Triggers the WORK-PIPELINE when a user request starts with a [] tag (e.g., [new-feature], [bugfix], [WORK start]). Use this skill whenever you detect a [] tag at the beginning of a user message.
npx skills add https://github.com/davepoon/buildwithclaude --skill work-pipeline
When the user's message starts with a [] tag, start the WORK-PIPELINE by reading ../skills/sdd-pipeline/references/agent-flow.md and following the orchestration flow.
Any message starting with [...] triggers this pipeline:
[new-feature], [enhancement], [bugfix], [new-work], [WORK start]When this skill is triggered, Claude Code provides the "Base directory for this skill" as an absolute path.
Derive the REFERENCES_DIR from it:
REFERENCES_DIR = {Base directory}/../sdd-pipeline/references
You MUST pass this absolute path to every sub-agent invocation (specifier, planner, scheduler, builder, verifier, committer).
Include it at the top of the prompt text:
REFERENCES_DIR={absolute_path}
Sub-agents need this path to read their reference files. Without it, they cannot find the files and will loop.
works/WORK-NN/Requirement.md, determines execution-mode (direct/pipeline/full)direct: call builder → committerpipeline: call builder → verifier → committer in sequencefull: call planner → ⛔ STOP for 2nd approval → scheduler → [builder → verifier → committer] × NIf the user's message ends with "auto" or "자동으로", skip ALL approval steps and execute the entire pipeline automatically. This is the ONLY case where approval gates can be skipped.
User requirement: $ARGUMENTS
Skill converted from mcp-deploy-manage-agents.prompt.md
Use this skill when the user wants to launch a new AltClaw, OpenClaw, PicoClaw, or Ottie deployment through Cloud Claw. Covers the same user-facing fields and constraints exposed in the Cloud Claw UI, using the local altllm cloud-claw-* commands. Do NOT use for post-launch lifecycle tasks like start/stop/delete/logs; use cloud-claw-manage-vm.
Build hosted agents using Azure AI Projects SDK with ImageBasedHostedAgentDefinition. Use when creating container-based agents in Azure AI Foundry.
Build MCP (Model Context Protocol) servers on Cloudflare Workers with tools, resources, and prompts.
Chain agent outputs as inputs in sequential or parallel pipelines for data flow orchestration
Audit cloned or reimplemented websites for fidelity gaps, tracking scripts, source-brand and language residue, placeholders, and risky external dependencies. Use before handoff or deployment, or when asked to review a website clone for cleanup and readiness.
> Install and operate Hermes Tweet, a Hermes Agent plugin for X/Twitter research, timeline reading, tweet analysis, and approval-gated tweet actions. Use this skill when installing Hermes Tweet, researching X/Twitter accounts, monitoring launch signals, investigating mentions, auditing giveaways, or preparing guarded tweet actions. Use proactively when a Hermes Agent workflow needs current X/Twitter context. Requires XQUIK_API_KEY for read and action tools.
Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.
Take davepoon/work-pipeline from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.