Agent skill

Conducty Debug

by robertbarclayy in robertbarclayy/conducty

Leverage-point analysis for failed prompts. An agent skill from robertbarclayy/conducty.

MITAuto-check passedDevelopment

Install Conducty Debug

skills CLI
$ npx skills add robertbarclayy/conducty --skill conducty-debug -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install robertbarclayy/conducty conducty-debug --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/robertbarclayy/conducty.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/conducty-debug .claude/skills/conducty-debug && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
conducty-debug
GitHub stars
176
Token cost
~1.9k tokens
SKILL.md length
908 words
Files
1
Skills in repo
20
Repo updated
First seen
Licence
MIT

At a glance

Leverage-point analysis for failed prompts. An agent skill from robertbarclayy/conducty.

  • Works in 4 steps: Classify the Failure → Investigate Root Cause → Hypothesis and Minimal Test → …
  • A prompt fails verification
  • SKILL.md covers The Leverage Hierarchy, The Four Phases, Circuit Breaker: 3 Retries and Pattern Library, plus 1 more section
  • Calls git

What it does

Conducty Debug is an agent skill from robertbarclayy/conducty. Leverage-point analysis for failed prompts. Determines whether the fix belongs at the plan, prompt, or code level before generating any fix. Use when a prompt fails verification, a checkpoint catches an issue, fix attempts aren't working, or the user says "debug", "why did this fail", "investigate".

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development. The repository describes itself as: Stop context-switching. Start batch-planning. Conducty replaces the fragmented cycle of plan → prompt → wait → get distracted → review → fix → repeat with advanced batch planning. The licence is MIT.

When your agent uses it

  • A prompt fails verification
  • A checkpoint catches an issue
  • Fix attempts arent working
  • The user says debug

Example prompts

  • “t working, or the user says”
  • “why did this fail”
  • “investigate”
  • “/conducty-debug”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Classify the Failure
  2. Investigate Root Cause
  3. Hypothesis and Minimal Test
  4. Generate the Fix

What it can do on your machine

Read from SKILL.md and the folder at commit 64aefd5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Conducty Debug loads about 1.9k tokens when it runs. Until then it costs about 79 tokens; SKILL.md has 908 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~79
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from robertbarclayy/conducty at commit 64aefd5, republished under its MIT licence (© robertbarclayy). 908 words, ~1,909 tokens.

Download SKILL.mdSave it as .claude/skills/conducty-debug/SKILL.md (or your agent's skills folder).
name
conducty-debug
description
Leverage-point analysis for failed prompts. Determines whether the fix belongs at the plan, prompt, or code level before generating any fix. Use when a prompt fails verification, a checkpoint catches an issue, fix attempts aren't working, or the user says "debug", "why did this fail", "investigate".
aliases
conducty-debug, debug
tags
conducty/skill, conducty/debug

Conducty Debug — Leverage Point Analysis

When something fails, the first question is not "what's wrong with the code?" It's "where is the highest leverage point to fix this?" A failure might be a code bug, a prompt quality problem, a plan assumption error, or a systemic issue affecting multiple prompts. Fixing at the wrong level wastes retries.

The Leverage Hierarchy

Fix at the highest level that applies:

Plan assumptions  →  fixes the most, prevents future failures
  ↓
Prompt quality    →  fixes this prompt and similar future prompts
  ↓
Code bug          →  fixes this specific failure only

Plan-level fix: The design was wrong, the acceptance criteria were incorrect, or the context was insufficient. A code fix won't help because the code was implementing the wrong thing correctly. Signal: the tracer failed, or multiple prompts in the same group fail for related reasons.

Prompt-level fix: The prompt was vague, missing context, had no no-go zones, or specified the wrong approach. The code did what the prompt said, but the prompt said the wrong thing. Signal: spec review passes but verification fails, or the implementer was BLOCKED/NEEDS_CONTEXT.

Code-level fix: The prompt was clear and correct, but the implementation had a bug. This is the only case where a traditional "fix the code" approach is appropriate. Signal: the failure is in specific logic, not in misunderstanding.

The Four Phases

Phase 1: Classify the Failure

Before doing anything else, determine the leverage point:

  1. Read the failure output carefully. What exactly failed? Not "tests fail" but which test, which assertion, what value.

  2. Compare failure against the prompt. Did the implementer build what the prompt asked for? If yes, the problem is the prompt or the plan, not the code. If no, it might be a code bug.

  3. Check if this is systemic. Are other prompts in the same group failing? Do they share assumptions, context, or dependencies? If 2+ prompts fail in the same group, suspect a plan-level issue before investigating individual code bugs.

  4. Classify:

    • Plan-level: Tracer failed, multiple related failures, design assumptions don't hold
    • Prompt-level: Agent was BLOCKED/NEEDS_CONTEXT, verification fails despite spec compliance, prompt smells visible in retrospect
    • Code-level: Clear implementation bug in otherwise well-specified work
Phase 2: Investigate Root Cause

Investigation depends on the leverage level. Use Read, Grep, Glob, and Bash (git diff, git log) to gather evidence — never guess.

For plan-level issues:

  • Re-read the design doc from [[conducty-shape]]. What assumption doesn't hold?
  • Check the project context file — is it stale or incomplete?
  • Was the complexity underestimated? Was the appetite realistic?
  • Would a different decomposition avoid this failure?

For prompt-level issues:

  • Check for prompt smells (see [[conducty-tdd]]): vague acceptance, missing context, mixed concerns, no verification, unbounded scope
  • Was the no-go zone clear enough? Did the agent creep outside scope?
  • Was the characterization step present for existing code modifications?
  • Would a different prompt structure have prevented this?

For code-level issues:

  • Read error messages and stack traces completely
  • Check what the prompt actually changed (git diff via Bash)
  • Trace data flow: where does the bad value originate? (Grep)
  • Find working examples of similar code in the same codebase
  • Compare what's different between working and broken
Phase 3: Hypothesis and Minimal Test
  1. Form a single hypothesis. "The root cause is X because Y." Be specific.
  2. Design the minimal verification. What's the smallest thing you can check to confirm or deny the hypothesis?
  3. Test it. One variable at a time. Don't fix multiple things at once.
  4. If wrong: Form a new hypothesis. Don't pile on fixes.
Show full SKILL.md (350 more words)Show less
Phase 4: Generate the Fix

The fix depends on the leverage level:

Plan-level fix:

  • Revise the design or plan assumptions
  • May require re-running [[conducty-shape]] for the affected goal
  • May require restructuring the group
  • Update the active plan note before generating new prompts

Prompt-level fix:

  • Rewrite the prompt with the missing context, clearer criteria, or better approach
  • Add the prompt smell that was missed to the improvement log
  • The fix prompt should reference the original failure: "This prompt failed because [root cause]. The rewritten version addresses this by [specific change]."

Code-level fix: Generate a root-cause-informed fix prompt:

markdown
Fix P{N}: {original description}

**Root cause**: {what was actually wrong, with evidence}
**Leverage point**: Code — the prompt was correct, the implementation had a bug

**What went wrong**: {the specific failure}

**Fix required**:
- {path/to/file} — {exact change needed and why}

**Do NOT**:
- {wrong fix that addresses the symptom}
- {scope creep that goes beyond the fix}

**Verification**: `{original verification}` AND confirm {specific fix evidence}

Circuit Breaker: 3 Retries

If a prompt has Retries >= 2 and this would be attempt #3:

STOP. Do not generate another fix.

This pattern indicates the fix is at the wrong leverage level. Three code-level fixes that don't work means the problem is at the prompt or plan level:

  • Each fix reveals new issues in different places → design assumption is wrong
  • Fixes require changes outside the prompt's scope → decomposition is wrong
  • Each fix creates new symptoms → the approach itself is flawed

Instead:

  1. Set Status to blocked
  2. Summarize: what was tried, what happened each time, what pattern you see
  3. Identify which higher leverage level the problem actually belongs to
  4. Present to the user with a recommendation: revise the design, split the prompt, or take a different approach entirely

Pattern Library

After resolving a failure, prepend an entry to [[Failure Patterns]] (the accumulating note in the vault — see [[conducty-obsidian]]):

markdown
### {YYYY-MM-DD HHmm} — {brief description}
- **Plan**: [[Plan YYYY-MM-DD HHmm Topic]]
- **Prompt**: see [[Prompt Log]] entry P{N}
- **Leverage point**: plan / prompt / code
- **Symptom**: {what the failure looked like}
- **Root cause**: {what was actually wrong}
- **Fix**: {what resolved it}
- **Prevention**: {what would prevent this in future prompts}

The pattern library is read by [[conducty-plan]] (Step 1) and [[conducty-improve]] to prevent repeat failures. A pattern that appears twice is a process gap, not bad luck. Prepend new entries (newest at top); never delete old ones.

Systemic Failure Detection

When investigating a single failure, also check for systemic issues:

  • 2+ failures in the same group with related symptoms → likely a shared assumption problem
  • Failures across groups in the same project → likely stale context or incorrect architecture understanding
  • Failures across projects → likely a prompt template problem

Systemic issues get plan-level or template-level fixes, not individual prompt fixes. Flag them for [[conducty-checkpoint]] and [[conducty-improve]].

© robertbarclayy, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/conducty-debug of robertbarclayy/conducty.

Open the folder on GitHubat commit 64aefd5

Compare with similar skills

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Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT
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Categories

Questions about Conducty Debug

What does Conducty Debug do?

Leverage-point analysis for failed prompts. An agent skill from robertbarclayy/conducty. Conducty Debug is an agent skill from robertbarclayy/conducty. Leverage-point analysis for failed prompts.

When should I use Conducty Debug?

Conducty Debug fits situations like: A prompt fails verification; A checkpoint catches an issue; fix attempts arent working; the user says debug.

How do I install Conducty Debug in Claude Code?

Run `npx skills add robertbarclayy/conducty --skill conducty-debug -a claude-code`. Or copy the skill folder (skills/conducty-debug in robertbarclayy/conducty) into .claude/skills/conducty-debug in your project. Claude Code loads it when a task matches its description.

How do I install Conducty Debug in Codex?

Run `npx skills add robertbarclayy/conducty --skill conducty-debug -a codex`. Or copy the skill folder (skills/conducty-debug in robertbarclayy/conducty) into .agents/skills/conducty-debug in your project. Codex loads it when a task matches its description.

Can I use Conducty Debug in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add robertbarclayy/conducty --skill conducty-debug -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/conducty-debug, .gemini/skills/conducty-debug, .github/skills/conducty-debug and .opencode/skills/conducty-debug in your project.

What does Conducty Debug need to run?

Going by SKILL.md and its folder, Conducty Debug needs the command-line tools its instructions call (git).

Does Conducty Debug access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Conducty Debug safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Conducty Debug use?

Conducty Debug is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Conducty Debug use?

About 1.9k tokens (SKILL.md is roughly 7.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Conducty Debug?

Skills that share tags, products or a category with Conducty Debug: Finishing a Development Branch (obra/superpowers, 296k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars), PR Babysitter (openinterpreter/openinterpreter, 69k stars) and Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Conducty Debug?

robertbarclayy (a GitHub user) maintains it in robertbarclayy/conducty, which has 176 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on June 19, 2026.

Source: robertbarclayy/conducty on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.