petal-components-mcp

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

No annotations provided, so description carries full burden. It accurately describes the non-destructive read behavior and the contents of the returned schema. No contradictory or missing behavioral information.

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 fluff. First sentence states purpose and contents; second gives crucial usage instruction. Every word 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?

Despite no output schema, the description enumerates what the returned schema includes (attrs, slots, defaults, allowed values, example). For a simple single-parameter lookup, this is fully informative. 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?

Schema coverage is 100% with a clear description of the 'name' parameter. The description adds valuable context: the relationship to HEEx tags and a pointer to list_components for inventory, enhancing understanding 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 'Get' and resource 'full schema for one petal_components component', listing specific contents (attrs, slots, defaults, allowed values, HEEx example). It distinguishes from siblings list_components (list vs single) and get_install_instructions (different purpose).

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 tells when to call: 'every time you are about to write a tag like <.button>, <.modal>...' and why: to avoid training-data guesses. It implies alternatives by mentioning list_components for inventory.

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 no annotations, the description discloses that steps cover mix.exs, deps.get, Tailwind config, and imports, and states idempotency. It does not explicitly declare read-only, but 'Get' in name and 'safe' imply no side effects. Sufficient for a read-only 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?

Two concise sentences. First sentence states purpose and resources, second covers content and safety. No unnecessary words; efficient structure.

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, and behavior adequately given no output schema or annotations. Could mention return format or prerequisites but overall complete for a simple information retrieval 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?

No parameters; schema coverage is 100%. Description adds no param info, which is expected. Baseline for zero parameters is 4, and description does not detract.

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 installation steps for petal_components in Phoenix projects. It distinguishes from siblings 'get_component' and 'list_components' which focus on individual components, not installation.

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 lists three scenarios for calling: user asks for installation, setting up new project, verifying existing installation. Also notes idempotency, making it safe for partially configured setups. No guidance on when to avoid, but positive cases are well covered.

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. The description implies a read-only listing but does not explicitly state behavior like idempotency, rate limits, or permissions. However, for a simple list tool with no params, the omission is acceptable but not ideal.

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 purpose, no wasted words. Every sentence adds value: first defines the tool, second explains when to call it.

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 tool with no output schema but sibling context, the description is complete. It tells what it returns (list of components), when to use it (before composition), and its role in the library ecosystem.

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 has zero parameters and 100% coverage. Description adds no param detail, which is appropriate since none exist. It provides context about the library and usage, earning above 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 clearly states the verb and resource: 'List every component shipped by petal_components.' It distinguishes from siblings by positioning this as the canonical overview tool, contrasting with get_component (for details) and get_install_instructions.

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?

Explicit guidance to 'call it before composing any HEEx' to avoid hand-rolling components. While it doesn't directly state when not to use, it implies the tool is for discovery and reuse, and siblings fill other roles.

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