check_dependencies
Generate dependency map showing which files each PM2 process requires. Returns dependency-map.json content.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Generate dependency map showing which files each PM2 process requires. Returns dependency-map.json content.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint, idempotentHint, and destructiveHint. The description adds that the tool 'Returns dependency-map.json content', which is consistent but adds minimal behavioral context beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence efficiently conveys the tool's action, output, and scope. No extraneous words, earning its place fully.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless, read-only tool with annotations, the description adequately covers behavior and return value. Lack of output schema is compensated by specifying the returned content ('dependency-map.json'), though more detail on format could be added.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so schema coverage is 100%. The description correctly implies no input is needed, meeting the baseline without the need for parameter explanations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Generate dependency map' specifying the verb and resource. It further clarifies the scope to PM2 processes and file dependencies, distinguishing it from sibling tools like check_page_changes or check_session_diff.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use or avoid this tool versus alternatives. While the purpose is clear, there is no guidance on context or exclusions, leaving the agent to infer usage from the tool name and sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, but there is some overlap among multiple audit/check tools (e.g., accountability_check, drift_audit, security_audit). However, descriptions and naming help differentiate their specific scopes, so ambiguity is low.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., check_archive_safety, propagate_family_member), making them predictable and easy to understand.
33 tools is on the high side, but the server covers a broad domain (system health, audits, propagation, session management, etc.). The count is justified by the comprehensive scope, though it may feel heavy for agents.
The tool set covers the entire lifecycle of system management: health monitoring, audits, propagation, sessions, compliance, and more. No obvious gaps for the stated purpose of a nervous system framework.