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/techtalk/ai-readiness-assessment/cursorrulesgit clone --depth 1 https://github.com/techtalk/ai-readiness-assessmentWhat 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 | $0.00119 | $0.00119 |
| Opus 5 | $0.00060 | $0.00060 |
| Sonnet 5 | $0.00024 | $0.00024 |
| Haiku 4.5 | $0.00012 | $0.00012 |
Grade A, and why
cursorrules 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 2d 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
Cursor rules — wordcount
Coding style:
- Use Python 3.10+ features (match statements,
X | Yunion types). - Prefer
pathlib.Pathoveros.path. - No bare
except:— always name the exception type. - All public functions have type hints.
- Run
ruff check .before pushing; fix the warnings, don't silence them.
Do not:
- Add dependencies without discussing first.
- Catch
Exceptionto "make tests pass." - Use
printfor diagnostics in library code (uselogging).
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.
- 2d ago First seen · 16 lines · 119 tokens per session scan A ef07785e864d
cursorrules is a cursor rule published in the GitHub repository techtalk/ai-readiness-assessment (9 stars, last pushed 15d ago), licensed Apache-2.0. It adds 119 tokens to every session, about $0.0006 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
aictx
Cursor rule "aictx" from oldskultxo/aictx, covering aictx, priority model, default loop, inspection and advanced tools and what to record.
verify-ai-readiness
Holistic assessment of the AI knowledge layer on a 5-level maturity scale; flags agent-blocking gaps.
01-qa-agent
QA AGENT PERSONA: Principles, Anti-patterns, workflows.
03-skill-testcases
SKILL: Generate Test Scenarios Matrix from API spec (use for /api-isolated-tests).
aria-audit
ARIA audit skills — /audit dispatcher plus /audit-knowledge, /audit-config, /audit-style, /audit-usage. Use when user says 'audit knowledge', 'audit config', 'audit style', 'audit usage', 'review setup', or runs the slash commands.
ai-dev-os-review
Performs a comprehensive self-review before creating a PR. Combines guideline compliance checking (L3) with design-level review (L2) and philosophical alignment (L1). Unlike @ai-dev-os-check which only checks rules, this also evaluates architecture decisions and code design quality.