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 skills add martinffx/atelier --skill oracle-debuggit clone --depth 1 https://github.com/martinffx/atelierWrote 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/martinffx/atelier/oracle-debug)<a href="https://agentmods.dev/skills/martinffx/atelier/oracle-debug"><img src="https://agentmods.dev/badge/skills/martinffx/atelier/oracle-debug/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/martinffx/atelier/oracle-debug"><img src="https://agentmods.dev/badge/skills/martinffx/atelier/oracle-debug.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00056 | $0.02170 |
| Opus 5.5 | $0.00022 | $0.00868 |
| Sonnet 5.5 | $0.00011 | $0.00434 |
| Haiku 4.5 | $0.00006 | $0.00217 |
Grade A, and why
oracle-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 10d 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 — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Oracle Debug
Random fixes waste time and create new bugs. Quick patches mask underlying issues.
Core principle: find root cause before a permanent corrective fix. Temporary containment is appropriate when needed to limit security, production, or data-loss impact.
Violating the letter of this process is violating the spirit of debugging.
The Iron Law
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
If you haven't completed Phase 1, you cannot propose fixes.
When to Use
Use for any technical issue:
- Test failures
- Bugs in production
- Unexpected behavior
- Performance regressions
- Build or integration failures
- Intermittent failures
Use this especially when:
- Under time pressure
- "Just one quick fix" seems obvious
- You've already tried multiple fixes
- The previous fix didn't work
- You don't fully understand the issue
The Four Phases
You must complete each phase before proceeding to the next.
Phase 1 — Root Cause Investigation
Before attempting any fix:
Use the project's domain glossary and ADRs to build a clear mental model of the relevant modules before tracing.
-
Read error messages carefully. Read the full stack trace, line numbers, file paths, and error codes. Don't skip warnings.
-
Build a fast feedback loop. If you don't have a fast, deterministic, pass/fail signal for the bug, no amount of code-reading will save you. Spend disproportionate effort here.
Try these in order:
- Failing test at the seam that reaches the bug
- Curl / HTTP script against a running dev server
- CLI invocation with fixture input
- Headless browser script (Playwright/Puppeteer)
- Replay a captured trace (network payload, event log)
- Throwaway harness (minimal subset of the system)
- Property/fuzz loop for "sometimes wrong" bugs
- Bisection harness (e.g.,
git bisect run) - Differential loop (old vs new version)
- HITL bash script (last resort — structure the human clicks)
Iterate on the loop: make it faster, sharper, and more deterministic. A 30-second flaky loop is barely better than no loop.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago Changed · +2 lines eb29077d25d0
- 1mo ago First seen · 226 lines · 56 tokens per session scan A fe3fbe8f6768
oracle-debug is a skill published in the GitHub repository martinffx/atelier (48 stars, last pushed yesterday), licensed MIT. It adds 56 tokens to every session and 2,170 once invoked, about $0.0002 per session on Opus 5.5. 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
omc-review
Evaluate finished work for defects, risk, and simplification before it ships.
verify
Verify that a change really works before you claim completion.
code-review
Reviews code for bugs, security issues, and best practices.
tech-debt-collector
Evidence-gated tech debt and bloat detection. Scouts signals, ranks by materiality, validates by refutation, reports up to 5 findings with actions.
doubt-driven-development
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production, security-sensitive logic, irreversible operations), or any time a confident output would be cheaper to verify now…
ralph
Self-referential loop until task completion with configurable verification reviewer.