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TapTap Open API MCP Server

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by taptap

get_debug_feedbacks

Pull user debug feedback records for the selected app, download screenshots and logs, and generate AI-ready debug context files.

Instructions

    [H5 Debug Workflow]
    Pull user debug feedback records for the selected app, download artifacts (screenshots/logs),
    and generate AI-ready debug context files.

    **PREREQUISITE: An app MUST be selected first.**
    Before calling this tool, ALWAYS call get_current_app_info to verify an app is selected.
    If not selected, guide user through:
    1) Call list_developers_and_apps to show available apps
    2) Show list to user and ASK them to choose
    3) Call select_app with user's choice
    4) Then call this tool

    **DEFAULT BEHAVIOR:**
    - fetch_and_mark_processed defaults to true
    - download_assets defaults to true
    - downloaded files are saved under logs/feed_back/feedback_{id}/

    **CALLING POLICY FOR AGENTS:**
    - If user says "拉取/查看反馈" without explicit read-only intent, DO NOT pass fetch_and_mark_processed.
      Let default behavior (true) apply.
    - ONLY pass fetch_and_mark_processed=false when user explicitly requests read-only
      behavior (e.g. "只查看,不标记处理").
    - When user provides a moment_id (or a TapTap moment URL), pass it via moment_id param to fetch a single feedback.
      In this case, fetch_and_mark_processed is automatically forced to false (read-only single lookup).
  

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many feedback records to pull (1-10, default 3).
statusNoFeedback status filter: - 0: all - 1: unprocessed - 2: processed When fetch_and_mark_processed=true, status filter will be ignored by server.
moment_idNoOptional. Filter to a single feedback by moment_id. Accepts either a pure numeric ID (e.g. "795659996946762795") or a full TapTap moment URL (e.g. "https://www.taptap.cn/moment/795659996946762795") — the handler will extract the numeric ID. When provided, server returns only the matching record, and fetch_and_mark_processed is forced to false (read-only single lookup). MUST be passed as a string to preserve precision for large IDs.
download_assetsNoWhether to download feedback JSON/screenshot/log files to local workspace. Default true.
fetch_and_mark_processedNoPull unprocessed records and mark them processed on server. Default true. Set false only for explicit read-only requests. When true, status is ignored.
Behavior4/5

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

The description discloses default parameter values, file save locations, and the forced read-only behavior when moment_id is provided. However, since no annotations are present (e.g., readOnlyHint, destructiveHint), the description carries full burden and could still mention potential side effects like rate limits, but it adequately covers the main behavioral aspects.

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 structured with clear sections (prerequisite, default behavior, calling policy) and includes front-loaded summary. Although it is somewhat verbose, every section adds essential context and earns its place, making it well-organized and informative.

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's complexity (5 parameters, important prerequisites, and no output schema), the description covers all necessary aspects: prerequisites, default behaviors, parameter interactions, and agent policies. It could provide more detail about the output format or specific error handling, but it is sufficiently complete for effective tool usage.

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

Parameters5/5

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

All parameters have 100% schema description coverage, and the description adds significant context beyond the schema: it explains moment_id accepts both numeric IDs and full URLs, clarifies that status is ignored when fetch_and_mark_processed=true, and provides default values and usage policies for fetch_and_mark_processed and download_assets.

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's function: pulling debug feedback records, downloading artifacts, and generating AI-ready debug context files. It distinguishes itself from the numerous sibling tools (e.g., check_ads_status, get_current_app_info) by focusing on debug feedback operations.

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?

Extensive usage guidelines are provided: a prerequisite (app must be selected), a specific calling sequence involving get_current_app_info, list_developers_and_apps, and select_app, default behaviors, and a detailed calling policy for agents regarding the fetch_and_mark_processed parameter when handling moment_id or read-only requests.

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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