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Glama

mkt_run_queue

Execute multi-channel marketing queues with dry-run default; live runs require a human-reviewed plan or matching routine policy.

Instructions

执行一个队列(全渠道:email/hn/github/reddit/linkedin/x-reply)。默认 dry-run;go=true 实跑;UNVERIFIED 渠道首跑校准仅限人工 CLI 通道;实跑须已人审 plan,或显式 routine=true 且策略匹配(无 plan 的 adhoc 仅 CLI;授权管理不对 MCP 开放)。

Input Schema

NameRequiredDescriptionDefault
goNo
accountNo可选:覆盖队列顶层账号,供 routine policy 精确校验
routineNo仅使用已存在的 routine policy;MCP 不能创建或撤销授权
queue_pathYesdata/queues/<campaign>.json

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.13.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations supplied, the description carries the safety burden and does so well: it discloses the dry-run default, that go=true causes real side effects, and that a gated approval/policy path is required before anything is sent. It stops short of describing what a real run does per channel, how partial failures are handled, or whether runs are idempotent or rate-limited.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded and no clause is filler — every segment carries gating or permission information. However, it is delivered as a single dense chain of semicolon-separated clauses with nested parentheses, which makes it harder to scan than a short list of conditions would be.

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 mutating execution tool with no annotations and no output schema, the description covers the critical ground: default mode, the live-run switch, approval/policy preconditions, and what MCP is not allowed to do. Only return-value expectations and per-channel execution semantics are unaddressed, which is a modest gap.

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 75%, and the description still adds real meaning: go is framed as dry-run vs. live execution, routine is framed as 'use an existing policy only — MCP cannot create or revoke authorization'. queue_path and account are left to their schema descriptions, which is acceptable given their coverage.

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 — '执行一个队列' — and enumerates the channels it covers (email/hn/github/reddit/linkedin/x-reply), so the agent knows exactly what the tool operates on. It does not name any sibling tool to distinguish itself from near-neighbors like mkt_action or mkt_orchestrate, which keeps it 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 Guidelines5/5

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

Explicitly states the default mode (dry-run), the switch for real execution (go=true), and the precise preconditions for real execution: a human-reviewed plan, or explicit routine=true with a matching policy. It also gives hard exclusions — UNVERIFIED-channel calibration and plan-less adhoc runs are manual-CLI-only, and authorization management is not exposed to MCP. This is a full when/when-not specification.

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