How do I install the Council Verify skill?

Run npx skillmds add majiayu000/council-verify in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Council Verify safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Council Verify?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Council Verify free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under Apache-2.

Who published Council Verify?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Council Verify by majiayu000 — Agent Skill

Name: Council Verify
Rating: 4.2 (5 reviews)
Author: majiayu000

Council Verify

Verify code, documents, or implementation against requirements using LLM Council multi-model deliberation. Use when you need multi-model consensus on correctness, completeness, or quality. Keywords: verify, check, validate, review, approve, pass/fail, consensus, multi-model

majiayu000 3872ccc 2 files · 3.1 KB Updated Sep 9, 2026 567 repo stars

File contents

Council Verification Skill

Use LLM Council's multi-model deliberation to verify work with structured, machine-actionable verdicts.

When to Use

Verify code changes before committing
Validate implementation against requirements
Check documents for accuracy and completeness
Get multi-model consensus on quality

Workflow

Capture Snapshot: Capture current git diff or file state (snapshot pinning for reproducibility)
Invoke Verification: Call mcp:llm-council/verify with isolated context
Receive Verdict: Get structured JSON with verdict, confidence, and blocking issues
Audit Trail: Persist transcript via mcp:llm-council/audit

Parameters

Parameter	Type	Default	Description
`rubric_focus`	string	null	Focus area: "Security", "Performance", "Accessibility"
`confidence_threshold`	float	0.7	Minimum confidence for PASS verdict
`snapshot_id`	string	required	Git commit SHA for reproducibility

Output Schema

{
  "verdict": "pass|fail|unclear",
  "confidence": 0.85,
  "rubric_scores": {
    "accuracy": 8.5,
    "completeness": 7.0,
    "clarity": 9.0,
    "conciseness": 8.0
  },
  "blocking_issues": [...],
  "rationale": "Chairman synthesis...",
  "transcript_location": ".council/logs/..."
}

Exit Codes (for CI/CD)

0: PASS - Approved with confidence >= threshold
1: FAIL - Rejected
2: UNCLEAR - Confidence below threshold, requires human review

Example Usage

# Verify current changes
council-verify --snapshot $(git rev-parse HEAD) --rubric-focus Security

# Verify specific files
council-verify --target-paths "src/auth.py,src/api.py" --snapshot abc123

Progressive Disclosure

Level 1: This metadata (~200 tokens)
Level 2: Full instructions above (~600 tokens)
Level 3: See references/rubrics.md for detailed rubric definitions

Related Skills

council-review: Code review with structured feedback
council-gate: CI/CD quality gate

---name: council-verifydescription: Verify code, documents, or implementation against requirements using LLM Council multi-model deliberation. Use when you need multi-model consensus on correctness, completeness, or quality. Keywords: verify, check, validate, review, approve, pass/fail, consensus, multi-modellicense: Apache-2.0--- # Council Verification Skill Use LLM Council's multi-model deliberation to verify work with structured, machine-actionable verdicts. ## When to Use - Verify code changes before committing - Validate implementation against requirements - Check documents for accuracy and completeness - Get multi-model consensus on quality ## Workflow 1. **Capture Snapshot**: Capture current git diff or file state (snapshot pinning for reproducibility) 2. **Invoke Verification**: Call `mcp:llm-council/verify` with isolated context 3. **Receive Verdict**: Get structured JSON with verdict, confidence, and blocking issues 4. **Audit Trail**: Persist transcript via `mcp:llm-council/audit` ## Parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `rubric_focus` | string | null | Focus area: "Security", "Performance", "Accessibility" | | `confidence_threshold` | float | 0.7 | Minimum confidence for PASS verdict | | `snapshot_id` | string | required | Git commit SHA for reproducibility | ## Output Schema ```json { "verdict": "pass|fail|unclear", "confidence": 0.85, "rubric_scores": { "accuracy": 8.5, "completeness": 7.0, "clarity": 9.0, "conciseness": 8.0 }, "blocking_issues": [...], "rationale": "Chairman synthesis...", "transcript_location": ".council/logs/..." } ``` ## Exit Codes (for CI/CD) - `0`: PASS - Approved with confidence >= threshold - `1`: FAIL - Rejected - `2`: UNCLEAR - Confidence below threshold, requires human review ## Example Usage ```bash # Verify current changes council-verify --snapshot $(git rev-parse HEAD) --rubric-focus Security # Verify specific files council-verify --target-paths "src/auth.py,src/api.py" --snapshot abc123 ``` ## Progressive Disclosure - **Level 1**: This metadata (~200 tokens) - **Level 2**: Full instructions above (~600 tokens) - **Level 3**: See `references/rubrics.md` for detailed rubric definitions ## Related Skills - `council-review`: Code review with structured feedback - `council-gate`: CI/CD quality gate

Frequently asked questions