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Tashtit Marketplace

Opinionated, production-focused engineering standards for AI coding agents.

Tashtit is an open-source plugin marketplace for teams that want agents to work with the same discipline expected from experienced production engineers. It packages reviewable standards, repeatable workflows, and practical engineering knowledge for Claude Code, Codex, and GitHub Copilot. Cursor is an optional compatibility target.

The project is hosted as tashtit/marketplace. Its stable marketplace identifier is tashtit.

Important

Tashtit is in its foundation phase. The repository structure, quality bar, and compatibility model are being established before the first stable plugin release. Nothing is currently advertised as production-ready.

Installation

Add the marketplace once per platform, then install plugins by name. engineering-standards below is an example; any name from Available plugins works.

Claude Code

claude plugin marketplace add tashtit/marketplace
claude plugin install engineering-standards@tashtit

GitHub Copilot CLI

copilot plugin marketplace add tashtit/marketplace
copilot plugin install engineering-standards@tashtit

OpenAI Codex CLI

codex plugin marketplace add tashtit/marketplace
codex plugin add engineering-standards

Every plugin except evalkit is published to the Codex catalog; evalkit supports Claude Code and GitHub Copilot CLI only.

Why Tashtit

Agent output should be safe to review, predictable to operate, and suitable for real repositories. Every stable Tashtit plugin is expected to be:

  • Opinionated: it recommends a default instead of returning an unranked menu.
  • Production-ready: it covers failure modes, verification, and operations.
  • Enterprise-minded: it respects security, auditability, least privilege, change control, and repository policy.
  • Portable: its core behavior is shared across supported agent platforms.
  • Evidence-driven: normative guidance cites authoritative sources or clearly labels a Tashtit convention.
  • Accountable: every plugin declares its behavior as acceptance scenarios, and a maturity claim above experimental requires a recorded passing review of each scenario on each claimed platform. Automation enforces that record, not the behavior itself.

Compatibility

Platform Priority Status
Claude Code Core Foundation
OpenAI Codex Core Foundation
GitHub Copilot Core Foundation
Cursor Optional Research

See compatibility for the adapter model and support policy.

Planned catalog

Most of the initial backlog has shipped and is listed under Available plugins. The remaining backlog is organized around:

  • reusable infrastructure snippets, beginning with Redis and connection lifecycle patterns;
  • code style and maintainability.

The prioritized scope and acceptance criteria live in the roadmap.

Available plugins

Plugin Version Maturity Default behavior
Agent Parity 0.1.0 Experimental Cross-agent instructions, MCP, skills, and plugin parity report, fixes on request
API Design Standards 0.1.0 Experimental Async REST jobs and safe API deprecation
Architecture Diagrams 0.1.0 Experimental C4 system context and container diagrams
Dependency Standards 0.1.0 Experimental Evidence-gated dependency intake, updates, and removal
Engineering Standards 0.2.0 Experimental Evidence-backed production change review
Evalkit 0.4.2 Experimental Host-adaptive static skill review and worktree-isolated skill/model benchmarks (Claude Code + Copilot CLI)
Git Workflow 0.1.0 Experimental Safe branches, commits, and pull-request handoff
GitHub Actions Standards 0.4.0 Experimental Secure, reproducible CI and release workflows
Interview Kit 0.1.0 Experimental Mock system design interviews graded against a cited concept library; enable after the build, not during
Logging Standards 0.1.0 Experimental Secure structured production logging
Maturity 0.3.1 Experimental Dockerfile, npm, repository-hygiene, and CI-workflow maturity evaluation, fixes on request
Repository Governance 0.1.1 Experimental Audit repository governance, then optionally apply merge policy and rulesets
Repository Onboarding 0.1.0 Experimental Read-only, evidence-backed repository assessment
TypeScript Library Build 0.1.0 Experimental Dual ESM and CJS library build and publish
TypeScript Style Standards 0.1.0 Experimental Convention-first TypeScript style: types, readonly, parameters, naming

Experimental plugins are published for evaluation and do not carry Tashtit's stable compatibility or production-readiness claim.

Repository model

plugins/<plugin-name>/
├── skills/                         # Shared canonical behavior
├── .claude-plugin/plugin.json      # Canonical Claude/Copilot manifest
└── .codex-plugin/plugin.json       # Generated for Codex's required path

.claude-plugin/marketplace.json     # Canonical Claude/Copilot catalog
.agents/plugins/marketplace.json    # Generated Codex catalog

Tashtit reuses one file wherever platforms accept the same standard location. When a format or a required location cannot be shared, provider files are generated with npm run sync and checked for drift in CI; they are never maintained as hand-copied implementations, and never as repository symlinks. See the architecture for the full deduplication policy.

Project status

Tashtit uses maturity levels so installation never implies unsupported stability:

  1. Experimental: design is still changing; no compatibility guarantee, and no behavioral review is claimed.
  2. Candidate: automated validation passes and every acceptance scenario has a recorded passing review on each claimed platform at the published version.
  3. Stable: documented compatibility, security review, and release history.
  4. Deprecated: supported only for a documented migration window.

Only stable plugins may use the production-ready label. Every plugin is currently experimental, so no behavioral review is being claimed yet; reviews are recorded in tests/plugins/<name>/acceptance.json and npm run validate rejects an unearned maturity claim.

Contributing

Read CONTRIBUTING.md, the quality standard, the dependency policy, and SECURITY.md before proposing a plugin. Contributions are accepted under the Apache License 2.0.

For project direction, see GOVERNANCE.md. For usage questions, see SUPPORT.md.

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Opinionated, production-ready engineering standards for AI coding agents.

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