mikeng-io/agent-skills/deep-verify
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Checking that the SKILL.md file is still in the repository.
Generic multi-agent verification framework with balanced expert analysis. Model-agnostic and domain-agnostic - verify any work through expert analysis.
Install
npx vskill@latest install mikeng-io/agent-skills/deep-verifySKILL.md
Deep Verify: Multi-Agent Verification Framework
Execute this skill to verify work through balanced expert analysis.
Execution Instructions
When invoked, you will:
- Resolve scope and context — invoke context skill (always), then preflight if confidence is low
- Populate verification scope from working_scope
- Generate expert agents based on the extracted context:
- Always spawn: Devil's Advocate, Integration Checker, Third-Party Reviewer
- Dynamically spawn domain experts based on detected domains
Domain expert selection via domain-registry: Read domain-registry/domains/*.md to match signals from working_scope. Minimum: 1 domain expert. No maximum.
- Aggregate findings from all experts with proper weighting
- Generate and save report to
.outputs/verification/
Dependency Check
Before executing any step, verify all required skills are present:
Where [skills-root] is the parent of this skill's directory. Resolve with ls ../ from this skill's location.
If any required file is missing → stop immediately and output:
All dependencies present → proceed to Step 0.
Step 0: Scope & Context Resolution
Context (always required):
Invoke Skill("context") first. It classifies the artifact, detects domains from domain-registry, and determines routing confidence:
Preflight (conditional — triggered by context confidence):
Invoke Skill("preflight") only if context_report.confidence == "low" OR one or more signals remain unresolved:
- Artifact is not clearly identified
- User's intent is unclear (what are we verifying?)
- Domains could not be detected
- Concerns or risks to verify are not stated
Preflight fills exactly the gaps context could not resolve (max 3 questions, one at a time):
If context_report.confidence == "high" → skip preflight entirely.
Merge into working scope:
Use working_scope throughout this skill.
Step 1: Populate Verification Scope
Using working_scope from Step 0, extract the verification context:
Step 2: Spawn Expert Agents
Spawn experts with dependency-aware execution for optimal analysis quality. Domain experts analyze first, then invariant experts use those findings.
Dependency-Aware Execution Strategy:
Verification has natural dependencies:
- Integration Checker needs domain findings to assess cross-system impact
- Devil's Advocate is more effective challenging concrete domain findings
- Third-Party Reviewer benefits from seeing complete analysis
Task Definitions with Dependencies:
Why This Order Matters:
- Domain experts first - Gather domain-specific findings and concerns
- Integration and critique together - Integration Checker assesses impact, Devil's Advocate challenges assumptions, both using domain findings
- Fresh eyes last - Third-Party Reviewer sees complete picture including domain analysis, integration impact, and challenges
Performance Benefit:
- Improves analysis quality - critics have concrete findings to work with
- Still maintains parallelism where possible (Wave 2 runs 2 tasks in parallel)
- Sequential where dependencies matter (Wave 3 needs everything)
Invariant Experts (Always Spawn)
Expert 1: Devil's Advocate
Expert 2: Integration Checker
Expert 3: Third-Party Reviewer
Domain Experts (Spawn Based on Conversation)
For each domain detected in the conversation, generate a domain expert prompt:
Spawn domain experts for each unique domain detected. Examples:
- "authentication" discussed → Spawn Security Expert
- "Figma design" mentioned → Spawn Design Expert
- "email campaign" discussed → Spawn Marketing Expert
- "policy update" discussed → Spawn HR/Legal Expert
Any domain can be detected - analyze the conversation and spawn appropriate experts.
Step 3: Aggregate Findings
After all experts complete, aggregate their findings:
Determine Verdict
- FAIL: Critical risks or blocking issues found
- CONCERNS: High risks identified
- PASS: No significant issues
Build Summary Table
| Dimension | Result | |
|---|---|---|
| Domain Correctness | ✅ PASS / ⚠️ CONCERNS | |
| Risk Assessment | Based on Devil's Advocate findings | |
| Integration Impact | Based on Integration Checker findings |
Step 4: Generate Report
Generate a markdown report with this structure:
Step 5: Validate Output Format
Before finalizing the report, validate it against the required format specification to ensure consistency.
Validation Gate
Spawn an output validator sub-agent using the Task tool:
This is the start of the file. Read the full SKILL.md on GitHub.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/deep-verify/SKILL.md
Popularity
- Repository stars
- 6
- 7-day trend score
- 10
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 23 Mar 2026, 7 months ago.
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