read_pack_workflow

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

No annotations provided, so description carries full burden. It discloses name validation (no path traversal) and that it returns a ready workflow.json graph. Could mention output format or error handling, but overall transparent.

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?

Two sentences plus a parenthetical, all front-loaded with purpose. Every sentence earns its place: purpose, usage guidance, and parameter context. No fluff.

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?

Given one parameter and no output schema, the description provides sufficient context: what the tool returns, how to use it, and validation. Could mention error behavior, but overall complete for a simple read tool.

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 100% with a description, but the description adds valuable context: 'a directory under packs/, e.g. 'krea2-txt2img-manual'. Get valid names from list_packs.' This enhances understanding.

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+resource: 'Return a bundled pack's ready workflow.json graph by pack name'. It distinguishes from siblings by specifying it's the 'EXPERT graph for that model family' and contrasts with inventing from scratch.

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?

Explicitly states when to use: 'use it as the source of truth when setting up the family on the user's canvas' and 'prefer this over inventing a graph from scratch'. It also directs to list_packs to get valid names.

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