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mcp-coreclaw

rerun_worker_run

Rerun a specific CoreClaw worker run with the same saved inputs.

WHEN TO USE: Use when the user wants to retry or repeat a known run id. 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 a new run_slug or synchronous result fields.

WORKFLOW: Follow with get_worker_run or list_worker_run_results for the new run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoResult limit. Example: 20. Must be 1-100. (default: 20)
offsetNoPage number, 1-based. offset=1 is page 1; offset=0 is accepted as page 1. (default: 1)
run_idYesWorker run identifier. Example: "01KKDXV2G26BT7NH4ZQR2R4NPZ". Obtain from run_worker, list_worker_runs, or get_last_worker_run.
is_asyncNoWhether CoreClaw should run asynchronously. Example: true. Use false only for small synchronous runs. (default: true)
callback_urlNoCallback URL for asynchronous status updates. Example: "https://client.example.com/openapi/callback". (optional)

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate a non-read-only, non-idempotent operation. The description adds meaningful context: reruns use 'same saved inputs,' returns a 'new run_slug or synchronous result fields,' and suggests follow-up actions. It doesn't detail side effects like resource consumption, but the annotations lower the burden and the description adds sufficient value.

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 clear sections. It is appropriately sized but includes a broad Chinese trigger phrase that catches many unrelated actions. Still, every section earns its place and the structure is effective.

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?

Given no output schema, the description provides return information and a workflow. It covers the essential use case. Minor gaps exist: the meaning of 'synchronous result fields' and the relevance of limit/offset are not explained, but the schema already describes parameters thoroughly.

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?

Schema description coverage is 100%, so the schema fully documents all parameters. The description does not add parameter-specific insight beyond mentioning 'same saved inputs,' but the baseline of 3 applies because the schema carries the heavy lifting.

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 description states 'Rerun a specific CoreClaw worker run with the same saved inputs,' which is a specific verb + resource + scope. It distinguishes from sibling rerun tools like rerun_last_worker_run by emphasizing 'specific' and 'known run id.'

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?

Explicit WHEN TO USE and WHEN NOT TO USE sections provide clear context. It mentions retrying/repeating a known run id and gives a follow-up workflow with get_worker_run or list_worker_run_results. Exclusions are stated (no public web search for private data).

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.

Resources