TSH Stack: Python

The business-analysis workflow end to end: discovery workshop materials — transcripts, Figma, PDFs, codebase context — become Jira-ready epics and user stories, a per-product domain dictionary and an outcome-based delivery roadmap, behind five human review gates, with a hook that, while a business-analysis session is open in the repository, refuses Jira writes to a project until the push gate is approved for that project. Also imports an existing Jira backlog for local iteration. Seven read-only worker subagents keep the heavy reading out of the conversation.

16 skills · 7 agents · hooks

Spec-driven feature implementation: committed plan files, delegated implementer subagents, a Figma-backed UI verification gate driven by Playwright-CLI capture, root-cause bug fixing guarded by a regression test, and TSH's structured pre-merge code review.

9 skills · 7 agents

What every TSH teammate needs regardless of discipline or stack: safe Git worktree lifecycle management, the house standard for writing technical documents, authoring Claude Code extensions, the project-context files Claude Code loads, the decision-record format and lifecycle, a one-command project setup that wires them all together, and three bundled MCP servers: Atlassian for Jira and Confluence, Figma for design context, and Context7 for library documentation.

6 skills · 3 MCP servers

Infrastructure, CI/CD and deployment the TSH way: Terraform modules, pipelines with OIDC and plan gates, production-shaped Kubernetes workloads, observability with SLOs, secrets management, and evidence-based cloud cost audits.

7 skills · 2 agents

GCP-specific infrastructure guidance: Terraform module patterns for VPC, GKE, Cloud SQL, Cloud Storage and Cloud Run, Workload Identity and CMEK defaults, and a full evidence-based GCP cost and labelling audit of a live project.

2 skills · 3 MCP servers

Quality assurance: Playwright end-to-end tests proven stable by repeated headless runs, and WCAG 2.1 AA accessibility audits that report the success criterion behind every finding.

2 skills · 1 agent

Matt Pocock's agent skills for real engineering (grilling, spec/ticket flows, TDD, code review, domain modelling and more).

39 skills

AGENTS.md as project instructions, by one option. Under claude-md-or-agents-md a project with no instruction files of its own gets its AGENTS.md files instead: a prompt.context hook asks $.fs.ancestors for every AGENTS.md and .claude/AGENTS.md from the filesystem root down to the working directory and hands them to the engine as project instruction files, which it renders, announces and withholds from agents exactly as it does CLAUDE.md, skipping any file the engine already loaded by import or link; a tool.call hook on Read attaches the ones under the project root as the engine attaches a nested CLAUDE.md. Under claude-md-and-agents-md every AGENTS.md is loaded beside CLAUDE.md. Under managed-only the project's and the person's instruction files are dropped and the organization's managed ones kept. Under claude-md the engine's walk stands alone. claude-md-or-agents-md is the default.

Production-grade engineering skills covering every phase of software development: spec, plan, build, verify, review, and ship.

25 skills · 4 agents

Agentic QE (external: maintained in proffesor-for-testing/agentic-qe, pinned to v3.15.17): a quality-engineering fleet with 11 QE agents, 9 skills, 9 commands, the agentic-qe MCP server pinned to the plugin version, and the aqe-mod guard that refuses destructive operations on AQE learning data

9 skills · 9 commands · 11 agents · 1 MCP server

Skill: add headroom-ai compress() to a Python or TypeScript app to cut LLM input tokens (tool outputs, logs, JSON, chat history). No API key.

1 skill

Generate natively editable PPTX from PDF / DOCX / URL / Markdown — real DrawingML shapes, text boxes, charts, and animations. Note: run `pip install -r requirements.txt` inside the installed plugin directory for the Python post-processing scripts to work.

1 skill