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jfrog_list_path

Read-onlyIdempotent

List files and folders in a JFrog repository path to inspect artifacts and directories without modifying anything.

Instructions

List files and folders under one JFrog repository path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoRepository-relative path using forward slashes. Omit, empty string, '.', or '/' for the repository root; '..', backslashes, raw URLs, and control characters are rejected.
depthNoTraversal depth. Defaults by tool and is capped by the configured JFROG_MAX_DEPTH value.
limitNoMaximum number of results to return. Values below 1 are rejected; values above the configured server limit are clamped.
cursorNoOpaque cursor returned by a previous response. Do not parse or construct cursor values client-side.
repo_keyYesJFrog repository key, for example libs-release-local. Raw URLs, path separators, and control characters are rejected.
include_foldersNoWhether folder entries should be included in the response.
include_timestampsNoWhether storage-list responses should request metadata timestamps when the Artifactory instance supports that mode.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. However, the description adds no behavioral details such as pagination via cursor, depth defaults, or that it uses the storage-list API. This is a minimal 'list' description that contributes little beyond the annotations.

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 a single, concise sentence that directly states the tool's purpose with no fluff or repetition. It is front-loaded and immediately informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 parameters incl. cursor/depth/limit, output schema, and annotations), the description is only minimally viable. The schema and annotations fill in many details, but the description lacks an overview of pagination, configurable options, or overall behavior, making it just adequate.

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%, and each parameter has a thorough description (e.g., path accepts root forms, limit clamping, cursor opacity). The description itself adds nothing about parameters, so the baseline of 3 applies—schema does the heavy lifting.

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 states a specific action ('List') and a clear resource ('files and folders under one JFrog repository path'). This distinguishes it from siblings like jfrog_list_repositories and jfrog_get_tree, though it doesn't specify whether the listing is recursive or immediate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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

No guidance is given on when to use this tool versus alternatives such as jfrog_get_tree or jfrog_find_files. There are no exclusions or context about typical use cases, leaving the agent to infer from the name alone.

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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