guide-risk-precheck

name	guide_risk_precheck
description	Precheck biological and interpretation risks before selecting perturbation targets or guide designs.
category	bio/perturb_seq
version	1
requires_tools	["search_knowledge_base","evidence_review","ensembl_api","ncbi_eutils","python_repl"]
requires_network	true
user_invocable	true
tags	["guide","crispr","risk","precheck","perturbation"]
aliases	["perturbation_risk_precheck"]
species	any
modality	perturb_seq
stage	validation
stability	stable
safety_level	medium

Guide Risk Precheck

Purpose

Flag major biological and interpretation risks before the user commits to a perturbation target or downstream guide design workflow.

When to use

Use this skill when the user is considering targets for CRISPR, CRISPRi, CRISPRa, or Perturb-seq and wants an early warning on likely failure modes.

Required inputs

• targets: one or more target genes
• system: cell type, species, or model
• perturbation type (optional)

Steps

1. Restate the perturbation system, species, cell context, and target list; say clearly when those assumptions are missing.
2. Use search_knowledge_base for local design notes, prior screen guidance, or target-specific warnings.
3. Use ensembl_api and ncbi_eutils to check gene structure, isoform complexity, prior perturbation context, and biologically plausible failure modes.
4. When public evidence is central to the risk call, run evidence_review on the target-plus-system question so supported concerns are separated from speculation.
5. Use python_repl to build a compact risk table when comparing multiple targets.
6. Return risks as warnings or hypotheses, not as definitive design failures, and recommend the next validation step before committing to guide design.

Output format

• Biological context or assumptions: species, cell state, perturbation mode, and any inferred system assumptions.
• Evidence or source basis: which search_knowledge_base, ensembl_api, ncbi_eutils, and evidence_review findings support the warning.
• Risk table: Target | Risk type | Why it matters | Support level
• Caveats or ambiguity: sparse literature, system mismatch, or unresolved biological uncertainty.
• Recommended next step: what to validate experimentally or computationally before guide selection.

Failure modes

• Very sparse literature: say the precheck is preliminary and avoid overconfident ranking.
• Too little system context: ask the user for cell type, species, or perturbation mode.
• Many targets: summarize the highest-risk ones first and note that the rest need a secondary pass.

Examples

• "Precheck risks for TOX, NR4A1, and BATF before a Perturb-seq experiment."
• "What could go wrong if I target MYC in activated T cells?"