design_backbone

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose the return shape ('output_pdb' as PDB text) and documents all inputs, but says nothing about runtime/GPU cost, determinism or seeding, or failure modes (e.g. invalid contig strings) — notable omissions for a diffusion-model tool.

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?

Structured as a purpose line followed by Args and Returns sections, with the core purpose front-loaded. No filler sentences; the argument lines are dense but each earns its place. Trailing whitespace/minor formatting is the only blemish.

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?

An output schema exists, so explaining return values is optional (though harmless here). Inputs and purpose are well covered for a 3-parameter tool, but the absence of any guidance on pipeline position relative to the sibling design/fold tools and the absence of runtime or determinism context leave it only minimally adequate for a specialized diffusion 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 description coverage is 0%, so the description must compensate, and it does: all three parameters are given meaning plus concrete examples ('A1-100/0 50-60' for contigs, ['A59','A83'] for hotspot_res). It stops short of explaining contig mini-language rules or expected PDB formatting, but the added value over the bare schema is substantial.

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?

Names a specific verb and resource ('Design a protein backbone') and names the engine (RFdiffusion), which is concrete. It does not explicitly distinguish itself from siblings like design_sequences, design_binder, or fold_complex, so an agent must infer the boundary from 'backbone' vs. 'sequences'/'binder'.

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 explains what the arguments mean but never states when to choose this tool over design_binder or design_sequences, nor any prerequisites (e.g. that this is the first stage of a design pipeline). Usage is only weakly implied by the hotspot_res description mentioning a 'binder'.

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