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node_dependencies

Compare a ComfyUI node pack's Python dependency requirements against the installed venv to report satisfied, missing, or mismatched packages. Read-only—no installation or changes.

Instructions

Report a custom node pack's Python dependency requirements vs the installed venv (read-only).

Wraps comfy node deps. Separate from nodes (that reads live object_info; this reads the venv's pip list) — nothing is installed or changed.

Args: pack: an INSTALLED pack name; omit for every pack (larger payload). registry_id: a NOT-yet-installed registry pack to pre-check (latest published version). Additive with pack — both yields two rows, keyed by (pack, registry), to compare installed vs. published.

Each row carries a status (satisfied/mismatch/missing/unparseable/ unknown). May return {"error", "unsupported": True} instead of the payload on a comfy-cli predating this verb.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packNo
registry_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations present, the description carries the full burden and does so well: it declares the operation read-only, states no installation or changes occur, describes the returned row statuses, and warns about an error/unsupported payload on older comfy-cli versions.

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 front-loaded with the core purpose, then uses terse labeled sections for context and args. Every sentence contributes either scope, usage guidance, parameter meaning, or output behavior with no filler.

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?

Given the simple two-optional-parameter surface and no output schema, the description covers the essential context: what the tool reads, how parameters affect scope, the shape of per-row statuses, and a possible error return. An agent has enough to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It does robustly: 'pack' is explained as an installed pack name with omission behavior, and 'registry_id' is explained as a not-yet-installed registry pack pre-check, including the additive behavior when both are supplied.

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 verb 'Report' and a specific resource: a custom node pack's Python dependency requirements versus the installed venv. It also explicitly contrasts itself with the sibling tool 'nodes', making its unique role unambiguous.

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?

The description provides solid context by explaining the difference from 'nodes' (live object_info vs pip list) and stating that nothing is installed or changed. It does not explicitly mention alternatives like 'workflow_deps' or 'install_node', but the read-only scope and parameter guidance are clear enough for most selection cases.

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