Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/kok-o/koko-contextos-agentsnpx agentmods add rules/kok-o/koko-contextos-agents/gemini-precisionWrote 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/kok-o/koko-contextos-agents/gemini-precision)<a href="https://agentmods.dev/rules/kok-o/koko-contextos-agents/gemini-precision"><img src="https://agentmods.dev/badge/rules/kok-o/koko-contextos-agents/gemini-precision/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/rules/kok-o/koko-contextos-agents/gemini-precision"><img src="https://agentmods.dev/badge/rules/kok-o/koko-contextos-agents/gemini-precision.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00040 | $0.01198 |
| Opus 5 | $0.00020 | $0.00599 |
| Sonnet 5 | $0.00008 | $0.00240 |
| Haiku 4.5 | $0.00004 | $0.00120 |
Grade A, and why
gemini-precision 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 3d 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: gemini-precision
gemini-precision
Overview
High-precision operational standard designed specifically to harness the high speed and expansive context window of Google Gemini models while eliminating common LLM failure modes: hasty assumptions, partial code placeholders (// ...), unverified assertions, and scope creep.
When to Use
Activate whenever:
- Executing non-trivial code modifications, refactoring, bug fixes, or architecture design.
- The user requires maximum rigor, reliability, and precision from Gemini.
- Handling complex multi-file changes where accidental side-effects must be zero.
Rules & Patterns
1. The Read-Before-Write Invariant (Zero Assumptions)
Never write code based on assumptions about the codebase.
- Before modifying a function or creating an integration, always inspect the actual files using
view_fileorgrep_search. - Check the exact runtime, framework version, and installed dependencies (e.g. React 19 vs 18, Next.js 15 vs 14, Tailwind v4 vs v3, Zod vs Joi) in
package.jsonor config files before generating code. - Verify imported symbol names and parameter signatures directly from source files.
2. The Zero-Placeholder Invariant (Complete Code Only)
Never produce lazy, incomplete, or stubbed output.
- ❌ Forbidden:
// TODO: implement logic here// ... rest of existing code ...// ... existing imports ...- Mock stub returns when real integration is required
- ✅ Mandatory:
- Provide 100% complete, fully-implemented, compilable, and drop-in ready code.
- When replacing a block of code, include all necessary imports, type definitions, and edge-case handling.
3. The Proof-of-Work Invariant (Verification Before Completion)
Never claim a task is complete without tool-verified evidence.
- When modifying code or configuration:
- Run the project validator or compiler (
node .agents/ctx.js validate,tsc --noEmit, etc.). - Run unit and integration tests (
npm test,pytest, etc.). - Run linter and formatting checks (
npm run lint:md,eslint, etc.).
- Run the project validator or compiler (
- If a test or validation fails, do not guess: read the exact error trace, fix the root cause, and re-run until green.
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.
- 3d ago First seen · 144 lines · 40 tokens per session scan A 04cdfbd4c63d
gemini-precision is a cursor rule published in the GitHub repository kok-o/koko-contextos-agents (2 stars, last pushed 4d ago), licensed MIT. It adds 40 tokens to every session and 1,198 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 2026-09-05.
Other cursor rules, from other repositories
inspect-quality
Interactive QA session where user reports bugs or issues conversationally, and the agent logs them to specs/bugs/registry.yaml with a structured audit schema. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, or mentions "QA session".
quick-fix
Streamlined fast-path for trivial data-only fixes — no TDD, no branching ceremony. Collapses 6 skills into 2 for changes that are purely data with no logic risk. Aborts with fallback to investigate-bug if guardrails trigger.
validate-fix
Prove a fix works before declaring done — re-run the failing test, run the full suite, typecheck, lint, and harden against recurrence. Use after implementing a bug fix, when user says "is this fixed?", or before closing an investigation.
wire-observability
Add structured JSON logging, observability commands, and idempotent setup scripts to a project. Use when a project needs production-readiness instrumentation, when user wants structured logging, or as a production-readiness gate at any phase of development.
fix-bug
Bug fix orchestrator — activeflow fixbug; reads specs/bugs/BUG-.md; chains investigate-bug, develop-tdd, validate-fix. Use when user reports a defect.
investigate-bug
Investigate a bug or issue by exploring the codebase to find root cause, then write a TDD-based fix plan to specs/bugs/BUG-.md. Use when user reports a bug, wants to investigate a problem, mentions "triage", or wants to plan a fix.