By arozumenko
Use role-based agents (BA, Tech Lead, PM, Python/JS dev, QA) and composable skills to implement structured SDLC workflows: bug-fix, feature planning, code review, TDD, project seeding. Integrates with Obsidian, Microsoft 365, Tricentis TOSCA, Vividus BDD, and Xray.
Use when the user wants a conversational assistant to answer questions, run errands across their tools (email, calendar, Teams, notes), or quietly maintain a second-brain knowledge base in the background. Octo — the user's personal assistant, engaged and resourceful.
> Use when the user wants a conversational assistant to answer questions, run errands across their tools (email, calendar, Teams, notes), or quietly maintain a second-brain knowledge base in the background.
RULES: You MUST respond to this message.
You are **Octo**, the user's personal assistant. Quiet. Observant. Low-noise — but never silent when the user is talking to you.
- **Vault path:** ~/Notes
Headless, file-system Obsidian vault operations (no Obsidian app needed). Use when the user says "save to vault", "log this note", "find my notes about X", "what's in my inbox", "open loops", or when filing an incoming signal (email/chat/memo) or updating people/project/meeting notes.
Disk-first, checkpointed research workflow with three modes — trend research, topic analysis, and fact-checking. Use when the user asks to "research trends", "analyze a topic", "fact-check this", "verify claims", "what's the state of X", or hands you a document to vet.
Gather cross-channel context (local KB, email, Teams, optional web) about a person or topic before responding. Use when the user says "what do we know about X", "find prior discussions with Y", or before drafting any reply where prior history matters.
Microsoft 365 (Graph) access to email, Teams, calendar, and SharePoint. Use when the user asks to "check my email/Teams/calendar", "what meetings do I have", "any messages about X", or whenever a task needs live M365 data rather than memory. Scriptable scans + interactive query.py.
Tricentis TOSCA Cloud automation via the bundled tosca_cli.py — create/update/run TestCases, Modules, Reusable Blocks, Playlists, folders, and TSU import/export. Use when the user asks to create a TOSCA test case, run a playlist, organize cases, or any TOSCA Cloud REST/CLI operation.
Uses power tools
Uses Bash, Write, or Edit tools
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The content layer for AI-assisted software delivery. Role-based agent personas (BA, Tech Lead, PM, devs, QA, PA), workflow skills (TDD, bugfix, code review, task completion, memory, …), and a registry that pulls proven skills from Matt Pocock, Jesse Vincent (obra/superpowers), and Paul Hudson so you don't have to reinvent them.
Install via the npx one-shot or a native plugin manifest and use the agents + skills directly in any AI IDE (Claude Code, Cursor, Gemini CLI, GitHub Copilot CLI, Windsurf, Codex).
flowchart TB
subgraph sdlc["sdlc-skills — content + install resolution"]
direction TB
agents[/"bundles/<br/>agent + skill content"/]
skills[/"orphan skills/<br/>standalone-only content"/]
registry[("skills.json<br/>catalog: orphan + external")]
installer(["bin/init.mjs<br/>npx installer"])
agents --- skills
skills --- registry
registry --- installer
end
subgraph consumers["consumers"]
direction LR
ides["AI IDEs<br/>Claude Code • Cursor<br/>Gemini CLI • Copilot CLI<br/>Windsurf"]
end
subgraph externals["upstream external skill sources"]
direction LR
ext_matt[["mattpocock/skills<br/>skills/engineering/tdd"]]
ext_obra[["obra/superpowers<br/>brainstorming, debugging,<br/>verification, ..."]]
ext_tws[["twostraws/*-Agent-Skill<br/>SwiftUI, SwiftData,<br/>Swift Testing, Concurrency"]]
ext_msft[["microsoft/playwright-cli<br/>playwright-cli"]]
end
installer ==>|fetch at install time| ext_matt
installer ==>|fetch at install time| ext_obra
installer ==>|fetch at install time| ext_tws
installer ==>|fetch at install time| ext_msft
sdlc ==>|direct install via<br/>plugin manifest or npx| ides
(Node shapes convey grouping so colors aren't needed: / / parallelograms
for content dirs, ( ) round-ended for the installer, cylinders for the
registry, [[ ]] subroutines for external sources. GitHub's Mermaid
renderer uses theme-adaptive colors in both light and dark mode.)
Agents are self-describing — each AGENT.md carries its own metadata
(role, group, theme, aliases, skills, model). IDE plugin systems read it at
install time. Nothing duplicated.
Most agents and skills live inside bundles (bundles/<id>/agents/ and
bundles/<id>/skills/). The top-level agents/ and skills/ directories
hold only standalone-only "orphan" content: one agent (personal-assistant)
and eight skills (deep-research, gathering-context, verifying-outcomes,
microsoft-365, obsidian-vault, tosca-automation, vividus,
xray-testing). skills.json registers those orphan monorepo skills and
the external skills fetched from upstream.
External skills (Matt Pocock's tdd, Jesse Vincent's brainstorming /
systematic-debugging / etc., Paul Hudson's Swift skills) live in their
upstream repos. The installer resolves each agent's declared skill list
against skills.json, clones external repos on first install into
~/.cache/sdlc-skills/registry/, and copies the subdir into your project's
skills directory (or symlinks it with --symlink).
After npx … init + a scout run, your target project has two top-level
directories plus the IDE's native install location:
your-project/
├── .claude/ ← IDE-native install (or .cursor/, .windsurf/, .github/)
│ ├── agents/<role>/ agent config (AGENT.md + SOUL.md)
│ └── skills/<name>/ skill content (SKILL.md + references)
│
├── .agents/ ← IDE-neutral content — every agent reads
│ ├── profile.md scout output: project card
│ ├── architecture.md scout output: system design
│ ├── conventions.md scout output: coding standards
│ ├── testing.md scout output: test infrastructure
│ ├── team-comms.md scout output: transport + roster
│ ├── onboarding.md scout's audit trail
│ └── memory/<role>/ memory-skill dir: MEMORY.md index,
│ curated entries (incl. scout-seeded
│ project_briefing.md), daily/, snapshot.md
│
├── AGENTS.md scout output: full team reference
└── CLAUDE.md scout output: 80-line auto-loaded context
.agents/ holds content every agent reads regardless of IDE. Nothing
in .agents/ is host-specific — it works identically under Claude Code,
Cursor, Gemini CLI, Copilot CLI, and Windsurf.
Scout (scout agent, run once when onboarding) populates everything
under .agents/ plus AGENTS.md / CLAUDE.md at the root. Re-run
scout whenever the stack evolves to refresh.
There are really two paths: the full experience (npx installer) and the monorepo-only fallbacks (native IDE plugins for people who don't want to be happy).
npx claudepluginhub arozumenko/sdlc-skills --plugin test-automation-workflowBrowse, query, and generate AI-powered code wikis. Provides the 'wikis' skill for listing wikis, reading wiki pages, asking Q&A questions, running deep research, and generating new wikis from repository URLs. Requires a running Wikis instance pointed to by WIKIS_URL.
Harness-native ECC operator layer - 67 agents, 271 skills, 92 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
Comprehensive feature development workflow with specialized agents for codebase exploration, architecture design, and quality review
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.