No-Shell Agent Architect MCP

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

With no annotations provided, the description carries full burden. It discloses what the tool evaluates (shell-risk, missing inputs, etc.), indicating it is an analysis tool. However, it does not mention side effects or output format, but given the context, behavioral transparency is good.

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, concise sentence that effectively communicates the tool's purpose. It is front-loaded with the key action and criteria, with no unnecessary 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?

For a tool with one parameter and no output schema, the description is adequate but lacks detail on what the output looks like (e.g., a score, report). While it lists the evaluation criteria, it does not explain how the result is returned, which could leave an agent guessing.

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?

There is one parameter 'plan' with a clear schema description. The tool description adds value by specifying the scoring criteria, enhancing understanding beyond the schema. Since schema coverage is 100%, baseline is 3, but the additional context justifies a 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?

The description clearly states the tool's purpose: scoring an automation plan for specific criteria like shell-risk, missing inputs, etc. The verb 'score' and resource 'automation plan' are specific, and the listed aspects distinguish it from sibling tools that build or design automation components.

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 use when you have an existing automation plan to audit, but it does not explicitly state when to use this tool versus alternatives (e.g., sibling tools for building plans). No exclusions or prerequisites are mentioned.

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 full responsibility for behavioral disclosure. It states the output is an intake questionnaire for a 10-minute process, but omits safety traits, side effects, authentication needs, or return format, significantly limiting 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 a single, direct sentence with no wasted words. It is front-loaded with the core action and target audience. While concise, it could include slightly more detail without losing efficiency.

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 simplicity (1 parameter, no output schema, no annotations), the description is adequate but leaves gaps: it does not clarify how the questionnaire is delivered or if it saves data. For a low-complexity tool, this is minimally acceptable but not fully complete.

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 one undocumented parameter 'goal' (0% coverage). The description suggests 'goal' relates to the automation target, adding some meaning beyond the empty schema. However, it does not provide explicit format, constraints, or examples, so compensation is partial.

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 generates a 10-minute intake questionnaire for a non-developer targeting one workflow automation. It uses a specific verb and resource, but does not explicitly differentiate from sibling tools like 'audit_automation_plan' or 'build_m2m_package_contract'.

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 non-developer needs a single workflow automated, providing context on audience and scope. However, it lacks explicit guidance on when not to use this tool or alternatives, leaving the agent to infer appropriateness.

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 of disclosing behavioral traits. It only says 'create' without indicating side effects, permissions needed, or whether the operation is reversible or destructive. Minimal 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 a single sentence starting with the verb 'Create', which is effective. It is concise but at the cost of omitting important details. Every word earns its place, but the description could be expanded without becoming verbose.

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 8 parameters, no output schema, and no annotations, the description is too brief. It does not explain the return format, the structure of the contract, or how each parameter affects the result. Incomplete for a complex 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 75%, so the baseline is 3. The description does not add any meaning beyond the schema; it does not explain parameter dependencies, defaults, or how they influence the 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?

The description clearly states the tool creates a machine-readable package contract for a specific audience (agencies, SaaS builders, agents), with a specific output (MCP/API plus human-readable artifacts). This distinguishes it from siblings like audit_automation_plan or build_customer_intake, which serve 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?

The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention prerequisites, exclusions, or recommended contexts. The agent is left without decision criteria.

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 should carry the burden. It only states the tool returns criteria, but omits any behavioral traits like side effects, required permissions, or whether the operation is read-only.

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 sentence, which is concise but lacks structure. It front-loads the purpose but provides no breakdown of output or parameters.

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 no output schema and low schema coverage, the description fails to specify what 'criteria' includes, how it is returned, or any usage limitations. It is incomplete for an agent to use effectively.

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 0% and the description does not explain any of the three parameters (goal, risk, domain). The required 'goal' parameter lacks meaning, and optional parameters are ignored.

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 returns dry-run, QA, audit, and PASS criteria for one automation workflow. It uses a specific verb and resource, distinguishing it from siblings like audit_automation_plan, though not explicitly contrasting.

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, no prerequisites or constraints mentioned. The description is purely functional without usage context.

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 present, so the description carries the full burden. It does not disclose any behavioral traits such as side effects, permissions, or whether the operation is read-only or destructive. The 'turn into' phrasing implies generation but lacks clarity.

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 efficiently communicates the core action and outputs with 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?

Given six parameters and no output schema, the description is insufficient. It names outputs but does not explain how inputs influence the result or how to properly invoke the tool, leaving significant 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 description coverage is 67%, and the description adds no meaning beyond the schema. Parameters like 'risk', 'domain', 'language' are not explained, leaving the agent uncertain about their use.

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: transforming a vague automation request into a concrete stack of tools, permissions, workflows, and boundaries. It differentiates from siblings like 'build_validation_pack' or 'recommend_agent_tools' by focusing on the high-level design step.

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 is provided on when to use this tool versus its siblings. The description lacks context about prerequisites or situations where this tool is appropriate.

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 only mentions the output is a natural-language command and avoids empty shells, but it does not disclose any behavioral traits such as error handling, side effects, or safety considerations.

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 sentence, which is concise and front-loaded with the core purpose. However, it is perhaps too brief and could be expanded to include more context without losing conciseness.

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 has 6 parameters, no output schema, and no annotations, the description is insufficiently complete. It does not explain the return format, the effect of optional parameters, or how the generated command is structured.

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 67% (4 of 6 parameters have descriptions). The tool description does not add any additional meaning beyond what is in the schema, so it fails to compensate for the two parameters (risk, language) that lack descriptions. A higher-coverage baseline would warrant a 3, but here it does not suffice.

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 creates a copy-paste natural-language command for executing a workflow without producing an empty shell. However, it does not differentiate this tool from its siblings, which also deal with automation workflows, and the phrase 'without producing an empty shell' is somewhat ambiguous.

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 its siblings (e.g., audit_automation_plan, build_customer_intake). No context about prerequisites or alternative tools is given.

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 fully disclose behavioral traits. However, it only states what the tool recommends, without mentioning side effects, permissions, read-only status, or any constraints. The agent gets no insight into how the tool interacts with the system.

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 sentence that clearly communicates the tool's function without extraneous words. It is front-loaded with the verb and target, making it efficient for quick parsing.

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 has 6 parameters (including enums and optional fields) and no output schema, the description is too sparse. It fails to explain expected output format, how parameters affect results, or any behavioral context, leaving the agent underinformed 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?

Schema description coverage is 67%, and the description adds no parameter-level information beyond the schema. While the schema is reasonably explicit for most parameters, the description does not elaborate on how parameters like risk or domain influence recommendations, offering no added value.

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: to recommend specific resources like MCP servers, plugins, skills, etc., for a requested automation. It uses a specific verb ('Recommend') and enumerates the types of recommendations, distinguishing it from sibling tools that audit, build, or design.

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 does not provide any guidance on when to use this tool versus its siblings. There is no mention of use cases, prerequisites, or exclusions, leaving the agent to infer usage context from the tool name alone.

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