema_validator, which validates rather than generates schemas.

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

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

The description implies the tool should be used when a JSON Schema needs to be inferred from an existing JSON value, but it does not explicitly discuss when to use it versus alternatives such as json_schema_validator or csv_to_json. There is no 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?

With no annotations provided, the description carries the full behavioral disclosure burden, but it only mentions the cost and the vague validation purpose. It does not indicate whether this is a read-only operation, what inputs are expected, what outputs are produced, or how errors are surfaced.

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 very short, but brevity here results from under-specification rather than efficient writing. The two sentences provide only a vague function and a cost, leaving critical details absent.

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?

Even for a simple one-parameter tool, the description is incomplete: it does not specify whether the input is a schema or data, what validation result is returned, what failure modes exist, or how the cost applies. Without an output schema or annotations, this is insufficient for an agent 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 describes a single 'input' object with no properties and additionalProperties allowed, providing no meaningful structure. The description does not explain what should go into the input or how the validator interprets it, so the parameter semantics are essentially empty.

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 'JSON Schema validation' essentially restates the tool name 'json_schema_validator' without a clear verb or operation. It is ambiguous whether the tool validates a JSON document against a schema or validates the schema itself, and it does not distinguish itself from sibling tools beyond the obvious generation/validation contrast.

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

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

The description provides no guidance about when to use this tool versus alternatives like json_schema_generator or data_quality_profile. The only additional context is the cost note, which does not help an agent decide when to invoke the tool.

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

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

No annotations are provided, so the description must carry the behavioral disclosure burden. It does add the cost detail ('$0.20 Base USDC'), but it does not clarify whether the tool fetches public snapshots, whether it is read-only, what it returns, or what 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?

Two short sentences, front-loaded with the core function and followed by the key cost constraint. There is no wasted wording or irrelevant detail.

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 that likely needs two snapshot sources and produces a diff report, the description omits input shape, output format, and any usage constraints. The cost disclosure helps, but an agent still cannot confidently invoke the tool based on this definition alone.

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

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

The input schema has a single generic 'input' object with empty properties and additionalProperties allowed, so schema documentation is effectively zero. The description gives only a vague domain clue ('between public OpenAPI snapshots') and does not specify actual input fields, formats, or examples.

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 uses a specific verb ('Find') and a precise resource: added, removed, and changed API paths and operations between public OpenAPI snapshots. This clearly distinguishes it from siblings like openapi_health_score or code_diff_summary.

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 states what the tool does but gives no guidance on when to choose it over alternatives, nor does it mention prerequisites or exclusions. Without a reference to sibling tools or edge cases, an agent gets no routing help.

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 present, so the description carries the full burden of behavioral disclosure. It does disclose a notable financial behavior—'Costs $0.15 Base USDC'—which is useful, but it does not describe side effects, authorization requirements, or expected output behavior beyond the name itself.

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 very brief and front-loaded with the core purpose, followed by a useful cost disclosure. No words are wasted, and both sentences add relevant information, though the brevity contributes to significant gaps covered in other dimensions.

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 tool has no annotations, no output schema, and a free-form input schema, yet the description only mentions the tool's purpose and cost. There is no explanation of the expected input format, the output shape, or any usage constraints, making this definition inadequate for an agent to invoke 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?

Schema description coverage is 0%, and the input schema is an empty object with additionalProperties allowed. The description provides no detail about what the 'input' parameter should contain—whether it is an OpenAPI document, a URL, a JSON string, or a file path—leaving the agent unable to construct a valid invocation.

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 producing an OpenAPI completeness and health score, which conveys the core function and distinguishes it in a general way from sibling tools like openapi_difference_report. However, it lacks an explicit verb such as 'computes' or 'generates,' and it does not directly contrast with sibling 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?

No guidance is provided about when to choose this tool over alternatives like openapi_difference_report, json_schema_validator, or website_health. The description only states what the tool does and its cost, leaving the agent to infer appropriate usage conditions.

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 of behavioral disclosure. It does disclose the $0.15 Base USDC cost and that the report comes from supplied snapshots, but it does not state what the input snapshots must look like, whether any data leaves the environment, what side effects occur, or what the output format is.

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

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

The description is short and front-loaded with the core purpose, followed by the cost in a separate sentence. It contains no filler, but the brevity also reflects a lack of necessary detail.

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 tool has an opaque nested input schema, no output schema, and no annotations, yet the description provides almost no operational context. An agent would not know how to supply snapshots, what parameters to include, or what the resulting report will contain, making the description materially incomplete.

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

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

The input schema is a generic object with no properties and additionalProperties allowed, and schema description coverage is 0%. The description only says 'supplied snapshots' but gives no structure, required fields, or format, so an agent cannot determine how to construct the input correctly.

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 resource (storefront price and availability) and the output (change report) from supplied snapshots. It is specific enough to distinguish it from sibling report tools like json_change_report or feed_change_report, though it lacks an explicit verb like 'generates' or 'compares.'

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 use this tool versus alternatives such as feed_change_report, json_change_report, or data_quality_profile. The only hint is that snapshots are supplied, but no conditions, exclusions, or alternative naming are provided.

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 behavioral context; it does disclose a $0.20 Base USDC cost and characterizes output as 'factual', but it omits whether the tool is read-only, what side effects occur, what auth is needed, or what the returned data looks 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?

Two brief sentences – the first states the function and the second notes the cost. No filler.

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

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

For a tool with an opaque free-form input, no output schema, and no annotations, the description is far too sparse. It doesn't explain how to supply metadata, what output format to expect, or any prerequisites, so an agent would struggle 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 only parameter 'input' is an open object with additionalProperties true and zero schema descriptions; the description only hints that the input is 'public metadata' without defining expected fields or structure, so it fails to compensate for 0% schema coverage.

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

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

The description uses the verb 'Create' and names concrete outputs ('release notes and dependency risk flags') plus the source ('supplied public metadata'), which clearly identifies the tool's function. It does not explicitly contrast with sibling tools like changelog_generator, so it doesn't fully earn the top score.

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 when-to-use or alternative guidance is provided. The description doesn't mention when to choose this over changelog_generator or dependency_license_report.

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 add some useful behavioral context: the cost ($0.25 Base USDC), the 'public repository snapshots' scope, and the phrase 'factual' implying evidence-based output. However, it does not disclose whether the tool fetches data itself, how it handles inputs, failure modes, or operational 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?

The description is compact, front-loaded with the main action, and each sentence earns its place by adding cost or purpose. It is concise, though slightly too sparse for the complexity implied by the opaque input schema.

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

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

Given no annotations, no output schema, and a nearly empty input schema, the description is the only source of operational context. It provides purpose and pricing but omits input structure, output format, usage context, and limitations, leaving significant gaps for an agent trying to invoke 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 schema exposes only an opaque 'input' object with no properties and additionalProperties: true, and schema coverage is 0%. The description hints that the input should contain public repository snapshots, but it does not specify the format, keys, or how the snapshots are represented, so an agent cannot construct valid parameters from the available information.

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 ('Compare supplied public repository snapshots') and a clear deliverable ('factual change and risk evidence'), so an agent can understand the core function. It does not explicitly differentiate from siblings like code_diff_summary or release_dependency_risk, but the 'public repository snapshots' framing is reasonably distinctive.

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 use this tool versus the many change/diff/report siblings. The description does not mention use cases, prerequisites, exclusions, or alternative tools, leaving the agent to infer selection criteria.

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 $0.15 Base USDC cost and clarifies that the audit is based on supplied facts rather than a live fetch. It does not mention output format, errors, or side effects, so meaningful behavioral gaps remain.

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 short sentences with no filler. Purpose and cost or front-loaded, and each word contributes to agent understanding.

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 are no annotations, no output schema, and the input schema is effectively empty. The description omits the expected fact fields, the audit criteria, and the return value, making it incomplete for reliable 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 input schema only defines an empty 'input' object with additionalProperties true, and schema description coverage is 0%. The description's 'public page facts' gives a general semantic hint, but it does not enumerate expected fields such as page title, meta description, canonical, or robots directives, so an agent cannot know what to populate.

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 uses a specific verb ('audit') and resource ('SEO metadata'), and clarifies that it operates on supplied public page facts. This distinguishes it from crawling-oriented siblings like website_health and sitemap_robots_audit, though it does not explicitly name an alternative.

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

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

The phrase 'from supplied public page facts' implies the tool should be used when the caller already has page facts rather than needing to crawl the page. However, no explicit when-to-use/when-not-to-use guidance or alternative sibling tools are mentioned, leaving the usage condition largely implicit.

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?

There are no annotations, so the description carries the full behavioral burden. It discloses the $0.15 cost and that files must be public and supplied, but it does not explain side effects, network behavior, required permissions, rate limits, or what kind of result is returned.

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 two short, front-loaded sentences with no filler. The core purpose and cost are both stated efficiently and every sentence adds useful information.

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

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

For a paid audit tool with an opaque input schema and no output schema, the description is not complete enough. It omits the expected input structure, the scope of the audit, and the shape or content of the results, leaving an agent unable to reliably invoke and interpret 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 schema describes a single 'input' object with no documented properties and 0% schema description coverage. The phrase 'supplied public files' gives a hint about the intended input, but the description does not specify what keys, file formats, URLs, or payload structure the agent should provide.

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 resource being audited (sitemap and robots.txt) and states that it works from supplied public files. This is enough to distinguish it from sibling tools like seo_meta_audit or website_health, though it does not enumerate what the audit actually checks.

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

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

No guidance is given for when to use this tool versus alternatives such as seo_meta_audit or broken_link_report. There are no exclusions, prerequisites, or conditions to help an agent choose it correctly.

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

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

No annotations are provided, so the description must carry the full behavioral burden. It adds the cost detail ('Costs $0.15 Base USDC') but does not clarify whether the tool performs a live network probe, consumes an existing probe payload, what the response looks like, or whether any side effects occur. The input semantics are also ambiguous.

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 short sentences with no filler: the first front-loads the tool's purpose, the second conveys the price. Every word contributes useful signal.

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 omits critical execution details: how to structure the probe input, what fields the probe must contain, what the report should include, and what the return format is. The tool is simple in parameter count but still under-specified for reliable autonomous 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 nested 'input' object with no documented properties and zero schema description coverage. The description only says a 'supplied HTTPS probe' is needed, but an agent cannot determine required fields, format, or how to structure the probe input.

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 deliverable ('TLS and security-header report') and the input context ('from a supplied HTTPS probe'), which clearly differentiates it from sibling report tools like website_health or seo_meta_audit. Despite lacking an explicit verb, 'report' conveys the expected action unambiguously.

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

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

The phrase 'from a supplied HTTPS probe' implies when to use it: when an HTTPS probe is available and a TLS/security-header assessment is needed. However, it names no alternatives, exclusions, or conditions for choosing this tool over related 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 an important cost of $0.15 Base USDC, adding useful behavioral context. It does not mention side effects, authentication, output behavior, or whether the supplied records are sent somewhere, but for a primarily analytic tool the cost disclosure partially compensates.

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

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

The description is compact and front-loaded, placing the main purpose before the cost note. Every sentence adds information, and there is no filler or redundant repetition of the tool name.

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 absence of annotations and an output schema, plus an almost fully open-ended input schema, the description is too thin for an agent to confidently invoke the tool. It lacks input format details, expected output description, and any guidance on how the supplied transaction records should be passed. The cost note is helpful but does not resolve these 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?

The input schema defines a single 'input' object with no properties and additionalProperties allowed, and schema description coverage is 0%. The description says the tool works 'from supplied public transaction records,' which indicates what belongs in the input object, but it does not specify how the records should be structured, what fields are expected, or what format is required. This leaves significant ambiguity.

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 that the tool produces a wallet activity summary from supplied public transaction records, naming both the resource (wallet activity) and the data source. It goes beyond a tautology, though it does not explicitly use a verb like 'generates' and does little to differentiate from sibling summary/report tools beyond the wallet-specific topic.

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 'from supplied public transaction records' implies the tool should be used when such records are available and a wallet activity summary is desired. However, it gives no explicit guidance on when to use this tool versus alternatives, no exclusions, and no mention of prerequisites or input format expectations.

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 present, so the description carries the full burden of behavioral disclosure. It does add valuable operational context by mentioning the $0.15 cost and HTTPS probe input, but it does not describe output contents, health metrics, failure modes, auth needs, or side effects. This is insufficient for an unannotated paid 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?

The description is a single sentence with no unnecessary words, and the cost is stated efficiently. It is front-loaded with the core purpose and adds a key practical detail, though the brevity also leaves out important operational specifics.

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

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

Given no annotations, no output schema, a nested free-form input object, and many sibling audit/health tools, this description is materially incomplete. It does not define what 'website health' includes, what the report contains, or how to structure the input. It reads as a one-line summary rather than a callable specification.

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 required 'input' object is free-form with no property definitions. The phrase 'from a supplied HTTPs probe' hints that the caller should supply a probe/url, but it does not specify what keys or format belong inside the input object. An agent would have to guess the expected input structure.

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 website health report produced from a supplied HTTPS probe, which goes beyond merely restating the tool name. However, 'health' is undefined, and there is no comparison with sibling report/audit tools like broken_link_report, tls_header_report, or openapi_health_score, so an agent cannot tell what specific health dimensions are covered.

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 use this tool instead of its siblings. The description does not state prerequisites, exclusions, or alternative conditions. The cost note is operationally useful but does not help an agent decide between website_health and similar audit or report tools.

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