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claude-session-continuity-mcp

solution_suggest

Get AI-synthesized fix suggestions for current errors by retrieving relevant past solutions from the archive, providing contextual recommendations.

Instructions

Get AI-powered fix suggestions for a current error based on the solution archive. Retrieves the most relevant past solutions and generates a contextual recommendation. Read-only. Use solution_find for direct archive lookup without AI synthesis; use solution_record after fixing an error to grow the archive.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorMessageYesThe current error message or stack trace
projectNoProject name for context (optional)
Behavior4/5

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

No annotations provided, but description explicitly states it is read-only, which is a key behavioral trait. It does not detail other aspects like auth or rate limits, but the read-only flag adds value beyond the structured fields.

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 three sentences, each serving a distinct purpose: main action, read-only note, and sibling alternatives. No wasted words, front-loaded with the core functionality.

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?

The description covers the tool's purpose, usage context, and behavioral trait (read-only). It does not explicitly state the return format, but the output is implied as a recommendation. Given the tool's simplicity and sibling guidance, it is largely 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?

The input schema has 100% description coverage, and the description restates the same parameter meanings without adding significant new context. Baseline 3 is appropriate as the description does not deepen understanding beyond the schema.

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 provides AI-powered fix suggestions for errors using the solution archive. It specifies the action (get suggestions) and the resource (current error, solution archive), and distinguishes from siblings.

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

Usage Guidelines5/5

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

Explicitly states when to use this tool versus alternatives: use solution_find for direct archive lookup and solution_record after fixing an error. This provides clear context for agent decision-making.

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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