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Generate No-Shell Prompt

generate_no_shell_prompt

Create a copy-paste natural-language command that tells an agent how to execute the workflow without producing an empty shell.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYesPlain-language automation goal.
riskNo
domainNoOptional domain hint such as email_docs, ecommerce_data, knowledge_base, coding.
languageNo
userTypeNoNon-developer, solo operator, small team, developer, agency, etc.
currentToolsNoTools/plugins/MCPs already available to the user.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

Without annotations, the description must disclose behavior. It only states the output is a 'copy-paste natural-language command' and mentions avoiding an empty shell. There is no information about side effects, required permissions, rate limits, or what happens to the input. The tool name suggests it avoids shell execution, but this is not explained.

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

Conciseness5/5

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

The description is a single 18-word sentence that conveys the core purpose efficiently. It is front-loaded with key information and contains no redundant or filler content.

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

Completeness2/5

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 annotations, and no output schema, the description is insufficient. It does not explain what a 'no-shell prompt' is, what the output looks like, or how parameters like 'userType' and 'currentTools' affect the result. The agent lacks enough context to use the tool effectively.

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

Parameters3/5

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

Schema coverage is 67% (4 of 6 parameters have descriptions), so baseline is 3. The tool description does not add any parameter-specific detail beyond the schema. It mentions 'goal' as required but does not elaborate on how to use risk, domain, language, etc. However, the schema itself provides some guidance.

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

Purpose4/5

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

The description clearly states that the tool creates a copy-paste natural-language command to instruct an agent, and mentions avoiding empty shell output. This distinguishes it from sibling tools which focus on auditing, building packages, or designing stacks. However, it could be more precise about the type of workflow automation.

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

Usage Guidelines2/5

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 like recommend_agent_tools or build_validation_pack. No context about prerequisites, appropriate scenarios, or exclusions is given.

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

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TDQS

B3.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: audit, intake, contract, validation, design, prompt generation, and recommendations. No two tools overlap in functionality, ensuring an agent can select the right tool without confusion.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case, with verbs like audit, build, design, generate, and recommend, and descriptive noun phrases. This uniformity makes the tool set predictable and easy to navigate.

Tool Count5/5

With 7 tools, the server covers the essential stages of automation design from intake to auditing without being sparse or overwhelming. The count is well-scoped for the domain.

Completeness5/5

The tool set covers the complete lifecycle of designing a no-shell automation: intake, design, validation, contract generation, prompt creation, and auditing. There are no obvious gaps in the workflow.