xytara MCP Executor

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 state whether the catalog is static, cached, or dynamic; whether it reflects permissions or feature flags; or what the return payload looks like. 'Current enabled' implies variability but no further detail is given.

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

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

A single, front-loaded sentence with no wasted words. The core action and resource appear immediately.

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 parameterless discovery tool with no output schema, the description is minimally adequate but leaves the return shape and freshness semantics unexplained. It is enough to identify the tool but not to predict its behavior fully.

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 takes zero parameters, so the baseline is 4. There are no parameters to document and the description appropriately does not mention any.

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 and resource ('Returns the current enabled MCP tool catalog') and adds a qualifier ('discovery-aware agents'). It is clear what the tool does, though it does not differentiate from sibling tools like summarize, json.validate, or zones.lookup since they serve entirely different purposes.

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 is provided. The phrase 'discovery-aware agents' hints at the intended caller but does not tell an agent when to invoke this versus other tools, nor are any alternatives named.

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 implies a read-only, deterministic operation (no mutation), but says nothing about what happens on an invalid payload (error vs. findings), whether it requires a known schema_name, or what the 'shape metadata' contains. That is a significant disclosure gap for a validation 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?

A single front-loaded sentence with no filler or waste. It is efficient, though brevity here borders on under-specification rather than tightness.

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

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

With no annotations, no output schema, and no explanation of failure behavior or the structure of the returned shape metadata, the definition leaves key questions unanswered for a tool whose entire job is producing validation results.

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

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

Schema description coverage is 100%, so both parameters are already documented in the schema, and the baseline is 3. The description adds nothing about how schema_name affects validation or whether it is required for meaningful output.

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 (validates) and resource (JSON object payload) and hints at the return value ('deterministic shape metadata'). Sibling tools (catalog, reply.draft, summarize, zones.lookup) are unrelated domains, so no differentiation is needed, but the description never clarifies what the payload is validated against or what 'shape metadata' means.

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?

Gives no when-to-use guidance, no prerequisites, and no alternatives or exclusions. An agent cannot infer from the text whether this is a pre-flight check before other tools or a standalone inspection utility.

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. 'Produces a draft' hints at a pure generation with no persistence, but it does not explicitly state side effects, whether output is stored anywhere, cost/latency, or tone-handling behavior beyond the parameter name.

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

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

A single front-loaded sentence with no wasted clauses. 'agent-ready' is slightly filler but the sentence is efficient and appropriately sized for a two-parameter transform 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 simple 2-parameter transform with no output schema, the description covers the basic purpose but omits the shape/format of the returned draft and any tone-specific behavior, leaving minor gaps an agent cannot fill from structured fields.

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 both text and tone. The description only restates that transformation draws from 'source text and tone,' adding no syntax, format, or value hints beyond the schema, making the baseline 3 correct.

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 (Produces) and resource (reply draft) and adds the inputs it draws from (source text and tone), which is enough to separate it from siblings like summarize and catalog. It is clear, though it partly restates the name rather than articulating a distinct scope.

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

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

No guidance on when to use this versus alternatives such as summarize, which is the closest sibling (both transform text). No prerequisites, exclusions, or trigger conditions are provided; the agent must infer usage 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 are provided, so the full behavioral burden falls on the description. It says 'deterministic' but doesn't explain what that means in practice (e.g., same output for same input) or describe return format, limits, or performance characteristics.

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 short sentence, but it front-loads a vague runtime qualifier ('first-run MCP execution') instead of practical details like output length or supported input. Minimal but wastes the one chance to inform.

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

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

No output schema, no annotations, and the description covers only a bare verb. It omits expected output form, determinism guarantees, and any limits. For a summarization tool, much more is needed for correct 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?

Only one parameter ('text'), and the schema already includes a description ('Plain text to summarize.'). With 100% schema coverage, the description adds little, but the baseline for zero undocumented params 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?

States a specific verb (summarize) and resource (text), but the phrase 'for first-run MCP execution' adds a runtime detail rather than scope. It doesn't distinguish from siblings like 'catalog' or 'reply.draft', leaving purpose only partly clarified.

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 versus alternatives or under what conditions (text length, language, etc.). The single sibling names don't help either. The agent must infer usage entirely.

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 burden. It only says it performs a lookup and lists record types, but does not disclose network behavior, error handling, timeouts, authentication requirements, or whether the operation is read-only. The read-only nature is implied but not stated.

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

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

The single sentence is concise and front-loaded, with no wasted words. It is efficient, though not especially structured beyond the core statement.

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 lookup tool with full schema coverage for its one parameter, the description is minimally adequate. However, because no output schema exists, it should ideally describe the return format (e.g., records, fields) or behavior, which it does not.

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 single hostname parameter, so the schema fully documents it. The description adds no additional meaning about the parameter beyond what the schema already provides, which matches the baseline of 3 when schema coverage is high.

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 ('lookup') and resource ('DNS and zone') and lists the record types queried. It is clear what the tool does, though it does not explicitly differentiate from any sibling tools (which are unrelated anyway).

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, nor any prerequisites, exclusions, or contextual conditions. Usage is only implied by the tool name and the mention of DNS record types.

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