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Detect Intrinsically Disordered Regions

detect_intrinsically_disordered
Read-onlyIdempotent

Identify intrinsically disordered regions in proteins using AlphaFold pLDDT scores, returning functional categories for clinical variant analysis.

Instructions

Map intrinsically disordered regions (IDRs) using pLDDT as proxy.

IDRs with pLDDT < 50 are predicted to be disordered in isolation by AlphaFold. This pLDDT-as-disorder-proxy approach is consistent with Ruff & Pappu (2021) and scales to the full human proteome from precomputed AlphaFold confidence.

IDR functional categories returned:

  • Linkers: short (< 20 aa) disordered regions between domains

  • Tails: N/C terminal IDRs

  • Long IDRs: candidate intrinsically disordered protein (IDP) segments

Clinical relevance:

  • IDRs are enriched for disease-causing mutations

  • IDRs host post-translational modification sites (phosphorylation, ubiquitination)

  • Long IDRs are emerging drug targets (targeted covalent inhibitors, phase separation modulators)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

The description adds significant behavioral context beyond annotations: the pLDDT proxy method, threshold <50, functional categories, and clinical relevance. Annotations already indicate read-only and idempotent, no contradiction. Could mention data source limitations.

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?

Well-structured with sections and bullet points. Some clinical relevance details may be secondary but do not significantly impair conciseness. Could be slightly shorter but efficiently organized.

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

Completeness4/5

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

Given the tool's complexity and existence of an output schema, the description covers purpose, method, output categories, and relevance. It does not explain the output schema format but that is handled by the schema itself. Sufficient for understanding.

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 0%, but the input schema itself describes the uniprot_id parameter with an example. The tool description does not add parameter details beyond what the schema provides, so baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool maps intrinsically disordered regions using pLDDT as proxy. It specifies the verb 'map' and resource 'IDRs', and distinguishes itself from siblings by focusing on disorder prediction, but does not explicitly contrast with other structural analysis tools.

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 for IDR detection with clinical relevance examples, but lacks explicit guidance on when to use this tool versus alternatives like analyze_structural_confidence. No 'when not to use' information is provided.

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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