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mcp-coreclaw

activate_run_queue_items

Activate one or more waiting CoreClaw Run Queue items so they start executing.

WHEN TO USE: Use when the user previously queued runs via queue_worker_run and now wants to start them. 中文触发: 当用户要在 CoreClaw 中查询、运行、重跑、停止、导出或查看对应 worker/run/task 数据时使用。

WHEN NOT TO USE: Do not use public web search or code search for private CoreClaw platform data. Do not call excluded internal worker-version or internal-detail APIs.

RETURNS: JSON with results[]: per-item {queue_ref, success}.

WORKFLOW: Call after list_run_queue_items confirms items are in waiting status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queue_refsYesJSON array of queue item IDs to activate or release. Example: ["22","23"]. Obtain queue_ref values from list_run_queue_items.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only show all hints as false, providing minimal safety context. The description adds value by disclosing the return format (results[] with per-item queue_ref and success) and the workflow prerequisite (call after list_run_queue_items confirms waiting status). This gives useful behavioral context beyond annotations, though failure modes are not fully detailed.

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 well-organized with sections (WHEN TO USE, WHEN NOT TO USE, RETURNS, WORKFLOW) and each part serves a purpose. However, the Chinese trigger phrase is somewhat redundant and broad, adding unnecessary length and potential confusion.

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?

The description covers purpose, usage conditions, return format, and workflow, which is complete for a simple one-parameter tool. No output schema exists, but the RETURNS section compensates by describing the JSON structure.

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 schema already provides a detailed description for queue_refs, including example and how to obtain the values. The tool description adds no further parameter information, so it meets the baseline of 3 but does not exceed it.

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?

The first sentence, 'Activate one or more waiting CoreClaw Run Queue items so they start executing,' uses a specific verb and resource, clearly distinguishing it from siblings like list_run_queue_items or release_run_queue_items. This is a precise statement of the tool's function.

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?

Includes explicit 'WHEN TO USE' ('previously queued runs via queue_worker_run and now wants to start them') and 'WHEN NOT TO USE' sections. However, the Chinese trigger phrase broadens the context to any CoreClaw operation, which could confuse an agent, so it's not perfectly clear.

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

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TDQS

A3.7/5.0
Disambiguation3/5

Most tools follow a systematic scope pattern (user's last run, worker's last run, specific run), so intent is discernible, but the reversed word order (e.g., get_last_worker_run vs get_worker_last_run) makes many tools easy to conflate. Descriptions are thorough, yet the sheer number of near-identical names creates real misselection risk.

Naming Consistency3/5

Verbs and nouns are consistently snake_case, but the modifier order alternates unpredictably—some tools say last_worker_run, others worker_last_run—across abort/export/get/list/rerun groups. This inconsistency makes the set feel less coherent than a strict verb_noun pattern would.

Tool Count2/5

At 42 tools, the surface is heavily inflated by triplicating every run-related action across user-last, worker-last, and specific-run scopes. Many of these could be consolidated into a single tool with optional worker_id/run_id parameters, making the count feel excessive for the domain.

Completeness4/5

The surface covers the full lifecycle of workers, runs, tasks, queue, and account, including poll/verify/batch operations that go beyond basic CRUD. Minor gaps exist (e.g., no explicit run-input retrieval, no worker editing), but agents can achieve all common workflows without dead ends.

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