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read_merged_forward

Read-only

Read a WeChat merged-forward chat record by session_id and local_id, then supplement with keyword-hinted index queries. Returns visible nested text and whether the original record is complete.

Instructions

读取一条微信合并转发聊天记录。先按session_id + local_id精确回查,再用有限关键词查询补充索引变体;返回当前数据库可见的嵌套文本,并明确是否为完整原始记录。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
offsetNo
local_idYes
page_sizeNo
scan_limitNo
session_idYes
max_queriesNo
keyword_hintNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv4.1.8
    • addedInput schema / properties / offset
      Added value: +{
      +  "minimum": 0,
      +  "type": "integer"
      +}
    • addedInput schema / properties / page_size
      Added value: +{
      +  "exclusiveMinimum": 0,
      +  "maximum": 100,
      +  "type": "integer"
      +}
    • addedInput schema / properties / scan_limit
      Added value: +{
      +  "exclusiveMinimum": 0,
      +  "maximum": 20000,
      +  "type": "integer"
      +}
  2. First observedv4.1.1

TDQS

B3.4/5.0
Behavior4/5

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

Annotations already declare the safe read-only profile, so the bar is lower. The description adds real behavioral context beyond that: it discloses a two-phase lookup strategy, that only nested text visible in the current database is returned, and that it explicitly signals whether the record is the complete original — a meaningful completeness caveat.

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?

A single dense sentence with purpose front-loaded and the retrieval strategy following. No wasted filler, though the internal-mechanism detail crowds out parameter explanation.

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

Completeness3/5

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

With no output schema and 7 undocumented parameters, the description carries substantial burden. It does cover purpose, retrieval strategy, and return semantics (nested text + completeness flag), but leaves the pagination/scan parameters completely opaque, which is a clear gap for a tool with this many controls.

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

Parameters2/5

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

Schema description coverage is 0% across 7 parameters, so the description must compensate. It only implies session_id, local_id, and keyword_hint; the pagination and scan-control parameters (offset, page_size, scan_limit, max_queries) are entirely unexplained in both schema and description.

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 states a specific verb+resource: reading a WeChat merged-forward chat record (读取一条微信合并转发聊天记录). It is clearly distinguishable from siblings like get_message_by_id or read_wechat_post. It does not, however, explicitly contrast itself against those siblings.

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?

Usage is implied by the two-phase retrieval strategy (exact session_id + local_id lookup, then keyword variants), which tells the agent the tool handles merged-forward records specifically. But there is no explicit when-to-use/when-not guidance and no named alternative for non-merged messages.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.