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suggest_adrs

Analyze code changes or project context to suggest architectural decision records (ADRs) with advanced prompting. Prevents duplication and leverages Reflexion learning for consistent decisions.

Instructions

Suggest architectural decisions with advanced prompting techniques (Knowledge Generation + Reflexion). TIP: Read @.mcp-server-context.md first for project history, patterns, and previous ADRs to ensure consistency.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectPathNoPath to the project directory.
analysisTypeNoType of analysis to performcomprehensive
beforeCodeNoCode before changes (for code_changes analysis)
afterCodeNoCode after changes (for code_changes analysis)
changeDescriptionNoDescription of the changes (for code_changes analysis)
commitMessagesNoRelated commit messages (for code_changes analysis)
existingAdrsNoList of existing ADR titles to avoid duplication
enhancedModeNoEnable advanced prompting features (Knowledge Generation + Reflexion)
learningEnabledNoEnable Reflexion learning from past experiences
knowledgeEnhancementNoEnable Knowledge Generation for domain-specific insights
conversationContextNoRich context from the calling LLM about user goals and discussion history
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions advanced prompting but fails to disclose key behavioral traits like whether the tool reads files, modifies anything, or requires specific permissions. This leaves agents uncertain about side effects.

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 extremely concise with two sentences. It is front-loaded and every sentence serves a purpose: the first states the function, the second offers practical advice. No unnecessary words.

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's complexity (11 parameters, nested objects, no output schema), the description is too brief. It does not explain output format, how to interpret results, or any limitations. The tip is helpful but insufficient for complete understanding.

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%, so the schema already documents all parameters. The description adds no extra meaning beyond the schema, achieving baseline 3 without improvement.

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 the tool suggests architectural decisions with advanced techniques, giving a specific verb and resource. However, it does not differentiate from similar sibling tools like generate_adr_from_decision or generate_adrs_from_prd, so it's not a 5.

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 tip to read @.mcp-server-context.md provides usage context but no explicit guidance on when to use this tool versus alternatives. There is no mention of when not to use it or comparison with siblings.

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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