Chalk Labs
Need help deploying debug-council?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/michaelboeding-debug-council
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: research
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/debug-council
What's inside
- Skill name
debug-council- Description
- Research-aligned self-consistency for debugging. Spawns independent solver agents that each explore and debug the problem from scratch. Uses majority voting. Based on "Self-Consistency Improves Chain of Thought Reasoning" (Wang et al., 2022). Use for critical bugs, algorithms, or when other approaches have failed.
- License
- MIT
- Instructions
- 264 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Debug Council: Research-Aligned Self-Consistency
Pure implementation of self-consistency (Wang et al., 2022). Each agent receives the **raw user prompt** and explores/debugs **independently**. No pre-processing, no shared context. Majority voting selects the answer.
**Use this for bugs and problems with ONE correct answer.**
## Step 0: Ask User How Many Agents
Before doing anything else, **ask the user how many solver agents to use**:
```
How many debug agents would you like me to use? (3-10)
Recommendations:
- 3 agents: Faster, still reliable
- 5 agents: Good balance
- 7 agents: High confidence
- 10 agents: Maximum confidence (critical bugs)
Note: Each agent will independently explore the codebase and find the bug.
This takes longer but provides true independence per the research.
```
Wait for the user's response. If they specified a number (e.g., "debug council of 5"), use that.
**Minimum: 3 agents** | **Maximum: 10 agents**
---
## CRITICAL: Pure Research Alignment
### What This Means
1. **NO orchestrator exploration** - Do NOT read files or gather context before spawning agents
2. **Raw user prompt to all agents** - Each agent gets the user's original request, unchanged
3. **Each agent explores independently** - Agents discover the codebase themselves
4. **True independence** - No shared context, no cross-contamination
### Why This Matters
The research shows that **independent samples** converge on correct answers. If we pre-process or share context, we:
- Introduce orchestrator bias
- Reduce independence
- May miss what individual agents would discover
---
## Workflow
### Step 1: Capture the Raw User Prompt
Take the user's request **exactly as stated**. Do NOT:
- ❌ Read files first
- ❌ Explore the codebase
- ❌ Add context
- ❌ Rephrase or enhance the prompt
Just capture what the user said.
### Step 2: Spawn Agents IN PARALLEL with RAW PROMPT
Spawn ALL agents simultaneously. Each gets the **exact same raw prompt**:
```
Task(agent: "debug-solver-1", prompt: "[USER'S EXACT WORDS]")
Task(agent: "debug-solver-2", prompt: "[USER'S EXACT WORDS]")
Task(agent: "debug-solver-3", prompt: "[USER'S EXACT WORDS]")
... (all in the SAME batch - parallel execution)
```
**DO NOT modify the prompt. DO NOT add context. Raw user words only.**
### Step 3: Agents Work Independently
Each agent will:
1. Read and understand the user's request
2. Explore the codebase using their tools (Read, Grep, Glob, LS)
3. Identify the root cause
4. Reason through solutions (chain-of-thought)
5. Generate a complete fix
**Each agent works in complete isolation** - they cannot see what other agents are doing or have found.
### Step 4: Track Progress & Collect Solutions
As agents complete, **show progress to the user**:
```
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
AGENT PROGRESS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
☑ Agent 1 - Complete
☑ Agent 2 - Complete
☑ Agent 3 - Complete
☐ Agent 4 - Working...
☐ Agent 5 - Working...
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
```
Update this display as each agent finishes. When all complete:
```
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
AGENT PROGRESS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
☑ Agent 1 - Complete ✓
☑ Agent 2 - Complete ✓
☑ Agent 3 - Complete ✓
☑ Agent 4 - Complete ✓
☑ Agent 5 - Complete ✓
All agents finished! Analyzing solutions...
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
```
Collect all outputs for voting.
### Step 5: Majority VotingFrom michaelboeding/skills, MIT.
More from michaelboeding/skills
- 0.656score
expired-patent-scout
michaelboeding
Find recently expired patents relevant to specified brands, products, or technology areas and develop evidence-backed product opportunity leads.
SkillAFreshness: A★ 30Claude Code +9 - 0.656score
search-trend-product-scout
michaelboeding
Discover and rank product ideas in a category using search trends, customer problems, and competing products.
SkillAFreshness: A★ 30Claude Code +9 - 0.656score
mobile-parity-check
michaelboeding
Compare the UI and UX of iOS and Android apps in either direction.
SkillAFreshness: A★ 30Claude Code +9 - 0.616score
chart-generation
michaelboeding
Use this skill for generating data-driven charts and visualizations using Python.
SkillBFreshness: B★ 30Claude Code +9 - 0.501score
patent-lawyer-agent
michaelboeding
Use this skill for intellectual property guidance, prior art research, patent strategy, and drafting patent applications.
SkillDFreshness: D★ 30Claude Code +9 - 0.501score
auto-permissions-review-install
michaelboeding
Install an AI-powered permission review hook that uses Claude Haiku to evaluate tool call safety before execution.
SkillDFreshness: D★ 30Claude Code +9 - 0.501score
patent-prosecution-agent
michaelboeding
Use this skill for responding to patent office actions, examiner rejections, and patent prosecution.
SkillDFreshness: D★ 30Claude Code +9 - 0.501score
cmo-agent
michaelboeding
AI Chief Marketing Officer that analyzes your website and deploys autonomous marketing agents across SEO, content, Reddit, Hacker News, X/Twitter, and AI…
SkillDFreshness: D★ 30Claude Code +9 - 0.501score
icon-generation
michaelboeding
Generate app icons with transparent backgrounds.
SkillDFreshness: D★ 30Claude Code +9 - 0.501score
brand-research-agent
michaelboeding
Use this skill to analyze a brand from their website before creating content.
SkillDFreshness: D★ 30Claude Code +9 - 0.501score
image-generation
michaelboeding
Use this skill for any image-related AI generation or editing task.
SkillDFreshness: D★ 30Claude Code +9 - 0.501score
music-generation
michaelboeding
Use this skill for AI music generation.
SkillDFreshness: D★ 30Claude Code +9
Signals
- Stars
- 30
- Forks
- 2
- Open issues
- 0
- Last commit (this folder)
- Dec 31, 2025 (10 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/michaelboeding/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from michaelboeding
- 0.656score
expired-patent-scout
michaelboeding
Find recently expired patents relevant to specified brands, products, or technology areas and develop evidence-backed product opportunity leads.
SkillAFreshness: A★ 30Claude Code +9 - 0.656score
mobile-parity-check
michaelboeding
Compare the UI and UX of iOS and Android apps in either direction.
SkillAFreshness: A★ 30Claude Code +9 - 0.656score
search-trend-product-scout
michaelboeding
Discover and rank product ideas in a category using search trends, customer problems, and competing products.
SkillAFreshness: A★ 30Claude Code +9 - 0.616score
chart-generation
michaelboeding
Use this skill for generating data-driven charts and visualizations using Python.
SkillBFreshness: B★ 30Claude Code +9 - 0.501score
auto-permissions-review-install
michaelboeding
Install an AI-powered permission review hook that uses Claude Haiku to evaluate tool call safety before execution.
SkillDFreshness: D★ 30Claude Code +9 - 0.501score
brand-research-agent
michaelboeding
Use this skill to analyze a brand from their website before creating content.
SkillDFreshness: D★ 30Claude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get debug-council running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
debug-council skill. Agent Mart. https://agentmart.dev/skills/michaelboeding-debug-council (last updated 2026-10-24)