Accordant is a .NET framework that turns executable behavioral specifications into generated tests for checking software implementations. It helps developers verify that real systems follow defined rules across many operations and state changes.
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 skills add microsoft/accordant --skill patternsgit clone --depth 1 https://github.com/microsoft/accordantWrote 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/microsoft/accordant/patterns)<a href="https://agentmods.dev/skills/microsoft/accordant/patterns"><img src="https://agentmods.dev/badge/skills/microsoft/accordant/patterns/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/microsoft/accordant/patterns"><img src="https://agentmods.dev/badge/skills/microsoft/accordant/patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00025 | $0.02319 |
| Opus 5.5 | $0.00010 | $0.00928 |
| Sonnet 5.5 | $0.00005 | $0.00464 |
| Haiku 4.5 | $0.00003 | $0.00232 |
Grade A, and why
accordant-patterns 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 1mo 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 — 346 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Common Patterns in Accordant
This skill covers frequently-used patterns when building Accordant specs.
Response-Dependent State
When state depends on server-generated values (IDs, timestamps, ETags):
spec.Operation<CreateOrderRequest, ApiResult<Order>>("CreateOrder", (request, state) =>
{
return Expect.That<ApiResult<Order>>(
r => r.IsSuccess && !string.IsNullOrEmpty(r.Data.OrderId))
.ThenState<AppState>(
// Lambda receives response AND a pre-cloned nextState
(ApiResult<Order> response, AppState nextState) =>
nextState.Orders[response.Data.OrderId] = new OrderState
{
Product = request.Product,
Status = OrderStatus.Created
},
// Mock for test generation (no real system running)
mock: () => new ApiResult<Order>
{
Data = new Order
{
OrderId = Guid.NewGuid().ToString(),
Product = request.Product
},
StatusCode = 201
});
});
Why the Mock?
During test generation, there's no real server. The mock provides a plausible response so Accordant can explore the state space. At test execution, the mock is ignored — real responses are used.
Validating Captured Values
spec.Operation<string, ApiResult<Order>>("GetOrder", (orderId, state) =>
{
if (!state.Orders.TryGetValue(orderId, out var order))
return Expect.That<ApiResult<Order>>(r => r.IsNotFound).SameState();
// Validate against captured state
return Expect.That<ApiResult<Order>>(
r => r.IsSuccess &&
r.Data.OrderId == orderId &&
r.Data.Product == order.Product &&
r.Data.Status == order.Status)
.SameState();
});
Request Derivations
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.
- 1mo ago First seen · 346 lines · 25 tokens per session scan A 6cad55fb7f4f
accordant-patterns is a skill published in the GitHub repository microsoft/accordant (69 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 2,319 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
Other skills, from other repositories
implementing-api-security-testing-with-42crunch
Implement comprehensive API security testing using the 42Crunch platform to perform static audit and dynamic conformance scanning of OpenAPI specifications.
API Test Suite Generator
Automatically generate comprehensive API test suites from OpenAPI specifications covering CRUD operations, error handling, authentication, pagination, and edge cases.
AI Test Generation Patterns
Systematic patterns for prompting AI coding agents to generate high-quality tests including prompt engineering for test creation, coverage-driven generation, mutation-aware testing, and review checklists for AI-generated test code.
Cursor AI Testing Patterns
Effective test automation patterns with Cursor AI IDE including Composer for test suite generation, Cmd+K for inline test edits, Chat for test debugging, codebase-aware test generation, and rules configuration for testing conventions.
GitHub Copilot Testing Patterns
Effective patterns for using GitHub Copilot to generate, refactor, and maintain test code including prompt engineering for test generation, Copilot Chat for debugging, inline suggestions for assertions, and workspace context optimization.
e2e-test-writer
Generate end-to-end tests for web applications using Playwright. Create test files from user flow descriptions, page snapshots, or existing page analysis.