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/leenspace/contextur/cursor-rulegit clone --depth 1 https://github.com/leenspace/contexturWhat 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 | $0.00009 | $0.00386 |
| Opus 5 | $0.00005 | $0.00193 |
| Sonnet 5 | $0.00002 | $0.00077 |
| Haiku 4.5 | $0.00001 | $0.00039 |
Grade A, and why
cursor-rule 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
This repo uses Contextur for AI code review. The reviewer prompts live in .contextur/reviewers/.
When asked to "review this PR" / "review the code" / "run a code review"
Run contextur review --base {{base_branch}} in the terminal, then follow the 3-stage pipeline in the output:
- Stage 1 — Specialists: run each triggered reviewer against the context bundle.
- Stage 2 — Challenger: validate findings (CONFIRMED / DOWNGRADED / REJECTED).
- Stage 3 — Synthesizer: produce the final developer-facing report.
Present only the synthesized report to the user.
When asked to "initialize contextur" / "set up contextur for this repo" / "personalize the reviewers"
Prefer .agents/skills/contextur-init/SKILL.md when it exists and follow it exactly. It contains the full protocol for ingesting existing AI-friendly docs, launching reviewer-focused research subagents, and appending ## Repo-specific rules sections to each reviewer.
If the shared skill is missing, read .claude/commands/contextur-init.md and follow that protocol instead. If both files are missing, ask the user to re-run contextur init in the terminal first.
When asked to "update contextur" / "refresh the reviewers" / "sync contextur with recent changes"
Read .claude/commands/contextur-update.md and follow its instructions. The update flow is idempotent — it looks for <!-- contextur:repo-specific-start --> / <!-- contextur:repo-specific-end --> markers and replaces only what's between them.
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 · 28 lines · 9 tokens per session scan A 4aa24f50c0c9
cursor-rule is a cursor rule published in the GitHub repository leenspace/contextur (7 stars, last pushed 2mo ago), licensed MIT. It adds 9 tokens to every session and 386 once invoked, about $0.0000 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.
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