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 rules/golid-ai/golid/audit-bugsgit clone --depth 1 https://github.com/golid-ai/golidWrote 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/golid-ai/golid/audit-bugs)<a href="https://agentmods.dev/rules/golid-ai/golid/audit-bugs"><img src="https://agentmods.dev/badge/rules/golid-ai/golid/audit-bugs.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 | $0.00019 | $0.02311 |
| Opus 5 | $0.00010 | $0.01156 |
| Sonnet 5 | $0.00004 | $0.00462 |
| Haiku 4.5 | $0.00002 | $0.00231 |
Grade A, and why
audit-bugs 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bug Audit Checklist
Thesis: Run this checklist against any file or module being reviewed. Each item references a real bug found in this codebase.
When to Run
Use workflow-routing first when the user asks for review/audit depth or when
the diff crosses T2/T3 triggers; this checklist is scoped by that tier.
Two trigger points, not just one:
- Pre-merge gate — before declaring a card/feature "done", run the relevant section of this checklist against every file you touched. ~20% of recent commits are post-hoc audit cleanup; running this proactively converts those into the original commit. This is the highest-ROI use.
- On demand — when explicitly asked to audit, review for bugs, or grade code quality.
The checklist below is the same for both; only the trigger differs.
Evidence Requirements
A finding isn't "audited" until you've produced one of:
- File path + function name + line range for the offending pattern (e.g.,
service/feature/feature.go::Create lines 45-52). rgcommand + match count for codebase-wide patterns (e.g.,rg "_ = pool\.Exec" -g '*.go' | wc -l → 3 hits).- "Verified clean" with the search you ran, when no instances exist (e.g.,
rg "createResource" frontend/ → 0 hits).
"Looks fine" is not an audit result. If you can't cite the search, you didn't run it.
Core patterns (apperror, parameterized SQL, batch(), Switch/Match, createResource, alive guard) — see codebase-standards. Frontend fetch — solidjs-data-fetching. Route UI — solidjs-pages.
Audit Strategy
A single audit pass catches ~60-70% of real issues. Each pass has blind spots due to which files get read first, which patterns the search focuses on, and attention saturation on large codebases. To maximize coverage:
- Run multiple independent passes with different focus areas — e.g., one pass for reactive patterns, one for auth/security, one for config consistency, one for the fork/rename story. Narrow scope finds more than broad sweeps.
- Vary the search strategy — don't just follow this checklist. Grep for known anti-patterns (
return () =>in.tsx,_ =in.go,anyin component props). Read files the checklist doesn't mention (entry-server.tsx, rename tool, CI config, env files). - Check reference implementations are textbook-perfect —
app.tsx,login/index.tsx,dashboard/index.tsx, andsettings/index.tsxare copied by the scaffold tool and by AI assistants. A bug in these propagates everywhere. - Verify the tool chain, not just the code — rename tool, scaffold templates, deploy scripts, and CI config can have bugs that downstream users inherit silently.
- After fixing issues, re-read the fixed files — fixes can introduce new problems (e.g., a rename tool step that corrupts URLs by naively replacing project names inside domain strings).
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 · 111 lines · 19 tokens per session scan A 31c2740d72f7
audit-bugs is a cursor rule published in the GitHub repository golid-ai/golid (40 stars, last pushed 2mo ago), licensed MIT. It adds 19 tokens to every session and 2,311 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 cursor rules, from other repositories
adapter-features
Database-specific features must be implemented in the specialized adapter only. Base adapters (postgres, mysql, etc.) must remain database-agnostic.
unit-tests-tdd
TDD required for behavior changes; ≥80% package coverage on touched packages; unit-test conventions.
integration-tests
Human-readable integration test requests; helpers vs httptest; suites/ vs per-DB placement.
state-management
Use the following stack. Do not introduce or recommend Redux or React Context for shared/global state.
backend
You are an expert in Go, Gin, Gorm, Gen, Cosy (https://cosy.uozi.org/) with a deep understanding of best practices and performance optimization techniques in these technologies.
core
Core token-efficiency and response discipline rules. Always active.