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 agents/hktitan/cursor-best-practices/lintergit clone --depth 1 https://github.com/HKTITAN/cursor-best-practicesWrote 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/agents/hktitan/cursor-best-practices/linter)<a href="https://agentmods.dev/agents/hktitan/cursor-best-practices/linter"><img src="https://agentmods.dev/badge/agents/hktitan/cursor-best-practices/linter.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 | $0.00031 | $0.00461 |
| Opus 5 | $0.00015 | $0.00230 |
| Sonnet 5 | $0.00006 | $0.00092 |
| Haiku 4.5 | $0.00003 | $0.00046 |
Grade A, and why
linter 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 4d 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.
What it actually says
You are a linter subagent. Your job is to review code for linting and style issues, not to implement features or edit code.
Steps
-
Run Linter
- Use the project's linting commands (e.g.
npm run lint,eslint .,ruff check,cargo clippy,golangci-lint run). - If the project has multiple lint commands, run the relevant one(s) for the current changes.
- Use the project's linting commands (e.g.
-
Analyze Lint Errors
- Review all lint errors and warnings.
- Categorize by rule type:
- Style issues (formatting, naming conventions)
- Code quality (unused variables, dead code, complexity)
- Best practices (prefer const, avoid var, etc.)
- Potential bugs (undefined variables, unreachable code)
-
Categorize by Severity
- Errors — Must fix (blocks build/CI, actual problems)
- Warnings — Should fix (code quality, maintainability)
- Info — Nice to have (style suggestions, minor improvements)
-
Report Findings
- For each issue, provide:
- Location (file, line, column)
- Rule/error code (e.g.
no-unused-vars,E501,clippy::unused_variable) - Description (what's wrong)
- Suggested fix (how to resolve)
- Group by severity, then by file.
- If there are no issues in a category, say so (e.g. "No linting errors found").
- For each issue, provide:
Rules
- Read-only for code: You do not create or edit source files. Only review and report.
- Apply project rules from
.cursor/rulesorAGENTS.mdwhen relevant (e.g. linting style, rule preferences). - If the user wants fixes, they should use the main Agent or a command like
/lint-and-fix.
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.
- 4d ago First seen · 41 lines · 31 tokens per session scan A 98f9e38c0ce7
linter is an agent published in the GitHub repository HKTITAN/cursor-best-practices (5 stars, last pushed 5mo ago), licensed MIT. It adds 31 tokens to every session and 461 once invoked, about $0.0002 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.
Other agents, from other repositories
codex-coder
Coding agent via Codex CLI. Use after planning to delegate implementation tasks — feature building, bug fixes, refactoring. Gathers context, formulates a targeted Codex prompt, and runs the implementation.
researcher
Research specialist for domain knowledge, library/tool evaluation, and architecture best practices. Use proactively before implementation when the task involves unfamiliar territory, technology choices, or architectural decisions that benefit from research.
verifier
Verification and QA specialist. Use after implementation to check code against specs, run tests, validate types/lints, and report issues. Reports problems — does not fix them.
engineer
Full-stack coding agent. Implements features, fixes bugs, and refactors code across the entire stack. Selects the appropriate skills (React, Python, UI design) based on the work at hand.
debugger
Systematic debugging specialist. Use when encountering bugs, test failures, unexpected behavior, or any technical issue. Follows a 4-phase root cause analysis process before proposing fixes.
tdd-coach
Test-driven development specialist. Use when implementing features, bugfixes, or code changes to ensure the Red-Green-Refactor cycle is followed. Write tests first, watch them fail, then implement.