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.
git clone --depth 1 https://github.com/Oriolshhh/runware-image-mcpWrote 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/rules/oriolshhh/runware-image-mcp/root-cause-debugging)<a href="https://agentmods.dev/rules/oriolshhh/runware-image-mcp/root-cause-debugging"><img src="https://agentmods.dev/badge/rules/oriolshhh/runware-image-mcp/root-cause-debugging/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/rules/oriolshhh/runware-image-mcp/root-cause-debugging"><img src="https://agentmods.dev/badge/rules/oriolshhh/runware-image-mcp/root-cause-debugging.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00010 | $0.00546 |
| Opus 5 | $0.00005 | $0.00273 |
| Sonnet 5 | $0.00002 | $0.00109 |
| Haiku 4.5 | $0.00001 | $0.00055 |
Grade A, and why
root-cause-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 5d 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: root-cause-debugging
Root-Cause Debugging
Purpose
Prevent guess-and-check patches by turning debugging into a bounded sequence of reproduction, isolation, falsification, correction, and verification.
When to use it
- Bugs, regressions, crashes, failing or flaky tests, races, data corruption, incorrect output, and unexpected performance changes.
- Any time the proposed fix precedes a demonstrated causal explanation.
Instructions
- Write expected versus observed behavior and capture the exact reproduction.
- Establish baseline frequency and environment; distinguish deterministic, intermittent, and environment-dependent failures.
- Minimize the reproducer and locate the narrowest failing boundary.
- Build an evidence ledger with four columns: observation, hypothesis, discriminating experiment, result.
- Rank hypotheses and test one at a time. Predict both supporting and rejecting results before the experiment.
- Once evidence supports a root cause, write a regression test at the lowest stable layer that exposes the causal behavior.
- Apply the minimal fix; rerun the original reproducer, regression, neighboring tests, and configured gates.
- Count each reproduce→investigate→experiment→fix→verify pass as one iteration
and obey the current
debug-loop.max_iterationsvalue.
Output format
A concise debug report: symptom, reproduction, environment, evidence ledger, root cause, rejected hypotheses, fix, regression test, iteration count, exact verification results, residual risk, and next experiment if unresolved.
Anti-patterns
- Editing before reproducing.
- Treating the first plausible explanation as proven.
- Combining multiple speculative changes in one experiment.
- Adding sleeps/retries without explaining the underlying timing or reliability issue.
- Weakening tests or suppressing errors to produce green output.
- Continuing beyond the configured iteration limit.
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.
- 5d ago First seen · 59 lines · 10 tokens per session scan A d1959bb77b01
root-cause-debugging is a cursor rule published in the GitHub repository Oriolshhh/runware-image-mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 10 tokens to every session and 546 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 2026-09-03.
Other cursor rules, from other repositories
running-tests
How to run tests, check for failures, and rerun specific failing tests — use the :agent variants of slow commands.
debug
Bug diagnosis and fixing standards - root cause analysis, minimal fixes, regression tests.
nodebench-auto-qa
Auto-QA after code changes using NodeBench MCP tools.
monitor-valgrind-cpp-linter-gate
Plan-close gate — Valgrind Memcheck make check and full-tree clang-format/clang-tidy (no git hooks).
005-code-quality
Logging, error envelopes, testing coverage, performance conventions.
monitor-debug-shm
DEBUG /dev/shm full-message mirror — security, gating, and tests.