Orihime

find_repo_dependencies

Identify all direct repository dependencies of a given repository by its logical name.

Instructions

Find all repositories that the given repository directly depends on.

Args:
    repo_name: The logical name of the repository as indexed (e.g. ``point-bank-bff``).

Returns:
    List of dicts with key ``name`` for each dependency repo.
    Empty list if the repo is not found or has no declared dependencies.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "repo_name": "<repo_name>"
    },
    "name": "find_repo_dependencies"
  }
}

Input Schema

Name	Required	Description	Default
`repo_name`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0May 8, 2026

TDQS

A4.3/5.0

Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns a list of dicts with a 'name' key, and handles missing repos or no dependencies gracefully by returning an empty list. It does not mention side effects, permissions, or rate limits, but for a read-only operation this is sufficient.

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 concise with two short sections: one for the main purpose and one for arguments/returns. Every sentence adds value, there is no fluff, and the key information is front-loaded.

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?

For a tool with a single parameter and an output schema (implied by 'has output schema: true'), the description fully explains the return format and edge cases (empty list for not found or no dependencies). No further context is needed for an agent to invoke it correctly.

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?

The sole parameter 'repo_name' has zero schema description coverage, but the description adds meaning by saying 'The logical name of the repository as indexed' and providing an example ('point-bank-bff'). This goes beyond the schema's 'Repo Name' title and clarifies what kind of name is expected.

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 clearly states the tool finds all repositories that the given repository directly depends on. It uses a specific verb ('find') and resource ('repositories that the given repository directly depends on'), and the name differentiates it from siblings like 'find_callers' and 'find_callees'.

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

Usage Guidelines3/5

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

The description explains what the tool does but does not explicitly state when to use it versus alternatives like 'find_callees' or 'find_cascade_risk'. It mentions that an empty list is returned if the repo is not found or has no dependencies, which provides some context on outcomes, but lacks when-not-to-use guidance.

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