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Perisclaw: Use ChatGPT and Claude with your WhatsApp

Search Chats

search_chats
Read-only

Fuzzy-match a chat (group or DM) by name. Same matching as search_contacts.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search_chats"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMax results. Default 10.
queryYesName or fragment.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds the useful behavioral detail that matching is fuzzy and identical to search_contacts, but says nothing about result ordering, total counts, or what happens when nothing matches. With annotations doing heavy lifting, a 3 is appropriate.

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?

Two short sentences, front-loaded with the core verb and resource, with zero filler. Nothing could be removed without losing information.

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?

For a simple two-parameter read tool with full schema coverage and complete annotations, this is nearly sufficient. The only material gap is the lack of any statement about result behavior (ordering, whether partial matches rank), which would help an agent interpret results.

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 both parameters (query as name/fragment, limit defaulting to 10) are already documented in the schema. The description only reinforces that the query matches on name; it adds no format hints or fuzzy-matching rules beyond what the schema states. Baseline 3 applies.

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?

States a specific verb and resource (fuzzy-match a chat by name) and scopes it to group chats and DMs, which separates it from siblings like search_messages (content search) and chats_recent (unfiltered list). It doesn't explicitly name those siblings, so it falls short of 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?

Usage is only implied: the phrase 'by name' signals this is the tool for name lookups rather than message-content lookups. No explicit when-to-use or when-not-use statement, and no named alternative such as search_messages.

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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