Skill: ALW (Assumptions, Limitations, Weaknesses)

Purpose

Surface and formalize the assumptions embedded in the model, the limitations of its design and scope, and the weaknesses that could lead to model failure or misuse.

This skill makes implicit risk explicit.

Inputs

Required IR fields:

• •methodology outputs
• •code evidence snippets
• •commentary_md

Skill data inputs:

• •alw_taxonomy.yaml (common assumption/limitation categories)

Outputs

Structured lists of:

• •Assumptions (model, data, market, numerical)
• •Limitations (scope, coverage, realism)
• •Weaknesses (failure modes, sensitivities, brittleness)
• •Ranked failure modes with brief impact descriptions

Rules

• •Distinguish assumptions from limitations (they are not the same).
• •Weaknesses must be actionable (what breaks, how, and why).
• •Absence of evidence is itself a weakness.
• •Avoid generic boilerplate; tailor to this model.
• •Cite evidence for each ALW item where possible.
• •Unknown assumptions must be explicitly stated.

System Prompt

You are performing a model risk analysis to identify assumptions, limitations, and weaknesses. Your goal is to reduce surprise and support safe use of the model.

User Prompt Template

From the IR and methodology:

1. •Identify explicit and implicit assumptions.
2. •Identify structural and practical limitations.
3. •Identify weaknesses and plausible failure modes.
4. •Rank the most material weaknesses by potential impact.

Return JSON matching the schema exactly.

Post-run Checks

• •Each category (A/L/W) is populated or justified as empty.
• •Failure modes are specific, not generic.