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Glama

summarize_thread

Read-only

Retrieve a thread's participants, message count, and newest messages for summarization. Use it to inspect conversation context, while search_messages finds threads and fetch_inbox drains unread mail.

Instructions

Return {thread_id, summary:{participants, total_messages}, messages} for you to summarize; this tool does not generate prose or mark mail read. Find thread_id with search_messages or fetch_inbox. per_thread_limit selects the newest messages with full bodies, returned oldest first. It defaults to 50 and caps at 1000, with no continuation cursor; total_messages counts the entire thread, even when messages is truncated. Use search_messages for text matching and fetch_inbox to drain unread mail. No matching thread returns zero messages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
thread_idYesThe first message's id, or the thread_id its replies carry.
project_keyYesAbsolute path of the repository's primary checkout.
per_thread_limitNoNewest messages to return; positive page size, default 50, capped at 1000.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.8/5.0
Behavior5/5

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

Goes well past the readOnlyHint/openWorldHint annotations by disclosing that it does not generate prose and does not mark mail read, that there is no continuation cursor, and that total_messages counts the entire thread even when messages is truncated. These are exactly the behavioral traits an agent needs beyond structured hints.

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?

Return shape is front-loaded and every sentence carries distinct operational information (return format, non-actions, id sourcing, limit behavior, no-cursor, empty-thread case). It is dense but not padded, staying a single tight paragraph.

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?

No output schema exists, yet the description fully specifies the return shape, truncation semantics, and the zero-message case, so the agent has everything needed to call and interpret results correctly.

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 coverage is already 100%, so the baseline is 3, but the description adds real meaning for per_thread_limit: newest messages with full bodies, returned oldest first, default 50, cap 1000. The thread_id sourcing hint also aids interpretation beyond the schema text.

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?

States a specific verb+resource and, crucially, clarifies the tool returns structured data {thread_id, summary:{...}, messages} rather than generating summary prose. It distinguishes itself from search_messages and fetch_inbox by scope, so an agent can choose without opening sibling schemas.

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?

Explicitly routes the agent: find thread_id via search_messages or fetch_inbox, use search_messages for text matching, fetch_inbox to drain unread mail. Names both alternatives and the condition that selects each, leaving nothing to inference.

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