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/synaptiai/synapti-marketplace/debugging-patternsnpx skills add synaptiai/synapti-marketplace --skill debugging-patternsgit clone --depth 1 https://github.com/synaptiai/synapti-marketplaceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/synaptiai/synapti-marketplace/debugging-patterns)<a href="https://agentmods.dev/skills/synaptiai/synapti-marketplace/debugging-patterns"><img src="https://agentmods.dev/badge/skills/synaptiai/synapti-marketplace/debugging-patterns.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00090 | $0.01441 |
| Opus 5 | $0.00045 | $0.00720 |
| Sonnet 5 | $0.00018 | $0.00288 |
| Haiku 4.5 | $0.00009 | $0.00144 |
Grade A, and why
debugging-patterns 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.
How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debugging Patterns
Domain skill for structured investigation of bugs and unexpected behavior.
Iron Law
ALWAYS FIND ROOT CAUSE BEFORE ATTEMPTING FIXES. Symptom fixes are failure.
A fix that doesn't address root cause creates a new bug later. Every. Single. Time.
Four-Phase Investigation
1. Gather Evidence
Collect before theorizing:
# Error logs, stack traces, recent changes
git log --oneline -10
git diff HEAD~3..HEAD --stat
- Read error messages and stack traces FULLY — don't skim
- Check logs in chronological order around the failure
- Note what changed recently (
git log,git diff) - Reproduce the error — if you can't reproduce it, you can't verify the fix
2. Pattern Analysis
Look for patterns in the evidence:
- When does it fail vs succeed? (inputs, timing, environment)
- What's different between working and broken states?
- Is the error consistent or intermittent?
- Use
Grepto find similar patterns: error messages, function calls, data flows
3. Hypothesis Testing
Form and test hypotheses systematically. Use TaskCreate for each hypothesis:
TaskCreate("Hypothesis 1: {theory}", "Confidence: High\nTest: {specific test}\nEvidence: {what points here}")
TaskCreate("Hypothesis 2: {theory}", "Confidence: Medium\nTest: {specific test}\nEvidence: {what points here}")
TaskCreate("Hypothesis 3: {theory}", "Confidence: Low\nTest: {specific test}\nEvidence: {what points here}")
| # | Hypothesis | Confidence | Test | Result |
|---|---|---|---|---|
| 1 | {theory} | High/Med/Low | {specific test} | {outcome} |
| 2 | {theory} | High/Med/Low | {specific test} | {outcome} |
| 3 | {theory} | High/Med/Low | {specific test} | {outcome} |
For each hypothesis: TaskUpdate(status: "in_progress") before testing, TaskUpdate(status: "completed") after — whether confirmed or disproven. Record the result.
Rules:
- Maximum 3 hypotheses at a time (more means insufficient evidence — go back to phase 1)
- Test highest confidence first
- Test ONE at a time — never change two things simultaneously
- A disproven hypothesis is progress, not failure
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 · 138 lines · 90 tokens per session scan A a841847094a0
debugging-patterns is a skill published in the GitHub repository synaptiai/synapti-marketplace (6 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 90 tokens to every session and 1,441 once invoked, about $0.0005 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 2026-09-03.
Other skills, from other repositories
create-or-update-concepts
Scan and analyze the project codebase to create or update concept files in agents-context/concepts/ (organized by domains/, source/, shared/) and update the README index and Load-When Cheatsheet.
step2-scope-tasks
Break a specification into ordered task groups with explicit context-awareness directives.
step1-write-spec
Gather requirements through structured Q&A, then formalize into a specification document.
configure-project
Configure lead-dev-os framework in your project — sets up agents-context, specs directory, and CLAUDE.md.
create-pr
Creates a GitHub Pull Request on the current branch with a description focused on WHAT changed (not HOW). Uses emojis in the title and description. Use when the user asks to create a PR, open a pull request, or submit changes for review. Triggers on mentions of PR, pull request, merge request, or code review.
step4-archive-spec
Archive a completed spec — moves it to specs-archived and blocks agent access.