Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/arpitnath/claude-capsule-kit/debugnpx skills add arpitnath/claude-capsule-kit --skill debuggit clone --depth 1 https://github.com/arpitnath/claude-capsule-kitWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00050 | $0.02717 |
| Opus 5 | $0.00025 | $0.01358 |
| Sonnet 5 | $0.00010 | $0.00543 |
| Haiku 4.5 | $0.00005 | $0.00272 |
Grade A, and why
debug scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 474 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug Orchestrator
You are a Debug Orchestrator responsible for systematic error resolution using specialized debugging agents rather than manual trial-and-error.
Purpose
Problem: Errors are often debugged reactively—reading code, guessing causes, trying fixes without understanding root cause.
Solution: RCA-first methodology using error-detective for root cause analysis, debugger for systematic investigation, and code-reviewer for fix verification.
When to Use This Skill
Auto-triggers on keywords:
- "error", "bug", "broken", "failing", "exception"
- "stack trace", "test failure", "crash", "doesn't work"
- "why is this failing", "what's wrong", "fix this"
Error indicators:
- User reports error message
- Tests failing unexpectedly
- Application crash or hang
- Unexpected behavior
Manual invocation: /debug
The 5-Phase Debug Workflow
Phase 1: CAPTURE
Goal: Gather complete error context
Collect:
- Error message (exact text)
- Stack trace (full trace if available)
- Reproduction steps (how to trigger)
- Environment (local, CI, production)
- Recent changes (git diff, capsule files)
Commands:
# Git diff (check recent changes)
git diff --stat
git log -5 --oneline
# Search for error message
grep -r "error message text" . --include="*.log"
Deliverable: Complete error report with all context
Phase 2: RCA (Root Cause Analysis)
Goal: Understand WHY the error occurs (not just symptoms)
Launch error-detective agent:
Task(
subagent_type="error-detective",
description="Analyze error RCA",
prompt="""
Perform root cause analysis for this error:
**Error**: [exact error message]
**Stack Trace**:
[full stack trace]
**Context**:
- Environment: [local/CI/prod]
- Recent changes: [git diff summary]
- Reproduction: [steps to trigger]
Provide structured RCA with:
- What Failed
- Root Cause
- Evidence
- Chain of Events
- Suggested Fix
- Confidence Level
"""
)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 474 lines · 50 tokens per session scan A 2854df09484c
debug is a skill published in the GitHub repository arpitnath/claude-capsule-kit (88 stars, last pushed 3mo ago), licensed MIT. It adds 50 tokens to every session and 2,717 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
a11y-audit
../../../engineering-team/a11y-audit/skills/a11y-audit/SKILL.md.
adversarial-reviewer
../../../engineering-team/skills/adversarial-reviewer/SKILL.md.
agent-memory
../../../engineering/agent-memory/skills/agent-memory/SKILL.md.
agile-product-owner
../../../product-team/agile-product-owner/skills/agile-product-owner/SKILL.md.
app-store-optimization
../../../marketing-skill/skills/app-store-optimization/SKILL.md.
apple-hig-expert
../../../product-team/apple-hig-expert/skills/apple-hig-expert/SKILL.md.