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Glama

start_meeting

Start a live meeting with a chosen agent (CFO, FP&A, etc.) by specifying an agenda. Receive a meeting ID to continue the conversation, enabling multi-agent collaboration across LLM providers.

Instructions

Start a meeting with an agent. Returns a meeting ID for follow-up messages. Use this to begin a synchronous conversation with another agent (CFO, FP&A, Product, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentYesAgent identifier or path to prompt file. Examples: "cfo", "fpa", "product"
modelNoModel id. Defaults: claude-opus-5 (anthropic), gpt-5.6-luna (openai), zai-org/GLM-5.3 (together), qwen/qwen3-235b-a22b-instruct-2507 (replicate), qwen3:14b (ollama), default (openai_compatible). Anthropic also accepts the aliases "opus" (claude-opus-5) and "sonnet" (claude-sonnet-5). Replicate accepts owner/name, owner/name:version, or a https://replicate.com/owner/name URL.
agendaYesThe topic, question, or task to discuss with the agent.
contextNoOptional additional context, document content, or data to share.
base_urlNoOnly with provider "openai_compatible": base URL of an OpenAI-compatible /v1 endpoint (e.g. http://localhost:1234/v1). Overrides OPENAI_COMPATIBLE_BASE_URL for this session/call. OPENAI_COMPATIBLE_API_KEY, if set, is sent as the bearer token to whichever base URL is used.
providerNoLLM provider to use. Default: anthropic. Options: anthropic; openai; together (Together AI — any Together model id, e.g. zai-org/GLM-5.3 or Qwen/...); replicate (owner/name, owner/name:version, or https://replicate.com/owner/name); ollama (local, only when reachable); openai_compatible (any /v1/chat/completions server — set OPENAI_COMPATIBLE_BASE_URL or pass base_url).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

There are no annotations, so the description carries the full burden. It does disclose the main behavioral contract: a meeting is started, the conversation is synchronous, and a meeting ID is returned for follow-up. It does not mention side effects, costs, authentication requirements, how long the meeting persists, or how it is terminated, but it is not misleading and provides the most essential behavioral facts.

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?

The description is two sentences with no filler. The first sentence states action and return value, and the second gives usage guidance with concrete agent examples. Every sentence earns its place, and the most important information is front-loaded.

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 creation tool with no annotations and no output schema, the description gives the critical information: it starts a meeting and returns a meeting ID for follow-up. The schema covers all optional provider/model parameters, and the required parameters (agent, agenda) are intuitive. It does not explain how to continue or end the meeting, but the sibling tools (say, end_meeting, list_meetings) make that discoverable, so nothing essential is missing for invoking this tool.

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?

The input schema already describes all 6 parameters with detailed explanations, examples, and defaults, so schema coverage is complete and the baseline is 3. The description adds only a slightly different set of agent examples ('CFO, FP&A, Product') that mostly repeats what the schema gives. It does not materially enrich parameter understanding beyond the schema.

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 names the exact action ('start a meeting'), the object of that action ('another agent'), and the key outcome ('returns a meeting ID for follow-up messages'). It also gives concrete audience examples (CFO, FP&A, Product), so an agent can tell what this tool operates on. It does not explicitly contrast itself with sibling tools like start_local_meeting or start_collaboration, so it misses the top mark.

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?

The description states when to use the tool: 'Use this to begin a synchronous conversation with another agent.' This gives clear context and implies it is the entry point for ongoing meetings rather than one-off calls. However, it offers no exclusions or explicit alternatives, leaving an agent to infer when not to use it relative to collaboration and local-meeting siblings.

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