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util_chainbow

Apply a rainbow gradient to protein chains to visually distinguish them, recoloring all or selected chains.

Instructions

Colors chains in rainbow gradient (CHAINs in rainBOW)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
selectionNoWhat to recolour. Defaults to everything.all

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only states the effect. It does not mention whether existing colors are overwritten, how the selection parameter affects the outcome, or what 'rainbow gradient' means in practice (e.g., per-chain coloring). This leaves significant behavioral ambiguity for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short and front-loaded with the essential action. The parenthetical '(CHAINs in rainBOW)' is a stylistic pun that adds no factual information, slightly reducing efficiency, but overall the description remains appropriately concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one optional parameter with full schema coverage and an output schema), the description is minimally viable. However, it lacks behavioral context (e.g., how selection is applied, whether it affects all chains or only current selection) and does not differentiate from similar sibling tools, making it complete only at a basic level.

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

Parameters3/5

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

Schema description coverage is 100% for the single 'selection' parameter, which is already documented as 'What to recolour. Defaults to everything.' The tool description adds no additional parameter semantics, so it meets the baseline of 3 but does not exceed it.

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 'Colors chains in rainbow gradient' uses a specific verb ('colors'), resource ('chains'), and effect ('rainbow gradient'), clearly distinguishing it from general coloring tools like 'color' and 'spectrum' by targeting chains specifically. The parenthetical pun reinforces the tool name without adding ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage ('colors chains') but provides no explicit guidance on when to use this tool versus alternatives such as 'spectrum' or 'util_rainbow'. There is no mention of prerequisites, exclusions, or conditions, so it relies on the reader inferring context from the purpose.

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

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