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youjunxiaji

gl-mcp-feedback

by youjunxiaji

interactive_feedback

Open a Web UI to collect interactive user feedback. Use it to confirm decisions, present summaries, and ask questions during AI workflows, avoiding unnecessary tool calls.

Instructions

Open a Web UI to collect interactive feedback from the user.

This tool is the PRIMARY communication channel with the user. The full list of "when to call" scenarios lives in the project's gl-mcp-feedback user rules; this docstring only covers the runtime contract that the tool itself enforces.

Strict prohibitions: - While this tool is available, DO NOT invoke Cursor's built-in AskQuestion. Route every question through summary as a numbered list. - DO NOT end the turn with a plain-text reply when there is substantive content for the user to read. Put it in summary. - When the user skips without feedback, re-call this tool to ask why; only stop on explicit termination (结束 / 不用了 / stop / done). - Allowed parameters: project_directory, summary, title, timeout. Names like question / choices / options belong to AskQuestion and will fail schema validation here.

summary writing rules: - Markdown: headings (##), lists, tables, code fences, bold for key decisions. Include modified file paths and explicit questions when applicable. - NEVER pass an empty string or the placeholder phrase 我已完成了您请求的任务。 — runtime validation rejects them and you must re-call with a real summary.

title writing rules: - Optional, ≤30 chars headline shown in the browser tab and summary header. Leave empty when summary is self-explanatory. - Examples: 需要你提供更多信息 / 修复完成,请验证 / 实现方案确认.

Args: project_directory: Absolute or relative project path. Defaults to cwd. summary: Required Markdown summary. No empty string, no placeholder. title: Optional short headline for the Web UI tab and summary header. timeout: Seconds to wait for user feedback. Keep >= 600.

Returns: ToolResult: TextContent with the user's text feedback plus MCPImage objects for any uploaded images. An empty result means the user skipped — re-call to ask why.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNoOptional short headline (max ~30 chars) for this feedback round, displayed in the browser tab and at the top of the AI summary panel. Should be concise (e.g. "需要你提供更多信息", "修复完成,请验证"). Leave empty when there's no good headline.
summaryNoMarkdown summary of the AI's current work / plan / question, rendered in the Web UI. MUST be filled in with substantive content; empty strings and placeholder phrases (e.g. "我已完成了您请求的任务。") are rejected at runtime.
timeoutNoSeconds to wait for user feedback. Keep >= 600.
project_directoryNoProject directory path..
Behavior5/5

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

No annotations are provided, so the description carries the full burden. It transparently discloses runtime validation (empty/placeholder rejection), the meaning of an empty result (user skipped → re-call), timeout behavior, and explicit termination terms. This goes well beyond basic behavior.

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 well-structured with clear sections (Strict prohibitions, summary rules, title rules, Args, Returns). It is front-loaded with the purpose and every section contains actionable rules without fluff, making the length justified.

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

Completeness5/5

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

Given no annotations and no output schema, the description fully compensates by covering purpose, usage, parameter semantics, return behavior (including image uploads), and error handling. It leaves little ambiguity for an agent selecting and invoking the tool.

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

Parameters4/5

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

Schema description coverage is 100%, so baseline is 3. The description adds value beyond the schema by providing writing rules (e.g., Markdown requirements, title ≤30 chars with examples), reinforcing that summary is effectively required despite its schema default, and setting a minimum timeout (≥600).

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 'Open a Web UI to collect interactive feedback from the user,' which is a specific verb plus resource. It also positions itself as the PRIMARY communication channel, distinguishing it from the sibling get_system_info and explicitly contrasting it with Cursor's AskQuestion.

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?

Provides explicit when-to-use and when-not-to-use guidance: 'DO NOT invoke Cursor's built-in AskQuestion' and 'DO NOT end the turn with a plain-text reply.' It also details the re-call policy on user skip and notes that full scenarios live in external rules, but the operational guidelines here are comprehensive.

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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