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Found 462 Skills
Automated pipeline for retraining ML models with new construction data. Monitor model drift, trigger retraining, and validate model performance.
Educational guide on best practices for creating implementation plans that prevent drift. Covers style anchors, task sizing, TDD requirements, affirmative instructions, drift handling, and quality gates. Use when creating or improving implementation plans to ensure they follow proven patterns.
Periodic evidence-based self-audit of the whole agent system — the orchestrator, its docs/SSOTs, rules, memory, subagents, tools, infra and the work it claims to have delivered — followed by immediate cheap-safe fixes and a ranked backlog. Use when the user says 'аудит системы', 'проверь себя', 'самопроверка', 'system audit', 'audit yourself', 'health check', 'что у нас накопилось', 'система раздулась', 'проверь что работает а что на бумаге', 'gap-анализ', 'что удалить', or on cadence triggers (every ~10 sessions, before a milestone, after a big refactor, when memory hits its caps, when onboarding this repo to a new agent). Seven lenses: delivery reality · knowledge drift · operational layer · layer telemetry (did it ever fire) · tools & infra · domain gaps · anti-bloat subtraction. Not for reviewing a single diff (use a diff-review pass) and not for probing a running product (use /memory-kit:qa-sweep).
Extract learning before restarting. Code is a draft; learning is the asset. Use when work is drifting, approach has reversed 3+ times, or scope is expanding while "done" keeps fuzzing.
GenAI-powered semantic validation - detects outdated docs, version mismatches, and architectural drift
Dynamically validate that the implemented codebase matches architectural decisions documented in plan files. Use when validating implementation matches planning documents, checking for architecture drift, or preparing for architecture reviews.
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for CI/CD, registry, dependency drift, artifact provenance, image build, release pipeline, and runtime consumer challenges. Use when the user asks to trace dependency drift, registry pulls, malicious packages, build or release tampering, CI execution, artifact signing, or which shipped artifact the runtime actually consumes. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
This skill should be used when the user wants to run baseline evaluations on existing agent skills, regenerate transcripts after a model upgrade, or check whether a skill still solves the gap it was authored for. Common triggers include "rerun the baselines", "re-eval skill X", "test all the skills", "check for skill drift", and "run the evals". Bakes in verbatim transcript capture (no paraphrasing), deterministic-only grading (regex / contains / file_exists — no LLM-as-judge), and the iteration-N workspace convention. Skip when authoring a new skill (use skill-creator) or modifying skill content directly.
Use when the user asks to "map what our surfaces say today", "inventory our current messaging", or "find the gap between what we say and what we mean"; produces the narrative baseline — a surface-by-surface inventory of what every owned touchpoint (homepage, pricing, docs, decks, social bios, email footers) claims RIGHT NOW, each line labeled Measured / User-provided / Estimated, plus a per-surface gap read vs the intended message and the drift-baseline snapshot the Evaluate phase measures future drift against. Not for authoring the canon — use message-system-architect; not for scoring the surfaces or running the vetoes — use narrative-quality-auditor. 现状叙事盘点/各触点口径/意图差距/漂移基线
Keep the AI policy current with practice — weekly sweep of saved AIAs, triage results, and vendor reviews to find policy drift, or direct query for a proposed new AI practice. Use when user says "policy sweep", "does our AI policy cover this", "we want to start doing X — does the policy need updating", "run the policy monitor", or on a recurring schedule.
Use when a skill, plan, or rule file needs a frozen Starlark governance rule block generated, or an existing frozen block drift-checked against a candidate. Invoke explicitly — not for general rule discussion.
Manage Harness Infrastructure as Code Management (IaCM) via MCP. Configure Terraform workspaces with remote state and RBAC, set up continuous drift detection with auto-remediation, design multi-tier change approval workflows, and estimate infrastructure costs before deployment. Use when asked to manage Terraform workspaces, detect infrastructure drift, set up approval workflows for infrastructure changes, or estimate Terraform costs. Do NOT use for creating Harness infrastructure definitions (use create-infrastructure instead) or OPA policies (use create-policy instead). Trigger phrases: terraform, workspace, drift detection, infrastructure cost, IaCM, state management, change approval, terraform plan, infracost, infrastructure governance.