graphite_list_nodesLists every node identifier recognized by the pinned graphene-cli; optionally filter by case-sensitive substring. Helps you find valid node names for authored node-graph procedural graphics.
List every node identifier the pinned graphene-cli understands (exits cleanly; cached in memory after the first call). Optional filter: case-sensitive substring match.
| Name | Required | Description | Default |
|---|---|---|---|
| filter | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses that the command exits cleanly and is cached in memory after the first call, and explains the filter behavior (case-sensitive substring). However, it does not mention return format, error handling, or permission requirements. These gaps are moderate for a read-only list operation.
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 states the core purpose first, then adds behavioral details and parameter info without redundancy. Every clause earns its place.
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 simple list tool with one optional parameter and no output schema, the description covers purpose, parameter behavior, and some operational characteristics. It lacks return type details, but these are not essential for a basic enumeration tool. Overall it is adequately complete.
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?
Schema coverage is 0%, so the description must explain the parameter. It does so effectively: 'Optional filter: case-sensitive substring match' clarifies the parameter's name, optionality, and matching semantics. This adds substantial value beyond the bare schema.
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 the verb 'List' and the resource 'every node identifier the pinned graphene-cli understands'. It distinguishes itself from sibling tools (render, validate, render_variants) by describing a listing operation, making its purpose unambiguous.
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?
No explicit guidance on when to use this tool versus alternatives. It does not mention when not to use it or suggest a sibling for other needs. Usage is only implied by the description's content, not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.