ReddRadar
Agent skill
audit-sampling-calculator
Statistical and non-statistical audit sampling skill with sample size determination and evaluation
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/business/finance-accounting/skills/audit-sampling-calculator
Metadata
Additional technical details for this skill
- domain
- business
- shared
- YES
- category
- audit
- priority
- medium
- specialization
- finance-accounting
SKILL.md
Audit Sampling Calculator
Overview
The Audit Sampling Calculator skill provides comprehensive audit sampling capabilities for both statistical and non-statistical approaches. It supports sample size determination, selection, and evaluation across various audit contexts.
Capabilities
Attribute Sampling
- Sample size calculation
- Expected error rate input
- Tolerable deviation rate
- Confidence level selection
- Upper error limit calculation
- Pass/fail evaluation
Monetary Unit Sampling (MUS)
- Population stratification
- Sampling interval calculation
- Selection methodology
- Projected error calculation
- Upper error bound
- Tainting analysis
Classical Variables Sampling
- Mean-per-unit estimation
- Difference estimation
- Ratio estimation
- Standard deviation calculation
- Precision determination
- Confidence interval
Sample Size Calculation
- Risk model inputs
- Tolerable misstatement
- Expected misstatement
- Confidence factors
- Population characteristics
- Prior year results
Projection of Errors
- Known error projection
- Likely error calculation
- Sampling risk assessment
- Anomalous error treatment
- Extrapolation methods
- Documentation requirements
Confidence Level Analysis
- Risk of incorrect acceptance
- Risk of incorrect rejection
- Achieved precision
- Sample result evaluation
- Decision criteria
- Conclusion documentation
Usage
Substantive Testing Sample
Input: Population, materiality, risk assessment, expected error
Process: Calculate sample size, select items, project results
Output: Sample selection, projected misstatement, audit conclusion
Control Testing Sample
Input: Control population, tolerable rate, expected rate
Process: Determine sample, execute testing, evaluate results
Output: Upper deviation rate, control reliance conclusion
Integration
Used By Processes
- Internal Audit Planning and Execution
- SOX Compliance and Testing
- External Audit Coordination
Tools and Libraries
- IDEA
- ACL Analytics
- Statistical sampling libraries
- Audit workpaper platforms
Cross-Specialization Use
- QA Testing Automation
- Data Quality domains
Best Practices
- Document sampling methodology selection rationale
- Ensure random selection integrity
- Investigate all identified errors
- Consider qualitative factors in evaluation
- Maintain population completeness
- Archive sampling parameters for reference
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
a5c-ai/babysitter
gsd-tools
Central utility skill for GSD operations. Provides config parsing, slug generation, timestamps, path operations, and orchestrates calls to other specialized skills. Acts as the unified entry point that the original gsd-tools.cjs provided via its lib/ modules (commands, config, core, init).
a5c-ai/babysitter
model-profile-resolution
Resolve model profile (quality/balanced/budget) at orchestration start and map agents to specific models. Enables cost/quality tradeoffs by selecting appropriate AI models for each agent role.
a5c-ai/babysitter
verification-suite
Plan structure validation, phase completeness checks, reference integrity verification, and artifact existence confirmation. Provides the structured verification layer ensuring GSD artifacts are well-formed and complete.
a5c-ai/babysitter
state-management
STATE.md reading, writing, and field-level updates. Provides cross-session state persistence via .planning/STATE.md with structured fields for current task, completed phases, blockers, decisions, and quick tasks.
a5c-ai/babysitter
git-integration
Git commit patterns, formats, and conventions for GSD methodology. Provides atomic commits per task, structured commit messages, planning file commits, branch management, and milestone tag operations.
a5c-ai/babysitter
frontmatter-parsing
YAML frontmatter parsing and manipulation for .planning/ documents. Provides read, write, update, query, and validation operations on frontmatter blocks in GSD markdown artifacts.
Didn't find tool you were looking for?