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/dineshdb/pie/debuggingnpx skills add dineshdb/pie --skill debugginggit clone --depth 1 https://github.com/dineshdb/pieWhat 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 | $0.00015 | $0.00496 |
| Opus 5 | $0.00008 | $0.00248 |
| Sonnet 5 | $0.00003 | $0.00099 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
debugging 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 yesterday.
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.
What it actually says
Debugging
Iron Law: NO FIXES WITHOUT ROOT CAUSE INVESTIGATION.
Phase 1: Root Cause
Before any fix:
- Read error completely — stack traces, line numbers, error codes
- Reproduce consistently — exact steps to trigger
- Check recent changes —
git diff, new deps, config changes - Trace data flow — where does the bad value originate?
Multi-component tracing:
# Trace a value through the stack
grep -rn "VARIABLE_NAME" src/
git log --oneline -10 # recent changes
git diff HEAD~3 -- src/module/ # what changed recently
Stack trace when lost:
import traceback; traceback.print_stack()
# or in Rust: println!("{:?}", std::backtrace::Backtrace::capture());
Phase 2: Pattern Analysis
- Find working examples in codebase:
grep -rn "working_pattern" src/ - Read reference implementation completely
- Identify ALL differences between working and broken
- Understand dependencies and assumptions
Phase 3: Hypothesis
- State: "I think X is root cause because Y"
- Make SMALLEST possible change
- Test ONE variable at a time
- If 3+ fixes failed → question architecture
Phase 4: Implement + Defense-in-Depth
- Create failing test case
- Implement single fix (no "while I'm here" changes)
- Verify fix works using
verificationskill - Add validation at every layer:
| Layer | Purpose |
|---|---|
| Entry | Reject invalid input at boundary |
| Business Logic | Ensure data makes sense for operation |
| Environment | Prevent dangerous operations in context |
| Debug | Capture context for forensics |
Red Flags — STOP
- "Quick fix for now"
- "Just try changing X"
- "Add multiple changes at once"
- "I don't fully understand but this might work"
- One more fix (when 2+ already failed)
All mean: Return to Phase 1. If 3+ failed → question architecture.
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.
- yesterday First seen · 71 lines · 15 tokens per session scan A 9175187dd1a1
debugging is a skill published in the GitHub repository dineshdb/pie (2 stars, last pushed 3mo ago), licensed MIT. It adds 15 tokens to every session and 496 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 2026-08-31.
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