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

With no annotations, the description carries the transparency burden. The verbs 'Check' and 'Shows status' clearly indicate a non-destructive read-only operation, but it does not explicitly state that no system modifications occur or describe any permissions/requirements.

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, front-loaded sentence that states the action first and then lists the exact items checked. Every word earns its place; 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?

For a simple status-check tool with no parameters and no output schema, the description is complete. It explicitly lists all CLIs covered and states that it shows availability, which fully satisfies the user's likely need.

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 there is no parameter information to add. Per the baseline for 0-param tools, a score of 4 is appropriate since the description fills the schema's empty space with context about what is being checked.

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 the specific verb 'Check' and identifies the resource as deployment CLIs, listing all nine tools it inspects. This clearly distinguishes it from sibling deployment and provisioning tools, which perform actions rather than inspect prerequisites.

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 is a pre-deployment checklist but does not explicitly state when to use it or provide alternatives. It doesn't mention that it should be used before deploy_to_* or orchestrate_deploy, leaving the usage context to inference from the tool name and sibling list.

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 the burden of behavioral disclosure. It does mention that Dockerfile and docker-compose.yml are auto-generated and that optional containers (PostgreSQL, MongoDB, Redis) can be included, but it omits important side effects like modifying or overwriting existing project files, starting long-running processes, or what happens if Docker is not available.

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 long, front-loaded with the core action, and contains no redundant or filler content. Each sentence adds useful context: what it does, what it generates, and a prerequisite.

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?

This tool has 12 parameters, no output schema, and no annotations, yet the description is very brief. It lacks crucial context about what happens after deployment (e.g., how to access the app, whether the command blocks or returns immediately), potential file modifications, and failure modes beyond the Docker prerequisite. The schema covers parameter meaning but not the overall deployment 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 description coverage is 100%, so the input schema already documents all 12 parameters. The description adds limited extra meaning by explicitly naming the supported database containers and auto-generated files, but it does not go beyond what the schema descriptions already convey.

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 what the tool does: deploys the project locally using Docker/Docker Compose, with auto-generated Dockerfile and compose file. It is specific about the resource (local Docker deployment) and differentiates from cloud deployment siblings like deploy_to_vercel and deploy_to_railway, though it does not explicitly contrast with the similar sibling 'deploy_local'.

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 explicitly states the prerequisite that Docker must be installed and running, and the scope ('locally using Docker') gives context for when to use this tool versus cloud-based alternatives. However, it does not provide exclusions or guidance on when NOT to use it (e.g., when the project is not Docker-compatible).

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 description discloses key behaviors: auto-detection, running dev commands, and handling dependency installation, migrations, and seeding. Since no annotations are provided, the description carries the burden, and it does add some context. However, it omits potential side effects like modifying project files, network access, or failure handling, leaving room for more transparency.

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 concise sentences. The first sentence names the core action, and the second adds essential behavior. No filler or repetition of schema content, making it efficient and easy to scan.

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 9 parameters, no output schema, and no annotations, the description gives a high-level overview but lacks detail on return values, long-running behavior, or prerequisites. It covers the main workflow but not enough to fully inform an agent about edge cases (e.g., what happens if migrations are skipped or if the port is busy).

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 input schema provides detailed descriptions for all 9 parameters, covering 100% of the schema, so the baseline is 3. The description's mention of 'handles dependency installation, migrations, and seeding' aligns with parameters like installDeps, runMigrations, and seedCommand, but it adds no new semantic meaning beyond what the schema already tells the agent. The description provides context but not additional parameter-level 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?

The description clearly states the tool's primary action: 'Start the project locally as a native development server.' It specifies the resource (project) and the mode (local), distinguishing it from sibling tools like deploy_to_vercel or deploy_to_railway. The auto-detection of project types adds specificity without ambiguity.

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 indicates local usage ('Start the project locally') and implies a development context, which contrasts with cloud deployment siblings. However, it does not explicitly state when not to use it or mention alternatives (e.g., 'use deploy_to_vercel for production'), so it lacks explicit exclusions. The context is clear enough for an agent to select this tool for local development.

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?

There are no annotations, so the description must disclose behavioral traits. It mentions the API token requirement and that 'Railway handles the full stack,' but does not explain whether the deployment is destructive, creates a new project or updates existing, what the success/failure output looks like, or any side effects on the local project. The mutation nature is only implicit via the word 'deploy.'

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 action, and every clause adds useful information. It avoids redundancy and is appropriately sized for the tool's complexity.

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?

This is a complex tool with 9 parameters, nested objects, no annotations, and no output schema. The description only covers the high-level purpose and token requirement, leaving significant gaps around deployment workflow, return values, error scenarios, and how it interacts with existing Railway projects. It is not complete enough for an agent to invoke confidently without further assumptions.

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 value beyond schema: it groups 'PostgreSQL, Redis, MongoDB' as optional plugins, aligning with the boolean parameters, and highlights the token requirement. No additional syntax or edge-case semantics are provided.

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: 'Deploy a project to Railway with optional database plugins.' This specifies the verb (deploy), the resource (project to Railway), and unique features (database plugins), distinguishing it from sibling tools like deploy_to_vercel and deploy_local.

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 clear context by naming the target platform (Railway) and optional plugins, implying when it should be used. It does not explicitly exclude alternatives or mention when not to use it, but the platform-specific focus gives sufficient guidance for typical selection scenarios.

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 the description alone must disclose behavioral traits. It only states a prerequisite (API token) but fails to mention that deployment is a mutating operation, potential side effects, or return behavior.

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 concise sentences, front-loaded with the primary purpose. Each sentence adds value without 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?

The tool is complex (8 params, deployment, env vars) with no output schema, but the description provides only basic purpose and a prerequisite. Missing are usage guidance vs. siblings, deployment side effects, and outcome details.

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 parameters are well-documented. The description adds meaningful context by listing supported frameworks and emphasizing the token requirement, going 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 ('Deploy'), resource ('to Vercel'), and scope ('frontend, fullstack, or API'). It also distinguishes from sibling tools by naming Vercel and supported frameworks.

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 implies this tool is for Vercel deployments, providing context without explicit alternatives or exclusions. It does not mention siblings like deploy_to_railway or deploy_local, but the targeting is 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?

With no annotations provided, the description must carry the full burden. It only states high-level outcomes (provisions databases, deploys apps, connects env vars) but does not disclose side effects, prerequisites, reversibility, or failure behavior. For a powerful orchestration tool, this is a significant gap.

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 long, front-loaded with the primary action, and lists targets compactly. It avoids redundancy with the schema and every sentence contributes meaningful 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 tool is complex (8 params, nested objects, no output schema), but the schema descriptions fill in most parameter details. The description provides a useful overview but lacks guidance on preconditions, return values, or edge cases (e.g., token requirements, project structure), leaving some context 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?

The schema already provides 100% coverage with descriptive text for every parameter, including the 'target' enum and 'tokens' object. The description adds only a general statement about automatic env var connection, not specific parameter-level semantics, so it remains at 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 clearly states the tool orchestrates full-stack deployments combining multiple services, and it explicitly lists target combinations (vercel+neon, etc.), distinguishing it from sibling tools that handle individual deployments or database provisioning.

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 combined, multi-service deployment is needed, as evidenced by 'combining multiple services' and the target list. It does not explicitly name alternative tools, but the context is clear enough compared to siblings.

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 must carry full behavioral disclosure. It only mentions tier support and API key requirement, failing to clarify side effects like cost, resource provisioning time, idempotency, or project creation behavior.

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 main action, and no filler. Every word contributes to understanding the tool's purpose and prerequisites.

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?

This is a complex 13-parameter provisioning tool with no output schema or annotations. The description doesn't cover return values, errors, execution time, or cost implications, leaving significant context gaps for an agent to predict 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 description coverage is 100%, so the baseline is 3. The description adds minimal parameter context beyond reinforcing that public/private keys are needed. No additional syntax or format details are provided 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 first sentence clearly states the tool creates a MongoDB Atlas cluster with database and user, which is a specific verb+resource combination. It distinguishes from sibling tools like provision_neon_database by specifying MongoDB Atlas explicitly.

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 mentions tiers (free to dedicated) and requisite API keys, giving clear context for when this tool is appropriate. However, it doesn't explicitly contrast with alternatives like provision_neon_database or state when not to use it.

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?

Without annotations, the description carries the transparency burden. It discloses mutating actions (create, apply schema, run migrations) and the requirement for an API key, but it does not describe side effects like cost, failure behavior, or what resources are affected. This is 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?

The description is two sentences, front-loaded with the main action, and wastes no words. It efficiently conveys purpose, capability, and a key prerequisite.

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 complexity (8 parameters, side effects, no output schema), the description is too brief. It doesn't explain what the tool returns (e.g., connection string, project ID) or potential errors, which is critical for a provisioning tool. Missing details about ordering or interactions between parameters also reduce completeness.

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 input schema has 100% coverage with descriptive parameter names and defaults. The description adds little beyond confirming that schema files and migration commands are supported, which is redundant with the schema. Baseline 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 specifies a clear action—creating a serverless PostgreSQL database on Neon—and distinguishes it from sibling tools like provision_mongodb. It also mentions schema/migration support, so the agent knows the tool's core function.

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 provisioning a Neon database but does not explicitly state when to choose this over alternatives. It provides a prerequisite (Neon API key) and mentions schema/migration support, which offers some contextual guidance, but no explicit exclusion or alternative references.

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