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 overviewgit 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/overview)<a href="https://agentmods.dev/skills/microsoft/accordant/overview"><img src="https://agentmods.dev/badge/skills/microsoft/accordant/overview/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/overview"><img src="https://agentmods.dev/badge/skills/microsoft/accordant/overview.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 | $0.00033 | $0.00963 |
| Opus 5.5 | $0.00013 | $0.00385 |
| Sonnet 5.5 | $0.00007 | $0.00193 |
| Haiku 4.5 | $0.00003 | $0.00096 |
Grade A, and why
accordant-overview 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Accordant Overview
Accordant is a model-based testing framework for .NET. You write a spec — executable code that captures what your system should do — and Accordant generates tests, validates responses, and finds bugs.
When to Use Accordant
Accordant excels when:
- Your system is stateful (databases, caches, queues, sessions)
- You have many operations that interact with shared state
- You want to test operation sequences (not just individual calls)
- You need to find race conditions in concurrent code
- You want a single source of truth for behavior (not scattered assertions)
Core Concepts
The Spec
A spec is executable code defining what your system should do:
var spec = new Spec<BankState>();
spec.Operation<string, ApiResult<decimal>>("CreateAccount", (accountId, state) =>
{
if (state.Accounts.ContainsKey(accountId))
return Expect.That<ApiResult<decimal>>(r => r.IsConflict).SameState();
return Expect.That<ApiResult<decimal>>(r => r.IsSuccess && r.Data == 0)
.ThenState<BankState>(s => s.Accounts[accountId] = 0);
});
State
State is what the system "remembers" between operations. Keep it minimal — only what's needed to define correct behavior:
[State]
public partial class BankState
{
public Dictionary<string, decimal> Accounts { get; set; } = new();
}
Operations
An operation represents an atomic action — API call, method invocation, command. Each operation has:
- Apply: What should happen (the spec logic)
- Execute: What actually happens (calls the real system)
Test Generation
Accordant explores operation sequences by simulating the spec, then runs generated tests against your real system:
var testCases = spec.GenerateTests(initialState, inputs, options);
var results = await spec.RunTests(context, initialState, testCases, executionOptions);
The Typical Workflow
- Define State — What does the system track?
- Define Operations — What can happen to that state?
- Bind to Real System — Connect spec operations to actual API calls
- Generate & Run Tests — Let Accordant explore and validate
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 · 122 lines · 33 tokens per session scan A e57696d7dea3
accordant-overview is a skill published in the GitHub repository microsoft/accordant (69 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 963 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.
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