allmcps-server

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 does mention the output (checkout URL and invoice), which is useful, but it does not disclose side effects such as whether the order is immediately charged, whether it modifies the server's listing, or any prerequisite state. This is a minor gap, making it adequate but not 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 a single, well-structured sentence that front-loads the action and resource, then specifies the return values. It contains zero redundant words and is easy to scan.

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 output schema and only three parameters (fully documented in the schema), the description provides enough to understand the core behavior and return type. However, it lacks details about the ordering flow and potential failure modes, which would be useful for a transaction-like operation. Still, for a simple initiate-order tool, it is largely complete.

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

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

Schema description coverage is 100% (all three parameters have descriptions). The description adds no additional meaning beyond restating 'by ID', which is already in the schema. Per the guidelines, with full schema coverage, a baseline of 3 is warranted.

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 'Initiate' and clearly states the resource ('sponsorship / boost order for an MCP server by ID') and the return value ('Stripe checkout session URL and x402 invoice'). This distinguishes it from sibling tools like get_boost_pricing and get_boost_status, which are query-only.

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 clearly implies when to use the tool: to start a boost order for a given server ID. However, it does not explicitly mention alternatives or exclusions (e.g., 'for pricing, see get_boost_pricing'). Since the context is unambiguous, a 4 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 provided, the description carries the full burden of behavioral disclosure. It only states the tool 'gets' pricing/features and does not disclose whether it is a safe read-only operation, requires authentication, or has any side effects. It also does not hint at the response format or potential caching/rate limits, leaving the agent without critical safety 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 a single, well-structured sentence that front-loads the action ('Get') and subject ('pricing and features'), with no redundant words or unnecessary detail. It is concise and immediately understandable.

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 no-parameter tool, the description provides the core purpose but lacks details about the return value or any caveats. Since there is no output schema or annotations, the agent does not know whether the response is a list of plans, a single object, or which specific fields are included. This leaves some ambiguity but is acceptable for a lightweight getter.

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 description does not need to add parameter semantics. The input schema already encodes an empty object, and the description reinforces the tool's purpose without needing to explain any arguments. The baseline for zero parameters is 4.

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

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

The description clearly states that the tool retrieves pricing and features for boosting/featuring an MCP server, using a specific verb ('Get') and resource ('pricing and features'). It is distinguishable from sibling tools like boost_mcp_server (which performs the action) and get_boost_status (which likely returns 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?

The description implies the tool is used to fetch pricing information, but it does not explicitly state when to use it versus alternatives, nor does it mention any prerequisites or exclusions. There is no guidance on when not to use it, but the purpose is clear enough.

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

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

No annotations are provided, so the description carries the full burden. It indicates a read-only operation via 'check,' but it does not explicitly state there are no side effects or disclose the response format or behavior for invalid IDs. The behavior is adequately implied but not thoroughly detailed.

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

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

The description is a single, concise sentence that front-loads the main action ('Check') and includes all relevant details (what is checked, for which server). It is efficient with no wasted words.

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

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

For a simple status check tool with one parameter and no output schema, the description is complete. It specifies the input (server ID) and explicitly lists the output components (boost status, verified badge level, sponsorship expiration), leaving no major 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 already covers the single parameter 'id' with a clear description, and the tool description repeats the 'by ID' context. No additional meaning is added beyond the schema, so a baseline score of 3 is appropriate.

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 boost status, verified badge level, and sponsorship expiration for a specific MCP server by ID. This uses a specific verb ('check') and resource, and is distinct from sibling tools like boost_mcp_server (action) and get_boost_pricing (pricing).

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 to check current boost status, verified badge level, and sponsorship expiration. However, it does not explicitly mention when to use it versus alternatives, such as when checking before boosting or comparing with get_boost_pricing.

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 explicitly states it 'gets' (read operation) and describes the exact content returned. However, it does not disclose potential error conditions, permissions, or rate limits. For a simple read operation, the description is honest but not exhaustive.

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

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

The description is a single concise sentence that directly states the tool's action and output, with no filler or unnecessary words. It is front-loaded and easy to parse.

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, no output schema), and the description adequately explains that it returns a config snippet and documentation. It could add details about return format or error behavior, but this is not essential given the low complexity. The description is complete enough for typical use.

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 the 'id' parameter well-described by its own schema entry. The description's 'by ID' adds no new meaning beyond the schema, so it correctly falls at the baseline of 3.

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: retrieving the exact claude_desktop_config.json setup snippet and documentation for a given MCP server ID. It uses a specific verb ('get') and resource ('setup snippet and documentation'), and distinguishes itself from sibling tools like search_mcp_servers or get_boost_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?

The usage context is implied: when the agent needs the installation configuration for a specific MCP server with a known ID. It does not explicitly mention alternatives or exclusions, so it falls short of a 4 or 5, but the purpose itself implies 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 burden of behavioral disclosure. It implies a read-only list operation and states the output includes server counts, but it does not explicitly confirm safety, mention rate limits, or describe the response structure in detail. This is acceptable for a simple listing tool but not fully transparent.

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

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

The description is a single, focused sentence that front-loads the key information: what is listed (categories) and what is included (server counts). There is no fluff or repetition.

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

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

For a tool with no parameters and no output schema, the description covers the essential facts: it lists categories with server counts. It could be even more complete by stating the return format or pagination behavior, but those are not critical for such a simple tool.

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

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

The tool has zero parameters, so the description needs to explain nothing about them. The baseline score for 0-parameter tools is 4, and the description appropriately does not waste space on parameters. It focuses on the output content instead.

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 with a specific verb ('List') and resource ('categories'), and adds useful context ('AllMCPs directory', 'server counts'). It distinguishes itself from siblings like search_mcp_servers by focusing on categories rather than servers themselves.

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

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

The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no caveats. It simply describes what it does without contextualizing its use.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not mention read-only vs. write behavior, whether it involves external calls, or execution time expectations. It only states the high-level outcome without any side effects or prerequisites.

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 clearly states the purpose and provides examples. It is front-loaded with the core action and avoids fluff, making it easy to scan quickly.

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 recommendation tool with one parameter and no output schema, the description provides a basic level of completeness. However, it lacks details on the structure of the recommended stack (e.g., what servers are included, how many, or how recommendations are generated). Given the context signals, it is minimally adequate but could be enriched.

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% with only one parameter 'role' and a description of example values. The description reinforces that the role should be a developer role or workflow and provides examples, adding value beyond the schema. However, it doesn't elaborate on allowed values or expected format beyond examples.

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

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

The description clearly states the tool's purpose with a specific verb 'Recommend' and resource 'curated multi-tool MCP server stack'. It specifies the target input (developer role or workflow) and provides examples. It distinguishes from siblings like search_mcp_servers by focusing on curated recommendations rather than search results.

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 context ('for a specific developer role or workflow') but does not explicitly state when to use this over alternatives like search_mcp_servers or list_mcp_categories. It lacks exclusions or guidance on when not to use it. The role examples provide some clarity on applicable inputs.

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

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

No annotations are provided, so the description carries the full burden. It only restates the search functionality without disclosing whether the operation is read-only, what the result format looks like, or any side effects. This is a significant gap for a search tool that presumably returns data.

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

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

The description is a single sentence with no filler words. It is front-loaded with the action and resource, making it easy to parse.

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 optional params and no output schema, the description provides the minimum viable context. However, it lacks details about result format, default behavior, or how it differentiates from list_mcp_categories. The absence of annotations increases the need for such context, making this adequate but not 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 descriptions cover 100% of parameters, so the baseline is 3. The description adds no new meaning beyond echoing 'keyword or category', which is already in the schema. The limit parameter is not mentioned in the description, so no additional value is provided.

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: 'Search the AllMCPs directory for Model Context Protocol (MCP) servers by keyword or category.' This uses a specific verb ('Search') and resource ('AllMCPs directory for MCP servers'), and distinguishes from siblings like list_mcp_categories by focusing on keyword/category search.

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

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

The description provides clear context for when to use the tool (searching by keyword or category), but it does not explicitly mention alternatives or exclusions. Sibling tools like list_mcp_categories are not referenced, so the guidance is clear but incomplete.

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 discloses that submissions are sent for 'indexing and review,' that enrichment fields are optional, and importantly that 'unrecognized enum values are simply dropped, not rejected.' It does not mention duplicate handling, verification flow, or side effects, but the provided details are meaningful and non-obvious.

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 with no filler. The first sentence states purpose, the second explains enrichment strategy with concrete source examples, and the third provides the safety policy for uncertain values. 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 a 16-parameter tool with no output schema and no annotations, the description provides a strong conceptual model of the submission action and the tolerance for incomplete or unrecognized data. It does not describe the post-submission response, but the combination of schema descriptions and the confidence-policy guidance makes the tool adequately usable.

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

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

Schema coverage is 100%, so baseline is 3. The description adds value beyond schema by explaining that all enrichment fields are optional and that unrecognized enum values are dropped rather than causing errors. This directly affects how the agent should populate enum parameters like category and authType.

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

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

The description opens with a specific verb and resource: 'Programmatically submit a new MCP server repository to AllMCPs.com for indexing and review.' This clearly distinguishes it from sibling tools like search_mcp_servers or verify_mcp_claim, which involve searching or verification rather than submission.

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 for how to use the tool: fill in enrichment fields only when confidently determined from the repository, and omit uncertain values. It does not explicitly contrast with sibling tools or state when not to use it, but the enrichment guidance is actionable and practical.

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

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It mentions the verification methods, but it does not disclose whether claiming is irreversible, requires authentication, or has any side effects on the listing. The 'claim' action likely mutates state, but the description leaves this ambiguous.

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

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

The description is a single concise sentence, front-loaded with the primary action, and contains no fluff or redundancy. Every word contributes to the tool's 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?

The tool has no output schema, and the description does not explain what the result looks like (e.g., success/failure, proof of ownership). Given the moderate complexity and the absence of behavioral details, the description is minimally adequate but lacks important context about outcomes and side effects.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds meaningful context by mapping the enums (github, website_badge, dns) to the actual verification steps (checking GitHub README badge, website badge, DNS TXT record), which the schema's short descriptions do not provide. This enriches the parameter understanding beyond basic types.

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 action ('Verify ownership and claim') and resource ('MCP server listing'), and specifies the verification methods (GitHub README badge, website badge, DNS TXT record). This distinguishes it from sibling tools like search, submit, or boost, which have different actions.

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 to verify and claim a listing after it has been submitted, but it does not explicitly state when to use it versus alternatives, nor does it mention any prerequisites or exclusion cases. The context is clear but not fully developed.

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