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/adrielp/ai-engineering-harness/debugnpx skills add adrielp/ai-engineering-harness --skill debuggit clone --depth 1 https://github.com/adrielp/ai-engineering-harnessWhat 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 | $0.00018 | $0.00567 |
| Opus 5 | $0.00009 | $0.00283 |
| Sonnet 5 | $0.00004 | $0.00113 |
| Haiku 4.5 | $0.00002 | $0.00057 |
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 3d 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug
You are tasked with helping debug issues during manual testing or implementation. This command allows you to investigate problems by examining logs, state, and git history without editing files.
Initial Response
When invoked WITH a context file:
I'll help debug issues with [file name]. Let me understand the current state.
What specific problem are you encountering?
- What were you trying to test/implement?
- What went wrong?
- Any error messages?
I'll investigate the logs, state, and git history to help figure out what's happening.
When invoked WITHOUT parameters:
I'll help debug your current issue.
Please describe what's going wrong:
- What are you working on?
- What specific problem occurred?
- When did it last work?
I can investigate logs, state, and recent changes to help identify the issue.
Process Steps
Step 1: Understand the Problem
- Read any provided context (plan or ticket file)
- Quick state check:
- Current git branch and recent commits
- Any uncommitted changes
Step 2: Investigate the Issue
Spawn parallel Task agents:
Task 1 - Check Recent Logs:
Find and analyze logs for errors
Return: Key errors/warnings with timestamps
Task 2 - Application State:
Check the current application state
Return: Relevant state findings
Task 3 - Git and File State:
Understand what changed recently
Return: Git state and any file issues
Step 3: Present Findings
## Debug Report
### What's Wrong
[Clear statement of the issue]
### Evidence Found
**From Logs**:
- [Error/warning with timestamp]
**From Application State**:
- [Finding from state]
**From Git/Files**:
- [Recent changes that might be related]
### Root Cause
[Most likely explanation]
### Next Steps
1. **Try This First**:
```bash
[Specific command or action]
- If That Doesn't Work:
- [Alternative approach]
Can't Access?
Some issues might be outside my reach:
- Browser console errors
- External service state
- System-level issues
Would you like me to investigate something specific further?
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.
- 3d ago First seen · 117 lines · 18 tokens per session scan A d3ae9e87e555
debug is a skill published in the GitHub repository adrielp/ai-engineering-harness (20 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 18 tokens to every session and 567 once invoked, about $0.0001 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…