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.
git clone --depth 1 https://github.com/neuromechanist/research-skillsWrote 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/neuromechanist/research-skills/ci_cd)<a href="https://agentmods.dev/rules/neuromechanist/research-skills/ci_cd"><img src="https://agentmods.dev/badge/rules/neuromechanist/research-skills/ci_cd.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 5.1 | $0.00008 | $0.00565 |
| Opus 5 | $0.00004 | $0.00282 |
| Sonnet 5 | $0.00002 | $0.00113 |
| Haiku 4.5 | $0.00001 | $0.00056 |
Grade A, and why
ci_cd 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.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CI/CD Workflow Standards
Purpose: Automated Quality Gates
Why CI/CD? Catch issues before users do. Think: Every pipeline failure is a production bug prevented. Goal: Fast feedback, high confidence, zero surprises.
Essential Workflows
1. Testing (test.yml)
Triggers: on: [push, pull_request] to main branches
Jobs (in order):
- Lint:
ruff check/eslint(fails fast) - Test: Real tests only, matrix for versions
- Build: Verify compilation if applicable
- Coverage: Optional reporting to Codecov
2. Documentation (docs.yml)
Triggers: on: push: branches: [main]
Jobs: Build with MkDocs → Deploy to GitHub Pages
3. Release (release.yml)
Triggers: Tag creation or manual
Jobs: Build → Create release → Publish packages
Minimal Python Example
name: CI
on: [push, pull_request]
jobs:
lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: astral-sh/setup-uv@v4
- run: uv python install 3.12 && uv tool install ruff && ruff check .
test:
needs: lint
runs-on: ubuntu-latest
strategy:
matrix: { python-version: ['3.10', '3.11', '3.12'] }
steps:
- uses: actions/checkout@v4
- uses: astral-sh/setup-uv@v4
- run: uv python install ${{ matrix.python-version }}
- run: uv sync --extra test
- run: uv run pytest --cov=src
Key Practices (Think About Pipeline Flow)
- Pin versions:
actions/checkout@v4(reproducibility) - Cache deps: Speed matters for developer happiness
- Fail fast: Lint→Test→Build→Deploy (catch cheap failures first)
- Matrix testing: Test all supported versions
- Secrets: Never commit credentials
- Conditional: Deploy only from protected branches
Pipeline Philosophy
Fast feedback: Developers should know in <5 min Clear failures: Error messages should guide fixes No surprises: If it passes CI, it works in production
Ask yourself:
- Will this catch real issues?
- Is the feedback loop fast enough?
- Are we testing what actually matters?
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 · 74 lines · 8 tokens per session scan A 4af6aa79c0db
ci_cd is a cursor rule published in the GitHub repository neuromechanist/research-skills (45 stars, last pushed 6d ago), licensed BSD-3-Clause. It adds 8 tokens to every session and 565 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 2026-09-04.
Other cursor rules, from other repositories
workflow
BDD-style workflow, UI screenshots in the PR, HTTP OpenAPI and config schema sync before lint, final checks.
add-linter
Add linter configs and GitHub Actions workflows for languages detected in the current repo. Use when the user wants to add linters, set up code quality checks, or after sync-scaffold suggests running /add-linter.
435-ci-cd-testing-gatekeeper
Purpose: Enforce quality and reliability via CI/CD.
quality
Quality tooling configuration and CI pipeline for the Composer plugin.
ponytail
Ponytail, lazy senior dev mode. Always pick the simplest solution that works.
angular-20
This rule provides comprehensive best practices and coding standards for Angular development, focusing on modern TypeScript, standalone components, signals, and performance optimizations.