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

Annotations provide only a title with no readOnlyHint or destructiveHint, so the description carries full responsibility. It discloses read-only behavior, that it 'Does not probe remote health,' and that an empty list means no servers registered in this process. These are meaningful behavioral details beyond the annotations.

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?

Four tightly packed sentences: purpose and fields, when to use, empty-list meaning, read-only safety and non-probing behavior. Every sentence adds value and the key information is front-loaded in the first sentence.

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

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

For a zero-parameter read-only tool, the description covers purpose, usage timing, result interpretation, and behavioral caveats. An output schema exists to document return values, so nothing essential is missing. The sibling context and the boundary with rack_add/rack_remove are clearly articulated.

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 and the schema has 100% coverage (empty object), which meets the baseline of 4. The description adds no parameter details because none exist, but it does describe the output fields, which is a small bonus. No deduction needed for a parameterless tool.

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

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

The description clearly states a specific verb and resource: 'List MCP servers currently mounted on the SuperAgentic rack' and even enumerates the returned fields (name, command or URL, notes). It differentiates itself from mutating siblings by explicitly labeling the operation read-only and naming rack_add/rack_remove as the mutation tools.

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

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

The description gives explicit when-to-use guidance: 'Use after rack_add to confirm membership.' It also clarifies the empty-list interpretation, preventing false conclusions, and explicitly routes mutations to rack_add/rack_remove. This is strong usage direction with no ambiguity.

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 safety annotations beyond the title, the description carries the full burden and does so excellently. It discloses that the operation is an idempotent upsert ('Overwrites an existing entry with the same name'), that it does not start the child process, does not validate the command, and is a local write only. This is far more than the structured annotations provide.

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. It front-loads the primary purpose, then adds side-effect warnings, then provides sibling routing. 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?

The tool is simple, the input schema covers all parameters, and an output schema exists. The description fully covers behavior, side effects, idempotency, validation limits, and sibling alternatives, leaving no significant gap for an agent to call it correctly.

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 all three parameters in detail. The description adds a small amount of meaning by explaining how 'name' connects to route_task and rack_remove and by clarifying that 'command' is not validated, but it does not substantially extend the parameter semantics 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 tool's action: 'Register an MCP server on the in-memory rack so later route_task calls can target it by name.' It names the specific resource (the rack) and the purpose, and it differentiates itself from siblings by explicitly mentioning route_task, list_rack, and rack_remove.

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 practical usage context: it says the tool is for registration, does not start or validate the child process, and explicitly points to list_rack for inspection and rack_remove for deletion. It could be slightly stronger by explicitly stating when not to use this tool, but the alternatives are clear.

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?

Annotations carry only a title, so the description bears the full disclosure burden and meets it: it flags 'Destructive', specifies that missing names return an error object instead of raising, and explains the narrow side effect of dropping only the catalog entry. This is exemplary transparency for a mutation 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?

Five short sentences, each carrying distinct information: action, destructiveness, error behavior, side-effect scope, and prerequisite. The main verb is front-loaded and no sentence is redundant.

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

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

For a single-parameter, in-memory destructive tool with an output schema present, the description covers the action, risks, error semantics, partial effects, and a confirmation step. Nothing essential to a correct call is missing.

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 already documents the sole parameter fully ('Rack key previously passed to rack_add'), and the description's 'by name' adds little beyond reinforcing that the identifier is a string key. With 100% schema coverage, the baseline of 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?

The description opens with a specific verb and resource: 'Remove one MCP server from the in-memory rack by name.' This is not a tautology of the title and clearly differentiates from siblings like rack_add and list_rack by naming the action and target.

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

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

It gives an explicit precondition ('Use list_rack first to confirm the name') and clarifies a limitation ('Does not stop a running child'), which tells the agent when this tool is not sufficient. It stops short of naming a sibling alternative for stopping a child, so it earns a 4 rather than a 5.

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

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

The annotations provide only a title, so the description carries the full burden. It discloses that the planner is a deterministic stub, lists candidates only, does not execute downstream tools, is read-only with respect to the rack, and makes no network calls. This is unusually 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 compact and front-loaded with the core purpose, followed by behavioral constraints and usage guidance. Every sentence adds value, and there is no redundant restating of the tool name or schema.

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 two-parameter tool with an output schema, the description covers purpose, behavior, limitations, and usage sequencing. The agent has everything needed to decide when to call it and what to expect.

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 parameters. The description adds context about the overall task-routing purpose but does not add new parameter-specific meaning beyond what the 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?

The description uses a specific verb-resource pair ('produce a routing plan for a natural-language task against the current rack') and immediately clarifies the current behavior (deterministic stub that lists candidate servers). This clearly distinguishes it from rack-management siblings like rack_add and rack_remove.

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 'Use after rack_add' and 'Not a substitute for status', giving both sequencing and an exclusion. It also tells the agent that the planner does not execute downstream tools, so the agent knows not to expect execution side effects.

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?

Despite minimal annotations, the description explicitly states 'Read-only local state' and 'Does not call downstream MCP servers (not open-world),' which are critical behavioral traits for an agent deciding whether this is safe to invoke. This goes beyond what the title and annotations alone convey.

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 sentences deliver purpose, usage guidance, and behavioral constraints without wasted words. The primary outcome is front-loaded, and every remaining clause adds decision-relevant context.

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

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

For a zero-parameter status probe with an output schema, this is complete: it states what is returned, when to use it, what it does not do, and how it relates to sibling tools. No additional context is needed for correct selection and invocation.

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

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

The tool has zero parameters, so the baseline for this dimension is 4. The description adds no parameter-level semantics because there are no parameters to document.

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

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

The description uses a specific verb ('Return') and names the exact resource: SuperAgenticMCP router health. It enumerates concrete output contents (version, process status, racked server count) and explicitly contrasts itself with list_rack for the actual catalog, making sibling differentiation clear.

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

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

The description explicitly directs when to use the tool: 'Use this as a connectivity probe before list_rack or route_task.' It also tells the agent to pair with list_rack for the catalog, providing clear guidance on which sibling to use for a different purpose.

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