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nuno-morais

Prompt Enhancer MCP

by nuno-morais

generate_system_prompt

Drafts a system prompt for a given role, then auto-lints and scores it to ensure quality. Optionally generates terse and guardrailed variants for comparison.

Instructions

Drafts a system prompt for a given role, then auto-lints and auto-scores it before returning. Pass rigor: 'both' to generate a terse and a guardrailed variant and get a judged comparison.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
roleYesThe agent's role/task, e.g. 'senior code reviewer'
modelNoOverride for the model
rigorNo'both' generates a terse and a guardrailed variant and judges them head-to-headguardrailed
engineNoThe underlying LLM engine to use
formatNoOutput format for the generated prompt(s)plain
transcriptNoOptional failed-conversation excerpt to diagnose from instead of a cold role
failure_modesNoOptional known failure modes to guard against (e.g. 'hallucinates file paths', 'too verbose')
Behavior3/5

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

With no annotations, the description discloses the key behavior: drafting then auto-linting and auto-scoring. However, it does not detail other aspects like return format or authentication needs. The 'rigor' behavior is explained, but overall transparency is adequate yet not comprehensive.

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?

Two sentences: first sentence covers the core purpose and auto-validation, second explains the key 'rigor' option. No filler, every sentence adds value. Ideal conciseness.

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

Completeness3/5

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

For a 7-parameter tool with no output schema, the description is somewhat minimal. It does not describe what the returned output looks like (e.g., combined prompt with scores) or mention optional parameters like transcript or failure_modes. Adequate but not complete.

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 100%, so baseline is 3. The description adds minimal new meaning beyond the schema; it repeats the 'both' option explanation already present in the schema's description. The role parameter is mentioned generally.

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

Purpose5/5

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

The description clearly states the tool drafts a system prompt for a role and then auto-lints and auto-scores it. It uses a specific verb 'Drafts' and distinguishes itself from sibling tools (lint_prompt, score_prompt) by combining these steps in one call.

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

Usage Guidelines3/5

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

The description implies the tool is an all-in-one for generating and evaluating prompts but does not explicitly state when to use it versus sibling tools. No alternatives or exclusions are mentioned, leaving guidance implicit.

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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