Skip to main content
Glama
zai-one

arsenkin-mcp

by zai-one

arsenkin_export_result

Export a saved job as JSONL or CSV with JSON-pointer provenance, avoiding provider calls. Retrieve bounded results for analysis or integration.

Instructions

Export a saved owned job as bounded JSONL/CSV with JSON-pointer provenance; no provider calls.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNojsonl
job_idYes
max_rowsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.2.0

TDQS

A4/5.0
Behavior3/5

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

Since no annotations are provided, the description carries the transparency burden. It adds useful behavioral facts: no provider calls, bounded output, and eligibility limited to saved owned jobs. However, it never explicitly says the operation is read-only/side-effect-free or what happens when the job is not saved/owned, leaving some safety behavior unstated.

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?

A single dense sentence with no filler. The key action is front-loaded, and every clause adds discriminative information.

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?

An output schema exists, so return structure is covered. The description supplies the key operational context: eligible jobs, output formats, provenance behavior, and the no-provider-call guarantee. The main omissions are explicit parameter mapping and a named comparison to get_result, which are relatively minor for this simple export 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?

Schema description coverage is 0%, so the prose has to compensate. It indirectly maps job_id (the job to export), format ('JSONL/CSV'), and max_rows ('bounded'), but it does not explicitly explain accepted format values or how max_rows limits the export. The parameter names are self-explanatory, but the description adds only partial detail.

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 names a specific action ('Export'), a specific resource ('a saved owned job'), and concrete output characteristics ('bounded JSONL/CSV with JSON-pointer provenance'). It also distinguishes the tool from siblings by noting it makes 'no provider calls', so an agent can separate it from get_result or submit.

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?

It gives clear context: only saved owned jobs are eligible and the operation is offline ('no provider calls'), which implies it should not be used for live provider results. It does not explicitly name a sibling alternative or state when not to use it, so it misses a 5.

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

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/zai-one/arsenkin-mcp'

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