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 darylmcd/Roslyn-Backed-MCP --skill test-coveragegit clone --depth 1 https://github.com/darylmcd/Roslyn-Backed-MCPWrote 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/darylmcd/roslyn-backed-mcp/test-coverage)<a href="https://agentmods.dev/skills/darylmcd/roslyn-backed-mcp/test-coverage"><img src="https://agentmods.dev/badge/skills/darylmcd/roslyn-backed-mcp/test-coverage.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 | $0.00046 | $0.01813 |
| Opus 5 | $0.00023 | $0.00907 |
| Sonnet 5 | $0.00009 | $0.00363 |
| Haiku 4.5 | $0.00005 | $0.00181 |
Grade A, and why
test-coverage 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 8d 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Coverage Analysis
You are a C# testing specialist. Your job is to analyze test coverage, identify untested code, and help scaffold tests for gaps.
Input
$ARGUMENTS is an optional project or test project name. If omitted, analyze the entire loaded workspace. If no workspace is loaded, ask for a solution path.
Server discovery
Use discover_capabilities (testing / all) or MCP prompt review_test_coverage. For red CI focused on failing tests first, skill test-triage is a lighter entry point.
Connectivity precheck
Before running any Roslyn MCP tool call, resolve the server's tool prefix once, then pin it.
The prefix is client-assigned — never hard-code it. Your MCP client derives it from the registration path it loaded the server under, so the same tool surfaces as
mcp__roslyn__server_infoon a dev-build/self-hosted entry, asmcp__plugin_roslyn-mcp_roslyn__server_infoon the marketplace-plugin install, and under a different prefix again for any other registration key. Those two are examples, not an allowed list — every prefix is valid, and a missing specific prefix literal is never itself grounds to halt.
- Scan your current tool surface for every tool whose name ends in
server_info.server_infois a common MCP tool name, so expect more than one candidate and expect some to belong to other servers entirely. - Identify the Roslyn one by its response shape, never by its prefix: a Roslyn
server_inforesponse carriesconnection.state,catalogVersion, andsurface.*. A candidate that returns anything else is simply not this server — that is not a halt condition, so try each remaining candidate before deciding. - Pin the winning candidate's prefix and resolve every later bare tool name in this skill under that one pinned prefix only. Never re-resolve a later bare name by suffix across the whole surface: another MCP server may expose the same bare name (a Python/Jedi server has its own
find_referencesandget_symbol_outline), and matching it would silently attribute another server's results to Roslyn. - Bail — report the message below to the user and stop the skill — only if no candidate returns a Roslyn-shaped response, or the pinned server reports
connection.stateas anything other than"ready"(initializing,degraded, absent):
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.
- 8d ago First seen · 132 lines · 46 tokens per session scan A 3103051eff4c
test-coverage is a skill published in the GitHub repository darylmcd/Roslyn-Backed-MCP (1 stars, last pushed today), licensed MIT. It adds 46 tokens to every session and 1,813 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 2026-08-31.
Other skills, from other repositories
migrate-xunit-to-xunit-v3
Migrate .NET test projects from xUnit.net v2 to xunit.v3 and fix v3 breaks. Use for package/CPM conversion, OutputType=Exe, preserving the VSTest or MTP runner (including projects currently using YTest.MTP.XUnit2), incompatible TFMs, async void tests, string-to-Type attributes, custom Fact/Theory/BeforeAfterTest…
go-testing
Trigger: Go tests, go test coverage, Bubbletea teatest, golden files. Apply focused Go testing patterns.
nw-fp-clojure
Clojure language-specific patterns, data-first modeling, REPL-driven development, and spec.
mobiai-ios-testing
Use when writing or running tests in an iOS project — unit tests, UI tests, snapshot tests, choosing the right framework.
restore-internals-seams-in-finally-blocks-after-each-test
When delegating a task affected by this skill, include.
testing-llm
LLM and AI testing patterns — mock responses, evaluation with DeepEval/RAGAS, structured output validation, and agentic test patterns (generator, healer, planner). Use when testing AI features, validating LLM outputs, or building evaluation pipelines.