MCPExplorer

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns multiple components (score, label, reasons, history), implying it is a read operation. However, it does not state required permissions, potential delays, or other behavioral traits beyond the return type.

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 communicates the tool's purpose and output. No extraneous information is included.

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 required parameter and no output schema, the description is largely complete. It specifies all elements of the return value. A minor gap is that it does not mention the input requirement (slug) explicitly, but that is covered in the input schema.

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% (the only parameter 'slug' is described as 'Server slug'). The description does not add further meaning to the parameter, such as format, examples, or how it is used. The baseline score of 3 is appropriate since the schema already defines the parameter 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 clearly states the tool returns trust score, label, scoring reasons, and verification history for an MCP server. It uses a specific verb ('Return') and identifies the resource ('MCP server'), distinguishing it from sibling tools like 'get_server' (which likely returns server info) and 'compare_servers' (comparison).

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. It does not mention prerequisites, context for interpretation, or any exclusion criteria. The agent must infer its applicability from the name alone.

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 provided, so description bears full burden. It does not state the tool is read-only, nor any side effects. 'Compare' implies read-only 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?

Single sentence that is front-loaded and contains only essential information with no redundancy.

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

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

Adequate for a comparison tool with two simple parameters. Lists comparison aspects. Could mention return format but not required with no output schema.

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 descriptions for both parameters are present and sufficient ('First server slug', 'Second server slug'). Description adds no extra detail, so baseline 3 applies.

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

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

Description clearly states it compares two MCP servers and lists the comparison dimensions (trust, transport, tools, install, links). Distinct from sibling tools like 'get_server' (single server) and 'search_servers'.

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 when-to-use or when-not-to-use guidance. Implicitly for side-by-side comparison. Does not distinguish from sibling 'get_alternatives'.

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

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

No annotations are provided, and the description does not disclose any behavioral traits (e.g., whether the generation is destructive, requires authentication, or produces a file vs. returning data). It lacks context beyond the basic action.

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 purpose. However, it could be slightly restructured to pair purpose with parameter details more explicitly; still, 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 two-parameter tool, the description covers the generation goal and runtime examples but omits the output format (e.g., JSON, YAML) and whether the config is printed or saved. Without an output schema, these details are important for agent 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?

Schema coverage is 100% with basic descriptions ('Server slug', 'Runtime slug'), but the description adds significant value by enumerating 9 specific runtime examples, helping agents understand valid values 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 clearly states the verb 'Generate' and resource 'install + client config for an MCP server in a given runtime', listing specific runtimes, which distinguishes it from siblings like list_runtimes or get_server that do different operations.

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 is clear but no explicit guidance on when to use versus alternatives. The sibling tools include related functions like get_server and list_runtimes, but no comparison or exclusivity is mentioned.

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 disclose behavioral traits. It mentions 'verified' and 'ranked by trust' but fails to explain verification criteria, trust ranking methodology, or any potential side effects. The read-only nature is 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?

A single concise sentence that is front-loaded and contains no wasted words. It efficiently communicates the tool's core 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?

For a simple 1-parameter tool with no output schema and no annotations, the description covers the basic purpose but lacks details on output format, ranking criteria, and the meaning of 'verified'. It is adequate but leaves gaps.

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

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

Schema coverage is 100% with parameter 'slug' described as 'Server slug'. The description adds context by framing the parameter as identifying a 'given server' for which alternatives are sought, but beyond that it does not add significant semantic 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?

Description clearly states the tool finds verified MCP servers with the same capabilities as a given server, ranked by trust. It uses specific verbs ('find', 'verified', 'ranked') and resource ('MCP servers'), distinguishing it from siblings like 'get_server' or 'compare_servers'.

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 seeking alternative servers with similar capabilities, but provides no explicit when-to-use, when-not-to-use, or alternatives. Sibling tool names offer context but the description itself lacks guidance.

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

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

No annotations are provided, so the description carries full burden. It mentions 'ranked by trust' but does not explain the ranking criteria or any other behavioral details (e.g., data freshness, pagination). 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?

A single sentence that conveys the core purpose and key differentiator (ranking by trust) with no extraneous information. 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?

For a simple read tool with one parameter and no output schema, the description covers the what and the ranking aspect. It does not describe the return format, but the context is sufficient for understanding.

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% for the only parameter 'slug'. The description adds no extra meaning beyond the schema's explanation ('Capability slug, e.g. 'send-email''). Baseline score applies.

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 clearly identifies the resource as 'best MCP servers that provide a capability', with examples like 'send-email'. It distinguishes from siblings such as get_server and search_servers by focusing on ranking by trust.

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 states the tool's purpose: to list servers by capability. It implies when to use it (when you need servers for a specific capability), but lacks explicit exclusions or mentions of alternatives among the sibling tools.

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

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

With no annotations provided, the description carries full burden. It describes the tool as a read-only snapshot, implying no side effects. While it doesn't mention rate limits or performance, 'live snapshot' sufficiently conveys non-destructive behavior and immediate data retrieval. Adequate for a stat query.

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 a colon and list, covering all key output categories without redundancy. It is reasonably concise, though slightly run-on. Every part contributes 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?

Given no output schema, the description enumerates the major return categories (totals, breakdowns, top lists). This is fairly complete for a stats endpoint. It could mention ordering or freshness, but for a zero-parameter snapshot it is adequate.

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 schema description coverage is 100%. The description does not need to add parameter details. Baseline for 0 parameters is 4, and the description adds no extra param info, which is acceptable.

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 'live snapshot of the indexed MCP ecosystem' with specific data categories (totals, provenance, transport, top-trust lists). The verb 'Get' and resource 'ecosystem stats' are unambiguous. It distinguishes from siblings which focus on individual servers or configurations.

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 'Live snapshot...' indicates it's for current state data, and the listed breakdowns imply use cases for ecosystem overview. It does not explicitly state when not to use or name alternatives, but the context of sibling tools (e.g., get_server, list_runtimes) suggests when this broader view is appropriate. Minor lack of 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?

No annotations provided, so description carries full burden. It clarifies that the tool fetches data (read operation) and specifies what is returned (servers, governance, plays). However, it does not mention side-effect safety, rate limits, or authentication needs.

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?

Single, well-structured sentence that front-loads the primary action and then lists the return components. No superfluous information.

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

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

The description adequately covers the complexity: one parameter, no output schema. It explains the components of the returned data. Minor gap: does not specify that the response is a single object, but that is implied.

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 a clear description for the 'slug' parameter. The tool description does not add additional parameter context beyond what the schema provides, meeting the baseline.

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 ('Fetch') and resource ('curated loadout') and details the components (servers, governance, plays), clearly distinguishing it from sibling tools like list_loadouts.

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

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

No guidance on when to use this tool vs alternatives such as get_server, list_loadouts, or get_alternatives. It does not provide context for 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 provided, so the description carries the full burden. It discloses the operation (fetch/full record) and what is returned, but lacks details on side effects, authorization needs, rate limits, or any potential impacts. This is a read-only tool, but without annotations, more context would be beneficial.

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, well-structured sentence that front-loads the core action. Every word contributes meaning; 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?

Given the tool's simplicity (one parameter, no output schema), the description effectively covers what the tool returns (full record with specific sections) and mentions the identifier type (slug). It lacks information about error scenarios or prerequisites, but is largely 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 coverage is 100% with a clear description for the single parameter 'slug'. The description adds only a minor example ('e.g. github'), which does not significantly enhance understanding beyond the schema. 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 verb 'Fetch', the resource 'full record for one MCP server', and the method 'by slug'. It also lists the types of data included (install methods, tools, trust, verification, provenance), making the purpose specific and distinct from siblings like search_servers or list_capabilities.

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 indicates use for fetching a single server's details by slug, but it does not explicitly state when to use this tool versus alternatives (e.g., compare_servers, get_alternatives) or when not to use it. 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?

Discloses ordering (most-populated first) and purpose, but does not explicitly state it's a read-only operation or discuss pagination beyond the limit parameter. However, no annotations exist to contradict.

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, front-loaded with purpose and example, followed by usage guidance. 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 list tool with one optional parameter and no output schema, the description adequately conveys return content, ordering, and integration with sibling tools.

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

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

Schema covers the single parameter with description. The tool description adds context on ordering and non-guessable taxonomy beyond what schema provides.

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

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

Description clearly states it lists capability slugs for filtering/lookup, with examples. Distinguishes from siblings by mentioning get_capability and search_servers.

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 advises using the returned slugs with get_capability or search_servers' capability filter, and notes the taxonomy isn't guessable, guiding appropriate 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 provided, so description carries full burden. It describes a read-only list operation with no side effects. Adds context about the nature of loadouts. Does not detail authentication or empty results, but for a simple list tool this is adequate.

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, no unnecessary words. Front-loaded with verb 'List', then explains what loadouts are and directs to alternative. Highly concise.

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

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

Given no output schema, no parameters, and low complexity, the description is complete. It explains what is listed, the nature of the items, and points to get_loadout for more detail. No 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?

No parameters in schema, so no additional meaning needed beyond what descriptor provides. The description adds context about what loadouts are, which indirectly clarifies that no parameters 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 clearly states the tool lists curated loadouts and explains what loadouts are (kits of MCP servers, governance, plays for jobs). It also distinguishes from sibling get_loadout by noting that list_loadouts is the agent-facing version and directing to get_loadout for full kit with live trust.

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 tells when to use this tool (for overview of curated loadouts) and when to use alternative get_loadout (for full kit with live trust). Provides context that this is the agent-facing version of the /loadouts product.

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 provided, but description adequately discloses that the tool returns a list of runtimes and config paths. It implies a read-only operation without needing to state it explicitly.

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, front-loaded with the purpose, and no unnecessary words. Every sentence adds 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?

Simple tool with no parameters and no output schema; description sufficiently covers what the tool returns (list with config paths). 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?

No parameters exist, so the description adds no parameter info beyond the schema. However, with 0 parameters, the baseline is 4, and description does not need to elaborate.

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

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

Description clearly states it lists runtimes supported by generate_runtime_config, with each one's config path. This is a specific verb+resource combination that distinguishes it from sibling tools like generate_runtime_config itself.

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 advises to use this tool instead of guessing runtime slugs, providing a clear when-to-use directive.

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 bears full responsibility for behavioral disclosure. It describes the output composition (loadout, servers, trust/risk, governance posture) but does not mention side effects, prerequisites, or safety implications (e.g., whether it makes external calls or modifies state). Thus, transparency is adequate but incomplete.

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

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

The description is a single, dense sentence that packs in key concepts but uses jargon ('curated loadout', 'governance posture', 'decision layer'). While informative, it could be more concise and structured for faster parsing.

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

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

Given no output schema, the description should clarify what the returned toolset contains beyond the mentioned components. It does not explain the return format (e.g., fields, structure), nor the process for transforming the goal into recommendations. This leaves gaps for an agent using the tool.

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

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

Schema coverage is 100%, so each parameter has a description. The tool's description adds meaningful context beyond the schema, such as explaining that risk_tolerance='read-only' restricts to safe tools for unsupervised agents, and that limit controls assembled servers. This enriches parameter understanding.

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: transforming a plain-language goal into a recommended, governed toolset including a curated loadout and assembled servers with live trust/risk info. It also distinguishes itself from siblings by positioning as 'the decision layer over search/capability/trust/loadouts'.

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

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

The description implies this tool should be used when a comprehensive, integrated recommendation is needed, rather than just searching or listing. However, it does not explicitly state when to use it versus alternatives like search_servers or list_loadouts, nor does it provide 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?

No annotations exist, so description must fully disclose behaviors. It mentions creating a submission but omits details like idempotency, rate limits, or follow-up actions.

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, front-loaded with verb and resource, 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 submission tool with 2 params and no output schema, the description covers purpose but lacks behavioral context (e.g., response format, confirmation). Could be more 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%, so the schema already documents parameters. The description adds minimal extra meaning beyond summarizing the detail field.

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 verb 'Report' and resource 'MCP server', specifying broken aspects (install, docs, endpoint) and outcome (creates submission). It distinguishes from sibling tools like get_server or check_trust.

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 a server is broken but provides no explicit guidance on when to use vs alternatives, nor any 'when not to use' 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 takes full responsibility for behavioral disclosure. It discloses two key behaviors: browsing by trust score when query is omitted, and the strict filter application with feedback via ignored_filters. It lacks details on authentication or rate limits, but those are not critical for a read-only search tool.

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

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

The description is two sentences, front-loaded with the primary purpose, and every part adds value. 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?

Given the absence of an output schema, the description lacks details about the return format (e.g., list of servers with fields, pagination metadata). The limit parameter implies pagination but no mention of next page tokens or result structure. This is a notable omission for a search tool with many sibling tools.

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

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

Schema coverage is 100% with descriptions for all 6 parameters, so the description adds minimal extra parameter meaning beyond the schema. The only additional context is the usage note about omitting query to browse, but this is a usage guideline rather than parameter semantics.

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 searches the MCPExplorer index by free text and filters, with the option to browse without a query. It uses a specific verb ('search') and resource ('MCP servers'), and the unique behavior of ranking by trust score distinguishes it from sibling tools like get_server or list_capabilities.

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 guidance on when to omit the query parameter for browsing, and assures that filters never silently fail (ignored_filters). However, it does not explicitly compare to alternative tools like get_server or compare_servers, though the context of search versus retrieval is implied.

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