Sighttrue

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

No annotations are provided, so the description carries full behavioral disclosure. It discloses the need for a key (authentication requirement) and gives a sense of the output (identifiers and dates grouped by severity). However, it does not explicitly state whether this is a read-only operation, nor does it mention any rate limits, error conditions, or response shape. For a simple query tool, this is adequate but not thorough.

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 concise: two sentences. The first states the core purpose, the second addresses the key requirement. No unnecessary words, and the information is front-loaded. Every sentence earns its place.

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

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

Given the tool's low complexity (2 params, no output schema, no annotations), the description provides a reasonable overview: it clarifies what the tool returns (advisories with identifiers/dates by severity) and the prerequisite (key). However, without an output schema or mention of the response structure, and with an undescribed 'registry' parameter, an agent may need additional inference to fully understand the expected input and output.

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

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

The description does not mention any parameters, adding no meaning beyond the input schema. The schema describes 'name' but not 'registry', leaving 50% coverage. The description fails to compensate for the missing registry description or provide any parameter-specific context, making parameter understanding incomplete.

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 it provides advisories broken down by severity with identifiers and dates, which implies a listing/retrieval tool. However, it lacks a clear verb (e.g., 'list', 'get') and does not explicitly mention that it operates on a specific package/registry, leaving the scope to be inferred from the parameters. It does distinguish itself from a counting tool by saying 'rather than counted', but does not name the 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 only usage guideline is the requirement for a key, with a link to pricing. There is no explicit statement about when to use this tool versus sibling tools, nor any exclusions or prerequisites beyond the key. The 'rather than counted' hint suggests a contrast with a count-focused tool, but no alternative is named, so guidance is minimal.

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 full responsibility for behavioral disclosure. It adds useful context about output ordering ('ordered by how much a reviewer would want to know') and authentication ('Requires a key'), but lacks details on error handling, rate limits, or the read-only nature beyond the verb 'read'.

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

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

Three concise sentences front-load the core purpose, add a value proposition, and note authentication. Every sentence earns its place with no redundant information, making it highly efficient.

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 covers the primary function, ordering, and authentication, but it does not explain the return structure ('every reading' is vague), the optional 'filename' parameter, or potential failure modes. Given no output schema and two parameters, this is a notable gap.

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

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

Schema description coverage is 0% and the description does not compensate. The required 'manifest' parameter is not explained (e.g., whether it is a path, content, or identifier), and the optional 'filename' parameter is ignored entirely. The description adds minimal meaning beyond the schema property names.

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 ('Read') and resource ('whole manifest'), clearly stating the function and output ('return every reading on record'). It also distinguishes itself from sibling tools by emphasizing 'One call instead of one per dependency', which sets it apart from per-package check 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 phrase 'One call instead of one per dependency' provides clear guidance on when to use this tool versus checking dependencies individually. It also mentions a prerequisite ('Requires a key'), but does not explicitly name alternative tools or state when not to use it.

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 the need for an API key and the specific data points returned, but does not mention potential error conditions, network behavior, or how OS support is determined.

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

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

Two sentences with no fluff; the first sentence front-loads the core functionality, the second adds the authentication requirement.

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

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

For a single-parameter tool with no output schema and no annotations, the description covers the main purpose and one prerequisite, but omits guidance on return value details or edge cases, making it minimally sufficient rather than complete.

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

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

The schema provides only a parameter name 'image' with no description. The tool description adds that it refers to a container base image, giving the parameter context, but does not specify expected format (e.g., tag, digest) or provide examples, so meaning is still limited.

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

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

The description clearly states the tool provides size, last rebuild date, and OS support status for a container base image. This distinguishes it from sibling tools focused on packages, providers, and EOL 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?

The description implies usage for inspecting base image details but does not explicitly compare to alternatives such as check_eol, which may overlap on OS support. The only usage condition mentioned is the requirement for a key, which is a prerequisite rather than a selection guideline.

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

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

With no annotations provided, the description carries the full burden and does well: it discloses that the tool returns only factual records, each fact carries the publisher's address, and it explicitly avoids making an install decision. It does not mention potential side effects, errors, or rate limits, but for a 'check' tool the main behavioral traits are well covered.

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 three sentences, front-loaded with the key usage instruction, and every sentence adds substantive detail (what facts, their provenance, and the tool's non-decisional nature). It is slightly dense but not verbose, and there is no filler or repetition.

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

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

Given there is no output schema and no annotations, the description is remarkably complete: it enumerates the main result categories and their provenance, and explicitly states the tool's scope (record-only, no recommendation). It lacks edge-case behavior (e.g., package not found) and registry parameter details, but for a simple two-parameter tool it covers the essential context well.

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 the 'name' parameter well ('Package name as the registry spells it') but leaves 'registry' as a bare string with no explanation. The description does not compensate for this gap; it never explains what registry values are valid, where the registry is, or how the two parameters interact. With only 50% schema coverage, the description should have added this crucial context.

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 ('check before install'), clearly identifies the resource (a dependency), and enumerates the exact facts returned (withdrawn, scripts, archived, advisories, license, publish time). It also distinguishes itself from sibling tools by stating it only reports facts and does not make an install recommendation, making the purpose unmistakable.

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

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

It explicitly says 'Call this before adding a dependency', which is a clear when-to-use directive. It also explains what the tool does not do (does not say whether to install), providing an implicit exclusion. However, it does not name specific alternative tools for cases when the user wants a recommendation or deeper analysis, so it falls short of a full 5.

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

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

No annotations are provided, so the description carries the transparency burden. It adds context about the data source (endoflife.date), update frequency (read daily), and product scope, but does not disclose return format, failure modes, or explicit read-only behavior. The inferred read-only nature from 'Check' helps, but more behavioral detail would be useful.

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

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

The description is two sentences, front-loads the main purpose, and adds a concise scope note. Every word earns its place, with no repetition of the tool name or unnecessary details.

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 check tool with two params and no output schema, the description covers the essential purpose, scope, and data source. It lacks explicit output format details and usage alternatives, but these are somewhat inferable. The description is adequately complete for its complexity.

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

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

Schema description coverage is 100% with both 'product' and 'cycle' fully described. The tool description adds no extra parameter meaning beyond the schema. Baseline of 3 applies since the schema already documents parameters adequately.

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 specific verb 'Check' with a clearly defined resource ('runtime, database or framework release') and outcome ('still receiving security fixes, and what to move to'). This distinguishes it from sibling tools by focusing on security-fix status and migration targets, not just generic EOL 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?

The description gives no explicit guidance on when to use this tool versus alternatives. It lacks any 'use this when' or 'for X, use Y' statements. The scope note about covering two dozen products is a limitation, not usage context.

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

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

With no annotations, the description carries the full burden for behavioral disclosure. It explicitly states 'Read', indicating a non-destructive operation, which is critical context. However, it does not disclose other potential behavioral traits like network dependence, rate limits, or whether data is cached, but the read-only nature is well established.

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, efficient sentence that front-loads the verb and resource, then enumerates the return fields in a colon-separated list. It is compact and avoid unnecessary words, though slightly long due to the list.

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 an output schema, the description adequately lists the return fields, which is helpful. However, it does not explain how to specify the registry parameter or handle error cases, and it omits any prerequisites or conditions. Still, it is fairly complete for a read-only status 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 description covers only the 'name' parameter. The 'registry' parameter has no schema description, and the tool description does not compensate by clarifying what registry values are valid or how to reference them. This leaves an important gap for agents to correctly invoke the tool.

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

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

The description uses the specific verb 'Read' and identifies the resource as 'one open-source package', clearly stating the scope and the data points covered (downloads, OpenSSF scorecard, advisory count, license, archived status, last push). This distinguishes it from more focused sibling tools like check_eol or typosquat_check.

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

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

There is no explicit guidance on when to use this tool versus alternatives. The description implies it is a general status snapshot, but it does not mention when to prefer it over focused tools or any exclusions such as specific registries or package types.

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 that incidents are retained in the system after being dropped from the provider's status page, which is valuable context. However, it does not describe the output format, possible empty results, or any errors. It also doesn't explicitly state that this is a read-only operation, though that is implied.

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, well-structured sentence that front-loads the core concept ('Recorded incidents') and includes the key differentiator. Every phrase earns its place; it is concise without unnecessary fluff.

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

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

Given the tool has no annotations and no output schema, the description should explain what the return value looks like. It does not, leaving the agent uncertain about the response structure. However, the tool is a simple read-only lookup, and the schema covers parameters. The description does clarify the historical nature, which is key, but omits output 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 description coverage is 50%: the provider parameter is well-described in the schema, but days has no description. The tool description's 'over a window' is an indirect reference to days but does not add concrete meaning. The description does not compensate for the missing days explanation, but the parameter name and constraints provide some clarity.

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 returning recorded incidents for hosting/API providers over a time window. It differentiates itself from siblings by specifying that these incidents are retained after the provider's own status page drops them, which distinguishes it from provider_incidents or other status-related tools. The scope is specific: provider and time window.

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 usage when historical incidents are needed (since they are kept after the provider's status page drops them), but it does not explicitly state when to use this tool versus alternatives like provider_incidents, nor does it specify exclusions. The context is clear but not fully explicit.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It states the tool 'reads' and describes the types of findings it reports (archived, advisories, source-available license, no push in a year), which is useful. However, it does not disclose network behavior, authentication requirements, error handling, or performance implications, leaving notable gaps.

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 straightforward sentences. The first sentence front-loads the core functionality and outputs, the second provides usage context. No fluff, no redundant information, and every sentence earns its place.

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

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

Given that there is no output schema, the description adequately conveys the return categories (archived, advisories, source-available licence, no push in a year). It also specifies the input formats (manifests). However, it omits details on parameter semantics and error behavior, so it is not fully complete for a tool that would benefit from such context.

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

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

The input schema has zero descriptions for the two required parameters ('names' and 'registry'). The description implies that 'names' is the list of package names from a dependency file and that the tool checks them against a registry, but it never explains the 'registry' parameter's possible values or format. This is insufficient for a 0% schema coverage case.

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

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

The description clearly states the tool's purpose: to read a whole dependency list and report on archived packages, advisories, source-available licenses, and stale packages. It uses a specific verb ('Read') plus a well-defined resource ('dependency list') and distinguishes itself from siblings like check_package by focusing on bulk analysis rather than individual packages.

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 explicit usage context: 'Use when reviewing a package.json, requirements.txt, Cargo.toml, composer.json or Gemfile.' This tells the agent when to invoke the tool, but it does not explicitly state when not to use it or mention alternative tools, so it falls short of a 5 but exceeds a 3.

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 valuable context: it only compares, does not pick a winner, and reports on specific dimensions. This implies a read-only, non-decisional operation. It does not explicitly state side effects or error behavior, but the 'compares only' phrasing is a meaningful boundary.

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 concise: two sentences, the first states the core purpose with specific examples of compared metrics, the second clarifies a key boundary ('does not pick a winner'). Every word earns its place; there is no redundancy or filler.

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

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

For a simple two-parameter comparison tool with no output schema, the description covers the essential context: what it compares, the scope (watched repos), and the non-decisional nature. It lacks details on return format or failure cases, but given the tool's simplicity and the listed metrics, it is reasonably complete.

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

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

The schema already provides full descriptions for both parameters (owner/name format), so the baseline is 3. The description adds the 'watched' constraint, which is useful context but does not alter the parameter format or semantics significantly.

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

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

The description clearly states the tool's purpose: comparing two watched repositories across specific dimensions (downloads, OpenSSF scorecard, advisories, forks, stars, findings). It distinguishes itself from sibling tools by being the only comparative tool and explicitly clarifies it does not pick a winner, leaving no ambiguity about its role.

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

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

The description implies the use case: comparing two watched repositories. The qualifier 'watched' is a clear prerequisite. However, it does not explicitly mention when not to use this tool or suggest alternative tools, such as check_package, which could be relevant for single-repository analysis.

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

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

With no annotations, the description carries the full burden. It usefully notes that the operation reads from a daily archive and requires a key, but it does not disclose output format, pagination/error behavior, or limitations such as archive depth.

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

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

A single, front-loaded sentence conveys the core purpose, data source, and auth requirement without any redundant wording. The pricing link is a useful addition and does not clutter the description.

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 two parameters and no output schema, so the description covers the essential idea. However, the absence of annotations and return-value explanation leaves some gaps, such as how the diff is represented or how 'changed' is defined.

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

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

The schema documents only 'since' with a format, while 'names' is an undocumented array. The description clarifies 'names' as a set of packages and reinforces the meaning of 'since', adding moderate value, but it does not specify constraints like non-empty arrays or duplicate handling.

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

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

The description clearly states the tool reports what changed for a set of packages since a given date, reading from the daily archive. This distinguishes it from siblings like watch_changes and package_weight_history, though it uses the noun phrase 'what changed' rather than an explicit verb like 'list' or 'get'.

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 on when to use this tool versus alternatives, and there are no examples or exclusion criteria. The key requirement is mentioned, but the description does not help the agent decide between diff_since and the many similar 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?

No annotations are provided, so the description carries full responsibility. It discloses the key requirement but does not reveal whether the tool performs network lookups, returns a boolean, or handles cases where domains are missing or unregistered. This is insufficient for a tool with no annotation safety hints.

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 for purpose followed by a brief requirement note. It is appropriately sized, front-loaded, and every word contributes to understanding the tool's function.

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

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

With no output schema and no annotations, the description should explain what the tool returns, error conditions, or edge cases. It does none of these. The description gives a good high-level purpose but leaves operational details uncovered, making it incomplete for an agent to fully predict behavior.

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 describes only the 'name' parameter (50% coverage). The description adds that the tool looks at domains the package points to, but it does not clarify the 'registry' parameter's role or how it affects the lookup. It does not compensate for the missing schema description of 'registry'.

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

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

The description clearly states the tool evaluates whether domains associated with a package (homepage, funding, documentation) still resolve to a registered owner. It distinguishes itself from sibling tools by focusing on domain registration status, though it lacks an explicit verb like 'checks' or 'returns'.

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 only mentions that a key is required, but does not specify use cases, prerequisites beyond the key, or situations where another sibling tool would be more appropriate.

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 the key requirement and the return content, but does not explicitly state whether it is read-only or how errors are handled. Some transparency is present, but 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?

Three short, focused sentences. Front-loaded with the main purpose, then use case and prerequisite. No unnecessary words.

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

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

For a simple one-parameter lookup tool, the description covers the key aspects: what it does, when to use it, and the auth requirement. It does not detail error behavior or output format, but those are not essential for a basic explain operation.

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 one 'id' parameter with no description. The description clarifies that this is a finding id, which fully compensates for the zero schema coverage. The agent knows exactly what to pass.

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 ('return') and resource ('finding') and clearly lists the output fields (what was measured, when, by whom, address). It easily distinguishes itself from sibling tools by its focus on explaining a single finding.

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 use case ('For an agent quoting a figure into a review') and a prerequisite ('Requires a key'). It does not mention explicit alternatives or exclusions, but the context is clear enough for an agent to decide when to use it.

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 that the catalogue is read daily across sixty providers and warns that prices can change without notice and training data becomes outdated, which is valuable behavioral context. It does not cover return format or error behavior, but for a read-only search, this is sufficient.

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

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

Two tight sentences; the first states purpose and data source, the second gives usage advice. No redundant or filler content.

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

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

The description covers purpose, key filters, data freshness, and usage timing. It lacks an explicit return-type description, but given the tool's simplicity and absence of an output schema, the essential context is provided.

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

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

The schema already describes maxPrice and minContext, but the provider parameter lacks a description. The tool description mentions 'price and context window' but does not clarify provider semantics or allowed values. With 67% schema coverage, the description adds some context but not enough to fully compensate.

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

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

The description clearly states the tool finds language models filtered by price and context window, and it emphasizes the catalogue's daily refresh and provider scope, distinguishing it from sibling tools like model_price_history. The verb 'Find' plus resource and criteria is specific and unambiguous.

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

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

The description gives explicit guidance: 'Use this before choosing a model' and explains the rationale (prices move without announcement, training data stale). It does not name alternative tools explicitly, so it lacks when-not guidance, earning a 4.

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

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

No annotations are provided, so the description must carry the burden. It does disclose the need for a key and points to a pricing URL, which is a useful prerequisite. However, it does not state whether the tool is read-only, what the output contains, or any other behavioral aspects beyond the auth requirement.

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 (two sentences) and wastes little space, but the first sentence is grammatically awkward (e.g., 'beside' likely means 'besides') and unclear. The auth note is useful but could be better integrated. Overall, it is concise but poorly structured for clarity.

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

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

Given that there is no output schema, no annotations, and only one undocumented parameter, the description needed to explain the tool's purpose, output, and parameter semantics thoroughly. It only provides a vague purpose and an auth note, leaving major gaps in understanding what the tool returns and how to interpret results.

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 one optional integer 'limit' with 0% description coverage, and the tool description does not mention this parameter at all. The agent has no insight into what 'limit' controls, such as maximum number of results, so the description 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 states 'Packages that ask for funding, beside how heavily they are installed and how many people write them,' which gives a vague sense that the tool relates to funding and package popularity metrics, but it lacks a clear verb like 'list' or 'find,' making the action ambiguous. It also does not differentiate this tool from the many sibling package-analysis 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?

There is no guidance on when to use this tool versus alternatives. The only additional note is 'Requires a key; see https://sighttrue.com/pricing,' which informs about authentication but not about usage context or when to prefer this over 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?

The description discloses that a key is required (authentication) and that the metric is time-based. It does not mention return format, pagination, or error behavior, leaving some behavioral uncertainty; however, for a simple read-only metric tool this is acceptable.

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 plus a URL, no filler. The description is front-loaded with the core functionality and then the key requirement.

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

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

No output schema exists, and the description does not specify the shape or interpretation of the result (e.g., a ratio, a series of data points). It also omits any error conditions or what happens with an invalid tag, so the description is not fully self-contained.

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 provides 'tag' as a string; the description clarifies it refers to a technology tag, which adds meaning. It does not provide example values, accepted formats, or context on how the tag should be specified (e.g., exact name, case sensitivity).

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

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

The description clearly states the tool computes a ratio of questions asked to questions answered for a technology tag over time. It distinguishes itself from sibling security/package tools by focusing on community help metrics, though it lacks an explicit verb like 'get' or 'calculate'.

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

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

It implies usage when you need Q&A availability metrics for a specific tech tag, and notes the requirement for an API key. No explicit alternatives or exclusion criteria are given, but the tool's unique focus makes the use case clear.

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

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

With no annotations, the description carries the burden of disclosing behavior. It reveals that the tool lists available readings and notes key requirements, implying a read-only scope. However, it does not mention return format, pagination, or whether the listing itself requires authentication, leaving some behavioral aspects unspecified.

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

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

Two sentences with no redundancy. The opening verb 'List' immediately conveys the action, and the second sentence adds practical usage guidance. Every word earns its place.

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

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

For a zero-parameter discovery tool with no output schema, the description includes the core elements: what it lists (all readings), what details it provides (measures and key requirements), and when to use it. This is complete for the tool's simple, meta 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?

The tool has zero parameters, so the baseline for this dimension is 4. The description appropriately omits parameter details, as the schema already confirms no parameters and coverage is 100%.

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 'List' and resource 'every reading this server can return', along with what each measures and key requirements. This clearly distinguishes it from sibling tools that focus on individual readings or analysis, establishing its role as a comprehensive index.

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

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

Explicitly instructs 'Call this first if unsure which tool answers a question', providing a clear when-to-use scenario. However, it does not list exclusions or name alternative tools, so it lacks the full 'when-not/alternatives' specificity for a top score.

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?

由于没有注释，描述承担了披露行为的全部责任。它提到了认证要求（密钥），但未说明该操作是否只读、是否具有副作用或返回数据的任何限制。缺少关于键如何传递或潜在速率限制的信息。

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?

描述由两句话组成，没有冗余词。第一句概括功能，第二句提供关键前提条件，非常高效。

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?

该工具简单（一个参数），但描述未说明返回数据的形式或密钥如何通过MCP提供。尽管目的明确，但缺乏足够的操作细节（如输出结构或错误场景）。

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?

模式对参数'model'没有任何描述，覆盖率0%。描述仅说'for a model'，这重复了参数名称，未解释模型是ID、名称还是其他标识符。描述没有增加任何有意义的语义。

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?

描述准确说明了工具返回的内容：模型的价格历史及读取日期。但缺少明确动词（如'获取'或'列出'），且未与兄弟工具如package_weight_history明确区分。

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?

描述仅指出需要密钥，并链接到定价页面，但未说明何时应使用此工具而不是其他工具（如list_readings或find_model）。没有提供使用上下文或替代方案的建议。

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 transparency burden. It does disclose that a key is required and that the output includes a 'date last seen', but it doesn't mention any other behavioral traits such as whether it returns a list, pagination, or if it's a read-only operation. This is adequate but not rich.

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, compact sentence that front-loads the purpose and follows with the key requirement and a link. No unnecessary wording or repetition.

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

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

Given the tool has no parameters and no output schema, the description provides the essential information: what it lists, the included date field, and the authentication requirement. It doesn't specify the exact return format, but this is a minor gap given the tool's simplicity.

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

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

The tool has zero parameters and an empty schema, so the baseline is 4. The description adds value by explaining that the data includes the 'date last seen', which is relevant context even though no parameters exist.

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

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

The description clearly states the tool reports 'Models that were in the catalogue and no longer are' with a last-seen date, making the purpose specific and concrete. It implicitly distinguishes from the similar sibling 'withdrawn_but_installed' by focusing on catalogue status rather than installation 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?

No guidance is provided on when to use this tool versus alternatives like 'withdrawn_but_installed' or 'find_model'. The only additional note is a key requirement, which is a prerequisite, not a usage scenario.

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

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

No annotations are provided, so the description carries the burden. It discloses that the tool returns raw readings, not a verdict, and that it requires an API key. However, it omits details about output structure (e.g., does it include timestamps? bytes?), limits, or pagination. This is partial transparency, enough to set expectations but not fully comprehensive.

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 sentences, front-loaded with the core purpose and followed by a key clarification ('not a verdict') and an auth requirement. Every sentence adds value—no fluff, no repetition of schema details. It is highly concise and well-structured.

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

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

With no annotations and no output schema, the description needs to cover more ground. It explains the basic operation and output nature, but lacks details on result format, any date range or filtering, and the exact meaning of 'registry'. It is adequate for a simple tool but leaves gaps that could cause incorrect usage, especially given the wealth of sibling tools (e.g., list_readings, model_price_history) that might overlap.

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

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

Schema description coverage is 50%—only 'name' is described ('Package name as the registry spells it.'), while 'registry' has no description. The tool description adds no parameter-specific detail, leaving 'registry' ambiguous (e.g., which registry? npm, PyPI?). The description mentions 'published artefact size' but does not clarify how the parameters map to that context, failing to compensate for the coverage gap.

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

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

The description clearly identifies the resource (published artefact size over time) and the action (returns readings/history). It distinguishes itself from sibling tools by explicitly stating 'Returns the readings taken, not a verdict', positioning it as a raw data tool versus assessment tools. However, it lacks an explicit verb like 'get' or 'list', relying on the noun phrase 'How...has moved'.

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 'not a verdict' implies use when raw historical data is needed rather than a conclusion, offering some guidance. It also notes 'Requires a key' as a prerequisite. But it does not explicitly name alternative tools (e.g., check_package, advisory_severity) or define clear when-to-use/when-not-to-use scenarios, leaving usage largely implied.

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

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

With no annotations, the description carries the full burden. It discloses meaningful behavior: grouping by component, scope over the whole archive, and the need for a key. However, it does not describe return structure, error behavior, or rate limits, leaving significant gaps in transparency.

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. The first delivers the core purpose and scope; the second adds a key requirement. Every word earns its place, and key information is front-loaded.

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

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

The tool is simple (one parameter) and the description covers purpose, scope, grouping, and key requirement. However, there is no output schema, and the description does not explain the return format (fields, structure, pagination). It is adequate for basic understanding but incomplete for full-invocation confidence.

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 implies 'provider' is the entity whose incidents are returned, but provides no format (slug, ID, name), required conventions, or examples. The description adds minimal semantic value beyond the parameter name itself.

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

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

The description clearly states the tool provides a provider's recorded incidents, grouped by the failed component, over the whole archive. It differentiates from a status-page window by explicitly noting the scope difference. Missing an explicit verb like 'list' or 'get', but the noun phrase is unambiguous.

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

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

The description gives clear context on when to use this tool: when you need incidents over the whole archive rather than the status-page window. It also mentions the key requirement. However, it does not name specific alternatives or explicit when-not-to-use conditions, so it stops short of a 5.

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

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

With no annotations provided, the description must carry the transparency burden. It does disclose that a key is required and that a stored fingerprint is used, but it omits any mention of output format, error behavior, or rate limits. The read-only nature is implied but not explicitly stated.

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

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

The description is brief and front-loaded, with the core purpose stated first and the auth pointer as a necessary second sentence. However, the first sentence is a grammatical fragment beginning with 'When' rather than a full declarative statement, which slightly hurts clarity.

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

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

Given the lack of annotations and output schema, this description is incomplete. It does not explain the provider parameter, provide usage context versus siblings, or describe what value the tool returns. While the tool is simple, the description leaves notable gaps that an agent would need to resolve.

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 one optional 'provider' string parameter with 0% description coverage, and the tool description never explains the parameter's format, allowed values, or how it maps to the stored fingerprint. The parameter name is self-explanatory to some degree, but the description adds no semantic value beyond the schema.

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

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

The description specifies the tool's purpose as reporting when a provider last changed its terms or pricing page, using a stored fingerprint. This clearly identifies the resource and distinguishes it from siblings like provider_incidents or model_price_history, though it lacks an explicit verb such as 'returns' or 'gets'.

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 provider_transparency or provider_incidents. The only context provided is the key requirement, which is an authentication prerequisite rather than usage 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?

The description discloses the authentication requirement ('Requires a key') and the metric definition, but it does not explain the return format, whether a single value or a list is returned, or how the optional 'provider' parameter affects behavior. Without annotations, this leaves a significant 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 a single, focused sentence that front-loads the core definition and adds the key requirement. There is no filler or repetition, making it highly efficient.

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 one optional parameter and no output schema, the description should provide enough context for correct invocation. It fails to explain the 'provider' parameter's role or expected input format, and the return value is unspecified. The simplicity of the tool is not an excuse for this level of incompleteness.

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

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

Schema description coverage is 0%, and the description only implicitly references 'provider' as the subject of the metric. It does not explicitly state that the 'provider' parameter filters by provider name, nor does it provide any format or example. This undercompensates for the schema's lack of detail.

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 defines what the tool measures: the time between an incident starting and its first public update. This is a specific, unambiguous purpose that distinguishes it from sibling tools like provider_incidents, though it lacks an explicit verb like 'returns' or 'gets'.

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 on when to use this tool versus alternatives such as provider_incidents or provider_terms_changed. The only usage condition mentioned is 'Requires a key,' which is a prerequisite, not a contextual recommendation.

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

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

The description discloses a key requirement and the data retention aspect ('kept after their status pages drop them'), adding useful context beyond the tool name. However, with no annotations, it fails to describe output format, error behavior, or explicitly confirm a read-only nature.

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 sentences, front-loaded with the core purpose and followed by the key requirement. Both sentences earn their place, with no redundancy or 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 tool with one undocumented parameter and no output schema, the description covers the core concept but omits parameter semantics, output format, and usage context. The pricing link is helpful 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?

The schema has one optional 'registry' parameter with zero description coverage, and the tool description does not explain what this parameter accepts or how it filters results. This leaves the agent without essential information for correct 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 states the tool provides recorded outages of package registries, distinguishing it from package-level tools through the phrase 'themselves.' However, it does not explicitly name sibling alternatives for comparison, so it misses 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 usage guidance is provided. The description does not mention when to use this tool versus alternatives like provider_incidents or check_provider, and the key requirement is a precondition rather than a usage guideline.

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 disclosing behavioral traits. It does mention that a key is required and that end dates 'including any already past' are included, which adds some context. However, it does not state whether the operation is read-only, what the return format is, or any side effects. For a tool likely performing a read operation, the lack of explicit safety guarantees is a significant 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 concise, consisting of two sentences that directly state the core purpose and a necessary requirement. There is no redundant fluff, and the sentences are front-loaded. However, the phrasing is slightly awkward and could be more structured, but overall it is appropriately short and efficient.

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?

This is a simple tool with one required parameter and no output schema, leaving the description as the sole source of context. The description does not explain what the response contains, how the tool behaves with various inputs, or what 'dependency set' means in practice. Given the lack of annotations and output schema, the description is insufficient for an agent to fully understand the tool's behavior.

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 parameter 'names' (array of strings), but the description does not mention this parameter at all. With 0% schema description coverage, the description offers no clarity on what 'names' refers to (e.g., dependency names, runtime names) or how to format them. The description does not compensate for the schema's lack of semantic meaning.

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

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

The description indicates the tool deals with end dates for runtimes required by a dependency set, which distinguishes it from sibling tools focused on other aspects. However, the verb 'Support' is vague; it does not clearly state whether the tool returns, lists, or checks these dates. The resource is identifiable, but the action is ambiguous.

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

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

The description mentions a prerequisite (requires a key) but provides no guidance on when to use this tool versus alternative sibling tools. There is no context about typical use cases, exclusions, or when another tool would be more appropriate. Only the authentication requirement is 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 provided, the description carries the full burden of behavioral disclosure. It states what the tool does, but omits details such as whether the search is case-sensitive, how the 'limit' parameter affects results, what happens when no matches are found, or whether it is read-only (though 'find' implies no mutation). The description does not contradict annotations (none exist), but it lacks richer behavioral context.

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

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

The description is two sentences, front-loaded with the primary action and purpose. Every sentence contributes value: the first defines what it does, the second gives usage guidance. There is no wasted text or repetition of schema details.

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 search tool with 2 parameters and no output schema, the description is mostly complete. It explains the purpose, the search criterion, and provides guidance on when to use it. It does not describe the return format or limit behavior, but these are not critical for a discovery tool. The absence of annotations is mitigated by the tool's inherently read-only nature implied by 'find'.

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 2 parameters (query, limit) with no descriptions in the schema itself (schema description coverage 0%). The description adds meaning to 'query' by explaining that it matches a string against repository names ('whose name contains a string'). However, the 'limit' parameter is not mentioned, so the description only partially compensates for the low schema coverage.

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

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

The description clearly states the tool's function: 'Find watched repositories whose name contains a string, with their current readings.' It specifies the verb (find), resource (watched repositories), and the output (current readings). It also distinguishes itself from siblings by positioning it as a discovery step: 'Use it to discover what is covered before calling the other tools.'

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

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

The description provides clear usage context: 'Use it to discover what is covered before calling the other tools.' This tells the agent when to use this tool (as a precursor to other tools). It does not explicitly mention alternatives or exclusions, but it gives a practical recommendation that is sufficient for a search 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?

The description adds some behavioral context beyond the schema by defining the exact time window (advisory published to postdating release) and the 'per package and distribution' output scope. However, it does not disclose potential edge cases (e.g., packages with no advisories, multiple releases) or output format, and with no annotations, the description carries the full transparency burden but only partially meets it.

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, focused sentence that conveys the core metric and the key requirement without extraneous information. The pricing link is useful and does not detract from the main message.

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 provides the essential context for the tool's function and authentication requirement, which is sufficient for a straightforward metric tool. However, the absence of any registry parameter clarification prevents it from being fully complete for invocation without additional assumptions.

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

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

Schema coverage is only 50% (name is described, registry is not). The description does not add any parameter-specific details, such as acceptable registry values or how the package name should be formatted, leaving a clear gap in understanding the registry parameter.

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 explicitly defines the tool's purpose: calculating the number of days between advisory publication and a subsequent release, offered per package and as a distribution. This clearly differentiates it from sibling tools like advisory_severity or check_* tools, which target other aspects of advisory/package data.

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, such as advisory_severity or explain_finding. The only practical note is the key requirement, but there is no explicit when/when-not guidance or reference to sibling tools for comparison.

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

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

The description discloses the need for a key and the fact that the tool only reports a state of existence without making a judgment. It also implies the use of installation popularity in the check. No annotations exist, so this information is valuable, though it does not detail the output format.

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

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

Two concise sentences; the first states the core purpose and the second adds behavioral and authentication context. No filler or repetition.

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

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

The tool is simple, but with no output schema, the description should clarify what the tool returns. It states that both names exist but not the response structure or accepted registry values, leaving gaps. Still, the core check and auth requirement are covered.

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 describes only the 'name' parameter; 'registry' has no description. The tool description does not mention the registry parameter at all, leaving it undefined. Thus the description adds little to parameter understanding beyond the schema's coverage.

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

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

The description clearly states the tool checks if a package name is one edit away from a more widely installed package, which is a specific and unique purpose. It also notes that both names exist and leaves ambiguity resolution to the caller, further clarifying its scope.

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 clear context for when to use this tool—checking for potential typosquats—and mentions a required key. However, it does not explicitly name alternative tools or state exclusions, so it stops short of full 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, the description carries the full burden. It discloses privacy ('list is private to the key that created it') and the auth requirement ('Requires a key'), but doesn't mention idempotency or behavior on duplicate additions. More behavioral detail would be helpful.

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

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

Three concise, front-loaded sentences. Each sentence adds value: purpose, privacy, and key requirement. No unnecessary words.

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

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

For a simple add-to-list tool, the description covers the main purpose, privacy, and key requirement. However, it doesn't clarify behavior on duplicate entries, return values, or how 'registry' influences the action. Still, it's reasonably complete for basic 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 coverage is 50%: 'name' has a description, 'registry' does not. The description doesn't elaborate on either parameter and doesn't explain how they are used together. It adds little beyond the schema, especially for the undocumented 'registry' parameter.

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

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

The description states a clear action: 'Add a package to the caller’s own private watchlist.' It specifies the resource (private watchlist) and distinguishes itself from siblings like watch_changes by emphasizing the private, caller-specific nature.

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 context on when to use ('so later readings are about their stack rather than the public one') and a prerequisite ('Requires a key'). It doesn't explicitly mention alternatives or exclusions, but the usage context is clear.

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

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

With no annotations, the description carries the full burden. It discloses the authentication requirement (key) and the scope (private watchlist), and lists the types of changes included. However, it does not state whether the operation is read-only, describe output format or pagination, or mention rate limits or other behavioral traits. The read-only nature is implied but not explicit.

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 efficiently covers the tool's function, the types of changes, and the required key. It is not overly verbose, though the list of change types adds length. The inclusion of a pricing link is useful but slightly extraneous. Overall, it is well-structured and front-loaded with the core purpose.

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 simplicity (one optional parameter, no output schema) and no annotations, the description provides a good overview of what constitutes a 'change' and mentions the key requirement. However, it lacks details on the response structure, potential errors, and edge cases (e.g., what happens if no changes exist). It is sufficient for basic selection but not fully complete for 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 0% description coverage, so the description must clarify the 'since' parameter. It does say 'since a given date', giving meaning to the parameter. However, it does not specify the date format, whether it is required (schema says optional), or the behavior when omitted. This is minimal compensation for the lack of schema documentation.

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

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

The description clearly states the tool's purpose: it lists all changes on the caller's private watchlist since a given date, enumerating specific change types (withdrawals, licence changes, advisories, archived repositories, runtimes going out of support). This distinguishes it from sibling tools like watch_add (which adds items) and diff_since (which compares repositories).

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 implicitly conveys when to use the tool: when you need a summary of changes across a watchlist since a date. It also notes the key requirement, which is a prerequisite. However, it does not explicitly mention alternatives or when not to use it, so it falls short of a 5.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that the tool reflects registry-listed rights, implying a read-only operation, and notes the authentication key requirement. However, it does not specify output format (count vs. list), potential errors, or rate limits, leaving some behavioral gaps.

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 three sentences, front-loading the core function in the first sentence. The second sentence adds valuable context, and the third provides an actionable requirement. Every sentence earns its place, with no redundancy or fluff.

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

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

For a simple two-parameter tool with no output schema, the description is reasonably complete. It conveys the tool's purpose, scope, and a key dependency. The main gap is the ambiguous output type (count vs. list) and lack of detail on how the registry parameter is used, but the description is adequate 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 50% coverage: the 'name' parameter has a description, but 'registry' does not. The tool description adds minimal parameter meaning, only implicitly referring to a 'package' and 'registry' without clarifying the 'registry' parameter's valid values or format. It does not sufficiently compensate for the missing schema description.

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

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

The description clearly states the tool's function: it counts accounts with publish rights on a package. It further distinguishes from related concepts by noting it answers 'who can put code on your machine' rather than 'who writes it,' which differentiates it from author-related queries. This makes the purpose specific and distinct from 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?

The description provides clear context for when to use the tool: to determine publish rights as opposed to authorship. It also mentions the prerequisite of requiring a key, which is a usage condition. However, it does not explicitly name alternative tools or state when not to use it, so it falls short of a 5.

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

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

The description discloses the need for an API key and mentions the output includes download figures and the publisher's notice, which adds some context. However, with no annotations, it does not state whether the operation is read-only, how results are ordered, what 'heavily installed' means, or any rate limits or error 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 compact: two sentences conveying the core purpose and the key requirement. It is front-loaded with the main concept, though a verb would make the first sentence more actionable; still, it wastes no words.

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

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

For a simple query tool with one optional parameter, the description gives enough to understand the basic output (download figure and publisher's notice) and the auth prerequisite. However, it omits explanation of the 'limit' parameter, the threshold for 'heavily installed,' and result ordering, leaving notable 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 includes an optional 'limit' parameter with no schema description, and the tool description does not mention or explain it. Since schema_description_coverage is 0%, the description provides no semantic support for the one parameter, leaving the agent to guess at its meaning and typical 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 clearly identifies the subject matter—packages withdrawn by their publisher but still heavily installed—and implies a query operation, but it lacks an explicit verb like 'list' or 'get.' The unique scope distinguishes it from sibling tools, but the missing action makes it less direct than ideal.

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

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

No explicit guidance is given for when to use this tool versus alternatives such as 'model_withdrawn' or 'check_package.' The context signals imply it is for a specific kind of package audit, but there is no direct comparison or prerequisite statement beyond the key requirement.

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