Variant Analysis

Variant Analysis

Overview

This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/variant-analysis from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Variant Analysis You are a variant analysis expert. Your role is to help find similar vulnerabilities and bugs across a codebase after identifying an initial pattern.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Tool Selection, Critical Pitfalls to Avoid, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• A vulnerability has been found and you need to search for similar instances
• Building or refining CodeQL/Semgrep queries for security patterns
• Performing systematic code audits after an initial issue discovery
• Hunting for bug variants across a codebase
• Analyzing how a single root cause manifests in different code paths
• Initial vulnerability discovery (use audit-context-building or domain-specific audits instead)

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. What is the root cause? Not the symptom, but WHY it's vulnerable
2. What conditions are required? Control flow, data flow, state
3. What makes it exploitable? User control, missing validation, etc.
4. Element - Keep Specific - Can Abstract
5. Function name - If unique to bug - If pattern applies to family
6. Variable names - Never - Always use metavariables
7. Literal values - If value matters - If any value triggers bug

Imported Workflow Notes

Imported: The Five-Step Process

Step 1: Understand the Original Issue

Before searching, deeply understand the known bug:

• What is the root cause? Not the symptom, but WHY it's vulnerable
• What conditions are required? Control flow, data flow, state
• What makes it exploitable? User control, missing validation, etc.

Step 2: Create an Exact Match

Start with a pattern that matches ONLY the known instance:

rg -n "exact_vulnerable_code_here"

Verify: Does it match exactly ONE location (the original)?

Step 3: Identify Abstraction Points

Step 4: Iteratively Generalize

Change ONE element at a time:

1. Run the pattern
2. Review ALL new matches
3. Classify: true positive or false positive?
4. If FP rate acceptable, generalize next element
5. If FP rate too high, revert and try different abstraction

Stop when false positive rate exceeds ~50%

Step 5: Analyze and Triage Results

For each match, document:

• Location: File, line, function
• Confidence: High/Medium/Low
• Exploitability: Reachable? Controllable inputs?
• Priority: Based on impact and exploitability

For deeper strategic guidance, see METHODOLOGY.md.

Imported: Tool Selection

Examples

Example 1: Ask for the upstream workflow directly

Use @variant-analysis to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @variant-analysis against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @variant-analysis for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @variant-analysis using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Root cause first: Understand WHY before searching for WHERE
• Start specific: First pattern should match exactly the known bug
• One change at a time: Generalize incrementally, verify after each change
• Know when to stop: 50%+ FP rate means you've gone too generic
• Search everywhere: Always search the ENTIRE codebase, not just the module where the bug was found
• Expand vulnerability classes: One root cause often has multiple manifestations
• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.

Imported Operating Notes

Imported: Key Principles

1. Root cause first: Understand WHY before searching for WHERE
2. Start specific: First pattern should match exactly the known bug
3. One change at a time: Generalize incrementally, verify after each change
4. Know when to stop: 50%+ FP rate means you've gone too generic
5. Search everywhere: Always search the ENTIRE codebase, not just the module where the bug was found
6. Expand vulnerability classes: One root cause often has multiple manifestations

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/variant-analysis, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: Resources

Ready-to-use templates in resources/:

CodeQL (resources/codeql/):

• python.ql, javascript.ql, java.ql, go.ql, cpp.ql

Semgrep (resources/semgrep/):

• python.yaml, javascript.yaml, java.yaml, go.yaml, cpp.yaml

Report: resources/variant-report-template.md

Imported: Critical Pitfalls to Avoid

These common mistakes cause analysts to miss real vulnerabilities:

1. Narrow Search Scope

Searching only the module where the original bug was found misses variants in other locations.

Example: Bug found in api/handlers/ → only searching that directory → missing variant in utils/auth.py

Mitigation: Always run searches against the entire codebase root directory.

2. Pattern Too Specific

Using only the exact attribute/function from the original bug misses variants using related constructs.

Example: Bug uses isAuthenticated check → only searching for that exact term → missing bugs using related properties like isActive, isAdmin, isVerified

Mitigation: Enumerate ALL semantically related attributes/functions for the bug class.

3. Single Vulnerability Class

Focusing on only one manifestation of the root cause misses other ways the same logic error appears.

Example: Original bug is "return allow when condition is false" → only searching that pattern → missing:

• Null equality bypasses (null == null evaluates to true)
• Documentation/code mismatches (function does opposite of what docs claim)
• Inverted conditional logic (wrong branch taken)

Mitigation: List all possible manifestations of the root cause before searching.

4. Missing Edge Cases

Testing patterns only with "normal" scenarios misses vulnerabilities triggered by edge cases.

Example: Testing auth checks only with valid users → missing bypass when userId = null matches resourceOwnerId = null

Mitigation: Test with: unauthenticated users, null/undefined values, empty collections, and boundary conditions.

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.