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KlausFreiberufler

DevFlow MCP Server

idea_prompts_get

Retrieves curated prompts for development areas like Auth or Performance, each backed by wiki evidence, to generate well-grounded project ideas.

Instructions

DF-318 — Idea-Prompt-Garage. Returns curated prompts per area (Auth, Billing, Performance, …) with wiki-evidence already loaded. The user pastes one of these prompts into a chat with you, and you respond using the devflow-area-ideation skill.

Each area has: name, icon, counts (ADRs/patterns/runbooks in scope), and a ready-to-paste prompt. Use this to find well-grounded next-step ideas for a project domain instead of brainstorming from scratch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdNoProject id (defaults to linked project)
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the output structure (name, icon, counts, prompt) and a usage flow (user pastes prompt into chat). However, it omits behavioral traits such as side effects, authorization needs, or behavior when projectId is omitted, 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.

Conciseness4/5

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

The description is mostly concise with two sentences and a list of area components. The inclusion of 'DF-318 — Idea-Prompt-Garage' adds minor noise but does not significantly impair readability. The key action is front-loaded.

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

Completeness4/5

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

Given the tool has one optional parameter and no output schema, the description provides a solid overview of return value usage. It lacks explicit details on output format or filtering, but overall it is sufficient for a simple retrieval tool.

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 description coverage is 100% for the single parameter (projectId), so the schema already documents its meaning. The description does not add any additional parameter semantics, such as default behavior or impact, which is acceptable at baseline 3.

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 returns curated prompts per area with wiki-evidence, specifying the exact purpose: to provide grounded next-step ideas instead of brainstorming from scratch. The resource (prompts per area) and action (returns) are specific and differentiate it from siblings like 'ideas_get'.

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

Usage Guidelines4/5

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

The description offers usage guidance by recommending use 'to find well-grounded next-step ideas instead of brainstorming from scratch.' However, it does not explicitly state when not to use the tool or compare it to alternative tools like 'ideas_get', so it lacks full situational context.

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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