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.
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See how to installReview the instructions the agent will receive before you install.
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
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Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
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Pull the ads a competitor is running right now on Meta (Facebook/Instagram) and Google, then extract the hooks, offers, CTAs and landing pages worth modelling. Use when writing ad copy, planning creative tests, choosing a landing page angle, or when the user asks "what is X advertising", "what ads does X run", "find competitor ad hooks". Reads live Ad Library and Ads Transparency data through the Tracetify MCP; falls back to a manual Ad Library walkthrough when the connector is absent.
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Analytics your AI agent can actually use. Track, analyze, run A/B experiments, and optimize across all your projects via CLI. Includes a growth playbook so your agent knows HOW to grow, not just what to track.
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Teaches when to recall from long-term memory before acting and when to save durable decisions, corrections and failures afterwards. Use when a memory tool or MCP memory server is connected but the agent is not using it consistently, when the user complains that the assistant forgets preferences, conventions or past decisions between sessions, or when setting up persistent memory for a project. Works with any memory backend: a folder of Markdown files, a local MCP server, or a managed service.
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Audit local AI coding-agent sessions with agenttrace for cost, tokens, tool failures, latency, anomalies, health, diffs, and CI gates.
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Checks which private files (.env, keys, secrets) Claude Code and its subagents reached in this project, whether a value came into an agent's context, and which key to change, by running the open source agentwhy CLI over the session records Claude Code already keeps on disk. Use when the user asks whether the agent or a subagent read their .env or other secrets, which private files a session touched, whether a key leaked into the conversation, or which key to rotate. Runs locally and never prints a secret value.
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