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/tqakdev/ctxlint/stylegit clone --depth 1 https://github.com/tqakdev/ctxlintWhat 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 | $0.00184 | $0.00184 |
| Opus 5 | $0.00092 | $0.00092 |
| Sonnet 5 | $0.00037 | $0.00037 |
| Haiku 4.5 | $0.00018 | $0.00018 |
Grade A, and why
style 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.
What it actually says
Style rules
- Use 2-space indentation. Semicolons required. Single quotes for strings.
- Always use named exports in shared modules. Never use default exports anywhere in this codebase.
- Keep functions under 50 lines. Extract helpers rather than adding nesting.
- No lodash. Modern JavaScript covers everything we used it for.
API rules
All API route handlers must validate request bodies with the schemas in src/schemas/
before touching the database. Return a 400 with the validation error message when
validation fails. Never trust client input, even from internal services.
- Every endpoint returns JSON, even errors. Error shape is
{ error: string }. - All timestamps in responses are ISO 8601 UTC with a trailing
Z.
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 · 23 lines · 184 tokens per session scan A 6f8e4101fd83
style is a cursor rule published in the GitHub repository tqakdev/ctxlint (1 stars, last pushed 1mo ago), licensed MIT. It adds 184 tokens to every session, about $0.0009 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 cursor rules, from other repositories
project
Core project context for ai-context-kit.
cursorrules
Cursor rule "cursorrules" from googlarz/agents-sync, covering .cursorrules — managed by agents-sync v1.0.0, language: typescript / next.js 14 and run tests: npm test.
react
React component conventions.
ult-onboarding-index
Discover CEP-managed content already present in a target repo (What/How layer docs, compiled guidelines, context packages, decision ledger) via existence checks against layout-slots-registry.yaml-resolved paths, then write one canonical root AGENTS.md onboarding index plus thin per-tool pointer stubs…
ult-institutional-memory-distill
Distill decisions, reasoning, and rejected alternatives from PRs, design docs, and postmortems into the project's decisionledger, so ult-context-generate's trip-wire can surface institutional memory before new work quietly repeats settled ground. Do NOT use to query the ledger against new work or decide…
demo-consume-context
Worked example that discovers, loads, and tags a context package per CONSUMING-CONTEXT-PACKAGE.md, then writes a reverse-index addendum — proves the produce/consume/tag loop end-to-end. Do NOT use for real feature work.