Skip to main content
Glama

Get the current engagement

get_engagement

Retrieve stored engagement records in your preferred format: request complete raw JSON, or Markdown tables that automatically trim to top rows for large datasets, with options to display all rows or set a custom limit.

Instructions

保存されているエンゲージメントの内容を返す。format="json" を指定すると生の JSON を全件返す。Markdown では登録件数が多いと各表を上位のみに自動で絞り(切った旨と全件の見方を必ず表示)、compact=false で全件、limit で件数を変えられる。 / Return the stored engagement; pass format="json" for the complete raw JSON. In Markdown, large engagements have each table trimmed to its top rows automatically (always saying so and how to see the rest); pass compact=false for every row or limit to change how many.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNo出力言語 / Output languageboth
limitNo1 表あたりの件数(既定 20、compact=true なら 5)。指定でその件数に絞る / Rows per table (default 20; 5 when compact=true).
formatNo出力形式 / Output formatmarkdown
compactNo各表を上位のみに絞る。未指定なら多いときだけ自動、false で全件 / Trim each table to its top rows; omit for automatic, false for every row.
Install Server

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does substantial work: it discloses that Markdown output is automatically trimmed for large engagements, states that format='json' returns the complete raw JSON, and explains how compact and limit override/control trimming. This is meaningful non-obvious behavior beyond the schema.

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 front-loaded with the core action and then details formatting behavior. It is relatively dense and bilingual, but the extra length is justified by the tool's non-trivial output behavior and the bilingual audience.

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 low-complexity retrieval tool with no required parameters and no output schema, the description covers the main behavioral context: output format, trimming behavior, and row-count controls. It does not explain what 'the engagement' contains or error cases, but the essentials for calling and interpreting results are present.

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 description coverage is 100%, so the baseline is 3, but the description adds value by explaining behavior tied to parameters: format='json' yields complete raw JSON, compact=false shows every row, and limit changes the row count. This goes beyond the schema's per-parameter descriptions.

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 uses a clear verb and resource: '保存されているエンゲージメントの内容を返す' / 'Return the stored engagement'. It is distinguishable from list_engagements and other engagement tools by focusing on the current/stored engagement, though it does not explicitly name any sibling alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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

The description gives useful within-tool guidance for format, compact, and limit options, but it provides no guidance on when to choose this tool versus siblings like list_engagements, switch_engagement, or check_engagement_health. No alternatives or exclusions are mentioned.

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

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Waganawa-Megumin/togaf10_EAP_MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server