Arclan MCP Registry

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

No annotations exist, so the description must carry the full burden. It correctly implies a read operation but does not disclose authorization needs, rate limits, or error behavior. Adequate but not thorough.

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

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

Two efficient sentences: first states purpose, second details inputs and outputs. 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?

Completeness is good for a simple retrieval tool: it lists return fields and acceptable inputs. However, it could mention error handling or that it returns a single server object.

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 clear descriptions for both parameters. The description adds examples and groups parameter usage, but that is marginal improvement over 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 tool retrieves full details for a specific MCP server, gives examples of identifiers, and lists return fields. This distinguishes it from siblings like query_registry (search) and recommend_server (suggestions).

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

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

The description implies usage for fetching server details but does not explicitly state when to use this tool versus alternatives. No 'when to use' or 'when not to use' guidance is provided.

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

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

With no annotations provided, the description fully discloses behavior: it returns servers with a default status set (active, mcp_partial, auth_gated), and explains how each filter modifies results. It describes the purpose as a validation check, implying read-only, and no destructive behavior is mentioned. The description is transparent about query scope and filter effects.

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

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

The description is a single paragraph of six sentences, each serving a distinct purpose: main action, default status, stdio usage, production_safe, read_only, and usage workflow. It is front-loaded with the primary purpose and uses no superfluous 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?

Given 7 parameters with full schema descriptions, no output schema, and no annotations, the description covers all essential aspects: default behavior, each filter's effect, and workflow guidance (use before connecting, report after). It is sufficiently complete for a search/query 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?

Although the schema covers 100% of parameters with descriptions, the tool description adds significant value by explaining default behavior, providing context for production_safe (specific thresholds 97% uptime, 95% handshake success), and read_only (no write/exec tools). This goes well beyond the schema descriptions.

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 it searches the Arclan registry for MCP servers with specific verb 'Search', and distinguishes itself from siblings like get_server (single server), recommend_server (recommendations), and report_server (contribute data). It also details default filtering and optional filters.

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 explicitly advises when to use this tool: 'Use this before connecting to an MCP server to check its validation status and score.' It also explains when to use specific filters (status=stdio, production_safe=true, read_only=true) and provides a follow-up action: 'After using a server, call report_server to contribute reliability data.'

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?

Describes scoring factors (production safety, keyword relevance, registry score, latency, freshness) and mentions result includes reason code array. No annotations, so description carries full burden; could mention rate limits or side effects, but for a read-only recommendation tool, it's sufficiently 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?

Two sentences, front-loaded with verb and resource, no redundant language. 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?

Covers purpose, usage context, alternatives, and parameter explanations. No output schema, but mentions reason code array. Missing details on error handling or pagination, but adequate for a recommendation 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?

Input schema has 100% description coverage, so baseline is 3. Description doesn't add meaning beyond what schema already provides for parameters (e.g., auth, limit, read_only, production_safe).

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 provides ranked server recommendations for a task, and explicitly distinguishes from sibling tool query_registry by specifying that it returns an opinionated ranked list rather than a filtered 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?

Explicitly instructs to use this instead of query_registry when wanting an opinionated ranked list, providing clear context for when to choose this tool over 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, so the description must carry the full burden. It discloses that reports influence registry trust scores and lists two supported report types. However, it omits details like idempotency, error handling, or authorization requirements. Acceptable 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?

Three concise sentences that effectively front-load the purpose, then explain the rationale, and finally summarize the two modes. Every sentence adds value 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?

Given 14 parameters, no output schema, and no annotations, the description covers the key points: purpose, usage timing, two report formats, and registry impact. It does not address repetition handling or report aggregation details, but remains largely complete for a reporting 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 description coverage is 100%, so the baseline is 3. The description adds minimal extra context: highlighting that criterion and component_score work together for structured scoring. The schema already documents each 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's purpose: 'Submit an agent usage report for an MCP server.' It uses a specific verb ('submit') and resource ('usage report'), and the context of the sibling tools (get_server, query_registry, recommend_server) makes it distinct.

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 explicitly says 'Call this after using an MCP server so the registry can track real-world reliability.' This provides clear guidance on when to use it. It also notes the two report modes (simple outcome and structured scoring) without explicit exclusions or alternatives, but the sibling context is sufficient.

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