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list_messages

Search the full message history by topic, text, status, kind, or work status. Returns newest first; use fields to project results and avoid large bodies.

Instructions

Search the full message history with optional filters. Use 'topic' for substring match on the topic, 'text' for substring match across topic OR body ('where did we discuss merchant_id'); 'status' (open/resolved), 'kind' and 'work_status' for exact match on structured fields. Returns newest first. 'pin_key' filters to proposals STRUCTURALLY linked to a pin (the field set at send time) — messages that merely mention the key in their text are deliberately NOT matched, which is the difference between this and text=. Optional 'fields' projects the response: a list of field names, or the single value 'headers' for the usual listing set (everything except the bodies). Omit it and the full record comes back exactly as before. Use it when a listing over a long history would otherwise be too large to return — bodies dominate the size, and a 'which messages' question rarely needs them; fetch the ones you want individually afterwards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo
textNo
limitNo
sinceNo
topicNo
fieldsNo
statusNo
pin_keyNo
to_roleNo
from_roleNo
unread_onlyNo
work_statusNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses sort order ('newest first'), the deliberate non-match semantics of pin_key, the exact contents of the 'headers' set, and the backwards-compatible default when 'fields' is omitted. It omits permission/auth requirements and pagination beyond the implicit limit.

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?

Long but dense and front-loaded: the general purpose comes first, then filters, then the pin_key/text distinction, then the fields projection. Nearly every sentence adds a distinct behavioral fact rather than restating the schema.

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?

An output schema exists so return values needn't be explained, and the filter semantics are largely covered. But for a 12-parameter tool with 0% schema coverage, five parameters (to_role, from_role, unread_only, since, limit) are undocumented anywhere, leaving the definition incomplete.

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 0%, so the description must compensate for all 12 params. It meaningfully explains topic, text, status, kind, work_status, pin_key, and fields, but leaves limit, since, to_role, from_role, and unread_only entirely undefined — roughly half the surface remains opaque.

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 ('Search the full message history') and enumerates the filter dimensions, so an agent knows exactly what it retrieves. It doesn't explicitly distinguish itself from close siblings like search_messages or message_history, which is the one thing keeping it from 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 Guidelines4/5

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

Gives concrete when-to-use guidance for the 'fields' projection ('use it when a listing over a long history would otherwise be too large') and explains the alternative explicitly for pin_key vs text=. Strong contextual routing, though it doesn't state when to prefer a different tool entirely.

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