Borrowing it
Nothing to install: this file belongs to managedcode/Orleans.RateLimiting. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/managedcode/Orleans.RateLimiting/main/.codex/skills/quality-ci/SKILL.mdgit clone --depth 1 https://github.com/managedcode/Orleans.RateLimitingWrote 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/skills/managedcode/orleans.ratelimiting/quality-ci)<a href="https://agentmods.dev/skills/managedcode/orleans.ratelimiting/quality-ci"><img src="https://agentmods.dev/badge/skills/managedcode/orleans.ratelimiting/quality-ci/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/skills/managedcode/orleans.ratelimiting/quality-ci"><img src="https://agentmods.dev/badge/skills/managedcode/orleans.ratelimiting/quality-ci.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 | $0.00067 | $0.01535 |
| Opus 5.5 | $0.00027 | $0.00614 |
| Sonnet 5.5 | $0.00013 | $0.00307 |
| Haiku 4.5 | $0.00007 | $0.00153 |
Grade A, and why
quality-ci 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 19d 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.
This is a copy
94% identical to quality-ci — 17 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
.NET Quality CI
Trigger On
- adding or tightening .NET code-quality gates in CI
- choosing analyzers, coverage, mutation, or architecture-test tooling for a .NET repo
- standardizing
.editorconfig,dotnet format, and warning policy
Value
- produce a concrete project delta: code, docs, config, tests, CI, or review artifact
- reduce ambiguity through explicit planning, verification, and final validation skills
- leave reusable project context so future tasks are faster and safer
Do Not Use For
- non-.NET repositories
- generic CI/CD guidance with no .NET quality stack decisions
- framework-specific test authoring with no quality-gate change
Inputs
- the nearest
AGENTS.md - the current repo-root
.editorconfigand MSBuild props - the current CI workflow and package references
- the active test runner model: VSTest or Microsoft.Testing.Platform
Quick Start
- Read the nearest
AGENTS.mdand confirm scope and constraints. - Run this skill's
Workflowthrough theRalph Loopuntil outcomes are acceptable. - Return the
Required Result Formatwith concrete artifacts and verification evidence.
Workflow
- Start with the repo-native baseline:
- repo-root
.editorconfig dotnet format --verify-no-changes- SDK analyzers with explicit
EnableNETAnalyzers,AnalysisLevel, and warning policy
- repo-root
- Add third-party analyzers only where they close a real gap:
StyleCopAnalyzersRoslynatorMeziantou.Analyzer- framework analyzers such as xUnit, MSTest, or TUnit analyzers
- Separate quality gates by purpose:
- formatting and style
- correctness and static analysis
- coverage and reports
- architecture rules
- security scanning
- mutation testing
- For complexity, use a composite approach:
- CA1502 thresholding
- maintainability limits in
AGENTS.md - architecture tests
- coverage and mutation where risk justifies it
- Make ownership explicit in
AGENTS.mdand CI:- which command formats
- which command analyzes
- which command measures coverage
- which runner model the tests use
- After any .NET code change, the repo's quality pass must be runnable by agents:
- format
- build
- analyze
- focused tests
- broader tests
- coverage and report generation when configured
- extra configured gates only when the repo actually enabled them
- Route tool-specific setup through dedicated skills where possible:
formatcode-analysisanalyzer-config- analyzer-pack skills such as
stylecop-analyzers,roslynator, andmeziantou-analyzer - frontend asset quality skills in mixed
.NETplus Node repos such aseslint,stylelint,htmlhint,webhint,biome,sonarjs,metalint, andchous - coverage/reporting skills such as
coverletandreportgenerator - architecture/security skills such as
netarchtest,archunitnet, andcodeql
- Avoid overlapping tools with conflicting ownership. If you add an opinionated formatter, define whether it replaces or complements
dotnet format.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 19d ago First seen · 155 lines · 67 tokens per session scan A 70b46a48e40c
quality-ci is a skill published in the GitHub repository managedcode/Orleans.RateLimiting (30 stars, last pushed 11d ago), licensed MIT. It adds 67 tokens to every session and 1,535 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to quality-ci, differing in 17 lines, and is treated as a copy.
Other skills, from other repositories
quality-ci
Set up or refine open-source .NET code-quality gates for CI: formatting, .editorconfig, SDK analyzers, third-party analyzers, coverage, mutation testing, architecture tests, and security scanning. USE FOR: .NET quality gates in CI; analyzer, coverage, mutation, and architecture-test choices; standardizing…
migrate-vstest-to-mtp
Use this skill before answering, planning, or editing whenever .NET tests or CI are switching from VSTest to Microsoft.Testing.Platform (MTP), or an MTP migration behaves differently. Triggers include "switch from VSTest"; MSTest/NUnit/xUnit MTP enablement; OutputType=Exe only for test projects in…
scaffold-dotnet-test-project
MUST USE when an existing .NET test project was excluded from a .slnf/CI solution filter, disappeared from .sln/.slnx discovery, or lost its production ProjectReference; also for requests to set up, create, reuse, add, register, include, or repair a test project. Handles "tests pass directly but CI discovers zero"…
Verification & Quality Assurance
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
quality-scan
Run a scoped, read-only quality scan and report exact-candidate evidence, failures and frozen debt. Use for an ad-hoc gate sweep or release preparation; a static scan is not full release acceptance.
e2e-testing
Use when reviewing CI coverage, automated checks, or test strategy related to Implement end-to-end testing. Focus on whether the rule is continuously verified, not just documented.