CryptoDecentral Sovereign MCP

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

With no annotations, the description carries the full transparency burden. It discloses that the tool returns canonical URLs, that the content is educational only, and that it is not financial advice or a recommendation mechanism. It does not mention authentication, errors, or output format, but for a zero-parameter read-only getter these gaps are minor.

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 front-loads the primary action ('Return ... URLs') and then adds necessary legal context. The series of short legal phrases is compact and relevant to the disclaimer nature of the tool, though slightly repetitive.

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 zero-parameter getter with no output schema, the description is largely complete: it states what is returned and clarifies the legal and educational context. It could specify the exact return shape, but the low complexity makes that a minor omission.

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

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

The tool has zero parameters, so there are no parameter semantics to document. The empty schema already provides complete coverage, and the description appropriately focuses on output and context rather than inputs.

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

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

The description names a specific verb ('Return') and a clear resource: CryptoDecentral's canonical educational and legal URLs, so an agent can tell this is the disclaimer-related tool. It is distinct from siblings like get_listing or search_content because it is the only tool focused on disclaimers and legal URLs. The phrase 'educational fence' is slightly opaque, but the overall purpose is still clear.

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

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

Usage context is implied rather than explicitly stated: an agent can infer this tool should be called whenever disclaimer or legal URLs are needed. However, the description does not explicitly say when not to use it or name alternatives, and the legal boilerplate is more about content than selection criteria.

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

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It does not describe return format, potential errors, authorization needs, or whether the listing contains nested or referenced content. The added disclaimers about educational use and financial advice are not behavioral details.

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 core functional sentence is concise and front-loaded. However, the remaining sentences are boilerplate disclaimers that do not help an agent select or invoke the tool, adding unnecessary length without operational value.

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

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

With no output schema, the description should explain what the returning listing looks like or what an agent can expect. It simply says 'directory listing,' leaving the return structure and any constraints undocumented. The educational disclaimers do not fill this 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 coverage is 100%, and the schema already documents the id parameter with an example. The description only adds 'by id', which adds little beyond what the schema already says. Baseline 3 is appropriate for high 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 phrase 'Get a single directory listing by id' states a clear verb, resource, and the fact that it targets one listing by ID. It is distinguishable from siblings like list_directory and search_directory by the 'single' and 'by id' qualifiers, though it does not explicitly name them.

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

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

No guidance is given on when to choose this tool over list_directory or search_directory. The description implies it is for retrieving one specific listing by ID, but it does not state alternatives or exclusion conditions.

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

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

With no annotations, the description carries the behavioral disclosure burden. It communicates that this is an informational, read-style retrieval and includes educational/legal disclaimers ('Educational only', 'Not financial advice', 'Not an FSP/CASP', 'DYOR'). It does not describe output format, size, or whether the tool has other side effects, but for a simple retrieval the core behavior is reasonably clear.

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 first sentence is tight, front-loaded, and immediately states what the tool returns. The remaining disclaimers are boilerplate and add little operational value, but they are short and do not obscure 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?

For a single-parameter retrieval tool, the description gives enough to call it correctly with either variant. However, it omits the default behavior when 'variant' is not supplied, does not describe the return structure, and does not explain when this tool should be preferred over sibling tools like get_site_posture or list_directory.

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

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

The input schema only provides a bare enum for 'variant' with no parameter descriptions. The description adds real meaning by mapping 'short' to llms.txt and 'full' to llms-full.txt. It does not state the default when the optional parameter is omitted, but the enum values are now semantically clear.

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 a specific resource ('the site's llms.txt map' or 'llms-full.txt'), with clear variant labels short/full. It does not explicitly contrast against sibling tools, but the named resource is distinctive enough that an agent can tell what this tool does.

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

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

The description implies the tool is used when the agent needs the site's llms.txt map and implies a choice between short and full variants. However, it gives no explicit when-to-use guidance, no mention of alternatives among the sibling content tools, and no exclusion criteria.

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

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

With no annotations, the description carries the transparency burden. It conveys that the tool is public, snapshot-like, and educational-only, which implies a read-only, low-risk operation. However, it does not state return format, side effects, or any operational boundaries beyond the disclaimers.

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 core content is front-loaded and clear, but the disclaimer stack is repetitive: 'Educational only', 'Not financial advice', 'Not an FSP/CASP', 'DYOR', and 'not recommendations' all reinforce the same point. It could be tightened without losing meaning.

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 public snapshot with no output schema, the description is largely complete: it says what data is provided, what is excluded, and how the output should be interpreted. Only an explicit return format or schema reference is missing, but its absence is minor here.

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

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

There are zero parameters and the schema coverage is effectively 100%. The description adds value by specifying exactly what metrics are included, which exceeds the baseline expected for a parameterless tool.

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

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

The description names a specific deliverable, 'public network metrics snapshot', and enumerates concrete contents: mempool fees in sat/vB, difficulty, Tor, and a Nostr sample. It also explicitly excludes asset prices and trading signals, which differentiates it from listing or price-oriented 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?

It clearly positions the tool as appropriate for educational network-metrics use and explicitly states it is not for asset prices, trading signals, or financial recommendations. It does not name a specific alternative sibling for those needs, 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?

With no annotations, the description carries the burden of behavioral disclosure. It adds useful context that the content is educational only and not financial advice, but it does not state read-only behavior, return format, or error behavior. For a simple getter this is acceptable but not richly transparent.

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

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

The functional core is front-loaded and concise, but five of six sentences are legal/disclaimer boilerplate. While possibly required, those sentences add little operational value for an agent trying to select or invoke the tool.

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

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

For a single-parameter getter with no output schema, the description gives enough to invoke it correctly: use a pillar slug. It also adds important context about educational use. It could mention how to discover valid slugs or point to list_pillars, but that is not essential 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?

Schema description coverage is 100%, and the single 'id' parameter is already well described as a 'Pillar slug' with examples. The description redundantly says 'slug' but adds no new semantic information 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 begins with a clear verb and resource: 'Get one pillar by id (slug).' This states exactly what the tool does and distinguishes it from sibling list_pillars by emphasizing retrieval of a single item.

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 tool clearly communicates its use case: fetch a single pillar when you have its slug. It does not explicitly name alternatives or provide when-not-to-use guidance, but the context is clear enough for an agent to select it appropriately.

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 and does a good job clarifying the tool's educational, non-advisory nature and what it does not do. It does not mention operational details, but for a zero-parameter informational 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?

The description is concise and front-loaded with the core purpose. Some redundancy exists between 'no custody, swaps, advice' and the later 'not buy, sell, custody, or swap recommendations', but it does not become bloated.

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 zero-parameter tool with no output schema, the description adequately explains what the tool returns and its limitations. It could be more complete by addressing how it relates to get_disclaimer, but it is sufficient for basic invocation.

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

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

The input schema has no parameters, so the semantic burden is minimal. Baseline of 4 is appropriate since no parameter documentation is needed.

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

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

The description clearly states the tool returns 'site posture' and defines what CryptoDecentral is and is not. It is specific enough to convey the resource and scope, though it does not explicitly differentiate itself from the sibling get_disclaimer.

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 direct guidance on when to use this tool versus alternatives like get_disclaimer. The disclaimers describe content rather than usage context, so an agent is left to infer when this tool is 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 of behavioral disclosure. It adds context by calling listings 'curated' and adding educational/non-recommendation disclaimers, but it does not mention result ordering, pagination, or that this is a read-only operation beyond the verb 'List'.

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

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

The core purpose and filters are front-loaded in the first sentence, but the later legal/educational disclaimers take up multiple sentences and provide limited operational guidance. It is not bloated, but not 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?

For a simple optional-filter listing tool, the description provides a basic invocation path. However, with no output schema and no description of the returned result structure or how filters combine, an agent is left with meaningful unknowns.

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

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

Schema description coverage is 0%, so the description must compensate. It only repeats the parameter names and labels them as optional filters; it does not explain what values q, category, and tag accept or what they filter on.

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

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

States a specific action ('List') and resource ('curated directory listings'), so the core purpose is clear. It is distinct from search_directory by implication, but it does not explicitly name or differentiate itself 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 indicates filters are optional and names them, which gives some usage context. However, it does not state when to use this tool versus search_directory or other listing/search siblings.

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

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

With no annotations provided, the description is the only source of behavioral context. It discloses the output fields and the educational nature of the content, but it does not state whether the operation is read-only, whether any pagination or limits exist, or whether authentication is needed. For a simple zero-parameter list, 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 first sentence is front-loaded and useful, but the description carries several overlapping legal disclaimers ('Not financial advice', 'Not an FSP/CASP', 'DYOR', 'not buy, sell, custody, or swap recommendations'). These are relevant for compliance but add redundancy and length beyond the core functional 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?

For a zero-parameter tool with no output schema, the description covers the essential calling context: what the tool lists and what fields will appear in the results. It is not missing critical invocation details, though it could optionally mention ordering or pagination.

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 properties and schema coverage is 100%, so there are no parameters for the description to explain. Per the rubric, zero parameters baseline is 4, and the description appropriately avoids inventing parameter semantics that do not 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 uses a specific verb ('List') and a distinct resource ('educational guides'), and even enumerates the returned fields (slug, title, description, url). This clearly differentiates it from sibling list tools such as list_directory, list_notes, and list_pillars.

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

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

The description provides no explicit guidance on when to use this tool versus alternatives, and it names no sibling tools or exclusion criteria. The resource name and verb imply its use, but that is left to inference rather than stated.

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

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

With no annotations, the description carries the full behavioral disclosure burden. It partially fulfills this by specifying the returned fields and implying a read-only list operation. However, it does not disclose pagination, ordering, completeness, authentication requirements, or other potential behavioral traits.

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 main sentence is concise and front-loaded, but the description then spends four sentences on repeated disclaimers ('Not financial advice', 'Not an FSP/CASP', 'DYOR', 'not recommendations') that add little for tool selection. These sentences could be condensed without losing meaning.

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 list tool, the output fields and educational scope are specified, which is helpful. However, there is no indication of when to choose notes over sibling list tools, nor any mention of list limits, ordering, or whether all notes are returned, so completeness is only partial.

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

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

There are zero parameters, so the description cannot add parameter meaning beyond an empty schema. The baseline of 4 for no-parameter tools applies, and the description does not introduce any conflicting or misleading parameter implications.

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 ('educational notes') and enumerates the output fields: slug, title, description, tags, url. It is clear, though it does not explicitly distinguish itself from sibling list tools such as list_guides or list_pillars beyond the resource name.

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 like list_directory, list_guides, or search_content. The disclaimers about financial advice and DYOR are compliance-related, not usage guidance, so an agent receives no selection criteria.

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

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

No annotations are provided, so the description carries the behavioral disclosure burden. It adds useful context: the content is educational, not financial advice, and not a recommendation. However, it does not disclose operational details such as data source, static vs live content, or update behavior, though these are less critical for a simple read-only listing.

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 core function is stated first and is clear, with examples. The second half consists of legal-style disclaimers that are somewhat repetitive, but the overall description remains short and readable, so the extra context does not significantly hurt usability.

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 zero parameters and simple list semantics, the description is essentially complete: it names the resource, gives examples, and indicates the output includes summaries. There is no output schema, but 'with summaries' provides enough shape for an agent to understand the expected result.

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

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

The tool has zero parameters, so the schema fully specifies invocation requirements, and the baseline for 0 parameters is 4. The description adds no parameter semantics, but none are needed.

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

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

The description uses a specific verb ('List') and a concrete resource ('educational pillars'), with examples such as privacy, wallets, deai, and nostr, plus the expected output ('with summaries'). This clearly distinguishes it from siblings like get_pillar, which likely retrieves a single pillar.

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 purpose implies the tool is for obtaining an overview of educational pillars, but the description does not explicitly say when to use it over alternatives like get_pillar or list_directory. The disclaimers provide context about how the content should be treated, but they do not guide tool selection.

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

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

No annotations are present, so the description is the only source of behavioral context. It adds educational/disclaimer context and clearly frames the operation as search, implying read-only behavior, but it does not describe result format, pagination, or matching semantics.

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 core behavior and type options are front-loaded in two short sentences, with legal disclaimers appended. It is concise, though the disclaimer block is not directly action-oriented.

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

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

For a simple two-parameter search tool, the description gives the essential purpose and the optional type filter. It lacks details on return values, search matching behavior, and relationship to the sibling search/list tools, and no output schema exists to fill this 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 partly compensates by explaining 'type' with its enum values and indicating title/summary as the search target. However, 'q' is never explicitly named or detailed, leaving required-parameter semantics vague.

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?

Clearly states it searches notes, guides, and/or pillars by title/summary, giving a specific verb, resource set, and search field. It does not explicitly contrast with siblings like search_directory or list_notes, so it misses the full 5.

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

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

The description implies its use by naming the query-driven search and the optional type filter, and it explains the type enum. It does not state when to prefer it over sibling list_* or search_directory tools, nor any exclusions.

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

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

With no annotations provided, the description carries the burden of behavioral disclosure. It adds useful context by describing results as 'unranked educational match' and by warning that listings and tools are not recommendations. However, it does not mention operational traits like auth requirements, rate limits, or output behavior, though a search is implicitly non-destructive.

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 core purpose is front-loaded and the description is not overly long. However, the legal disclaimers are repeated and could be condensed; several clauses make the same 'not advice/recommendation' point. It is serviceable but not tightly 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?

For a simple search tool with no output schema, the description establishes the purpose, scope, result nature, and domain constraints. It does not specify return format, pagination, empty-result behavior, or parameter interactions, but these are partly inferable from the name and schema. Adequate with clear gaps.

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

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

The description maps the parameters by saying 'query/category/tag', which clarifies that 'q' is a free-text query while 'category' and 'tag' echo their own names. With 0% schema description coverage, this is helpful but shallow: it does not explain how the parameters combine, whether they are filters or mutually exclusive, or what values are valid.

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

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

States a specific verb, 'Search', a resource, 'directory listings', and the search dimensions 'query/category/tag'. This makes the main purpose clear, but it does not explicitly contrast with siblings like list_directory or search_content, so differentiation is left mostly to the resource name.

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

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

No guidance is given for when to use this tool versus alternatives such as list_directory or search_content. The disclaimers ('Educational only', 'Not financial advice', etc.) impose domain constraints but do not help with tool selection or invocation context.

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