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Repositorio de GitHub

fsharp

fsharp contiene 12 skills recopiladas de dotnet, con cobertura ocupacional por repositorio y páginas de detalle dentro del sitio.

skills recopiladas
12
Stars
4.3k
actualizado
2026-06-17
Forks
865
Cobertura ocupacional
5 categorías ocupacionales · 100% clasificado
explorador de repositorios

Skills en este repositorio

binlog-analysis
Analistas de sistemas informáticos

Triage a build / compile / restore / WarnAsError failure from its MSBuild binary log. Fetches the binlog (a local build's, or a failed dotnet/fsharp Azure DevOps PR build's published artifact) and analyzes it live via the `binlog-mcp` MCP server — structured errors, root-cause diagnosis, and an MSBuild perf X-ray. NOT for test failures or CheckCodeFormatting: a build binlog has no errors there.

2026-06-17
hypothesis-driven-debugging
Desarrolladores de software

Investigate compiler failures, test errors, or unexpected behavior through systematic minimal reproduction, 3-hypothesis testing, and verification. Always re-run builds and tests after changes.

2026-06-17
pr-build-status
Desarrolladores de software

Retrieve and analyze Azure DevOps build failures for GitHub PRs. Use when CI fails. CRITICAL: Collect ALL errors from ALL platforms FIRST, write hypotheses to file, then fix systematically.

2026-06-17
pr-description
Escritores y autores

Use when drafting, proposing, creating, or editing prose for a dotnet/fsharp GitHub PR or issue — body, title, comment, review summary, edits — including bare asks like "open a PR", "ship this", "write up what I did", "summarise the change", "reply on the PR", "edit the issue body", "gh pr create", "gh pr comment", "gh pr edit --body", "gh issue comment", "gh pr review --body". Primary use case is PR descriptions; same rules apply to PR/issue comments and review summaries. Not for labels, reviewers, merging, or code-review findings (just the prose write-up of them).

2026-06-08
fsharp-diagnostics
Desarrolladores de software

Always invoke after editing `.fs` files under `src/Compiler/`. Fast parse/typecheck without `dotnet build`, plus symbol references and inferred type hints. Use whenever the user asks about F# errors, compile errors, type inference, finding usages, or renaming a symbol in the compiler tree.

2026-06-04
reviewing-compiler-prs
Analistas de garantía de calidad de software y probadores

Performs multi-agent, multi-model code review of F# compiler PRs across 19 dimensions including type checking, IL emission, binary compatibility, and IDE performance. Dispatches parallel assessment agents per dimension, consolidates with cross-model agreement scoring, and filters false positives. Invoke when reviewing compiler changes, requesting expert feedback, or performing pre-merge quality checks.

2026-05-20
flaky-test-detector
Analistas de garantía de calidad de software y probadores

Detect flaky tests by scanning recent AzDo CI builds for test failures recurring across multiple unrelated PRs. Use when investigating intermittent failures, CI instability, deciding which tests to quarantine, or checking if RunTestCasesInSequence no-ops are causing parallel-safety issues.

2026-03-16
vsintegration-ide-debugging
Desarrolladores de software

Fix F# debugging issues (breakpoints, .pdb, sequence points). Build, run VS integration tests, inspect IL/PDB.

2026-03-13
ilverify-failure
Desarrolladores de softwareProgramadores informáticos

Fix ILVerify baseline failures when IL shape changes (codegen, new types, method signatures). Use when CI fails on ILVerify job.

2026-02-12
release-notes
Desarrolladores de software

Write release notes for completed changes. Use when PR modifies tracked paths and needs release notes entry.

2026-02-12
postmortem
Desarrolladores de software

Write a postmortem for a regression that escaped to production, broke real users, and traces back to a design flaw worth documenting for future implementors. Only invoke after confirming no existing postmortem or doc covers the same root cause.

2026-02-11
creating-skills
Desarrolladores de software

Create custom agent capabilities when discovering novel tools, receiving task-agnostic tips from reviewers, or after researching specialized workflows not covered in existing instructions. Teaches structure, YAML optimization for LLM discoverability, and token efficiency.

2026-01-13