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Found 24 Skills
Generates actionable Disaster Recovery (DR) runbooks from infrastructure and requirements. Validates IaC for resilience (backups, redundancy).
Discovers all documentation in a project, analyzes it for redundancy, contradictions, and staleness, proposes a consolidation plan, then executes it. Produces optimized docs for both humans and agents. Use when user says "combine docs", "consolidate documentation", "merge docs", "clean up docs", "fix documentation", "optimize docs", "documentation sprawl", "too many docs", or asks about doc organization.
When the user wants to build or improve a sales bot's ability to try alternative channels when one fails. Also use when the user mentions "channel fallback," "channel switching," "multi-channel retry," "delivery failure handling," or "channel redundancy."
Review and reorganize Claude Code permission settings across all config files (global settings.json, project settings.local.json, dotfiles copies). Identifies redundancy, misplaced permissions, and lack of read/write organization. Produces a clean layout where global settings are the source of truth and project-local files only contain project-specific overrides. Use this skill whenever the user mentions reviewing permissions, cleaning up settings, auditing allowed tools, reorganizing settings.json, or asking "what permissions do I have". Also use when adding new MCP servers or tools and wanting to decide what to pre-allow. Triggers: "review permissions", "audit settings", "clean up settings.json", "permissions audit", "/permissions-audit".
Guides failure-prevention culture and operational excellence for mission-critical engineering— zero-defect aspiration vs error budgets; HRO principles; defense-in-depth; fail-safe/fail-closed; verification gates and independent checks; redundancy and graceful degradation; pre-mortems and FMEA; stop-the-line; defect escape, near-miss, and repeat-incident metrics; leadership against normalization of deviance—not blame culture. Use for failure-prevention programs, HRO practices, verification gates, fail-safe design, pre-mortem/FMEA, stop-the-line, near-miss reporting, or defect-escape metrics—not SRE error budgets only (site-reliability-engineer), incident command only (incident-management-engineer), backup/restore only (cyber-resilience-engineer), CI lint only (build-validator), agile coaching, HR discipline, or classified ATO without ops-excellence lens (classified-cyber-security-senior-manager).
Optimizer that refines and professionalizes AI agent skills through real usage — saves tokens, eliminates redundancy, and tightens instructions so skills cost less to run. Learns from mistakes, reviews quality, and improves over time. Observes skill execution in the current conversation, analyzes up to four sources (conversation friction, file diffs, user feedback, static diagnostic) plus accumulated lessons, and proposes concrete improvements to the target skill's SKILL.md. Works with Claude Code and compatible SKILL.md-based agent frameworks. Use after executing any skill: `/skill-optimizer [name]` or `/skill-optimizer` to auto-detect. `--review` processes accumulated lessons.
Planner-pass coverage + redundancy report for an outline+mapping, producing `outline/coverage_report.md` and `outline/outline_state.jsonl`. **Trigger**: planner, dynamic outline, outline refinement, coverage report, 大纲迭代, 覆盖率报告. **Use when**: you have `outline/outline.yml` + `outline/mapping.tsv` and want a verifiable, NO-PROSE planner pass before writing. **Skip if**: you don't want any outline/mapping diagnostics (or you have a frozen/approved structure and will not change it). **Network**: none. **Guardrail**: NO PROSE; do not invent papers; only report coverage/reuse and propose structural actions as bullets.
Find, rank, and safely remove accidental codebase complexity by proving real consumers, dynamic entrypoints, compatibility obligations, duplicate representations, speculative surfaces, and lifecycle ownership. Use when asked to simplify or clean up a repository, reclaim code entropy, reduce over-engineering or redundancy, find deletion candidates, collapse duplicate state/APIs, remove dead or added-then-abandoned code beyond static-tool output, or implement an evidence-backed simplification pass in any language or stack. Also trigger for 代码化简、熵回收、删代码、清理冗余、收敛抽象、去除过度设计. Do not use as a performance audit unless simplification is the stated goal.
Design carrier- and enterprise-scale backbone networks—core/distribution/edge topology, OSPF, IS-IS, BGP and route policy, WAN/MPLS/SD-WAN, DCI, peering, transit, IX, anycast, ECMP, BFD, FRR, addressing, backbone QoS, capacity, maintenance domains, and observability (NetFlow, SNMP, telemetry); EVPN/VXLAN spine-leaf where relevant. This skill should be used when the user asks about network backbone, backbone architect, BGP design, OSPF, IS-IS, WAN architecture, MPLS, SD-WAN, data center interconnect, DCI, internet peering, transit provider, IX, core network design, route policy, ECMP, network redundancy, spine-leaf, or EVPN—not app HTTP/API (enterprise-integration-api-developer), cloud landing zone or VPC only (cloud-architect, enterprise-cloud-architect), host or endpoint security (information-security-engineer), cloud/Linux sysadmin (cloud-system-administrator), cabling without routing (infrastructure-engineer), or OT/ICS (scada-ics-cyber-security-specialist).
Evaluate a repo agent harness (AGENTS.md, rules, skills, skill refs) for broken paths/commands, redundant instructions, and usefulness using a stack-agnostic dual-judge protocol with planted traps. HIGH PRIORITY questionnaires at top: Q1 optional docs, Q2 B/C budget before Track A (certainty/tokens). A always runs after Q2; B/C opt-in. ADRs/RFCs excluded from T2. Mixed apply uses 11-mixed-apply.md (KEEP/CUT). Use when the user says harness eval, harness-eval, harness debug, audit AGENTS.md, audit skills/rules, instruction audit, redundancy of agent instructions, usefulness of skills, Ship/Review/Hold/Slim/Keep-core for harness, or wants Track A/B/C harness evaluation. Do NOT use for harness setup or init, feature spec-driven work (tlc-spec-driven), or applying Ship/Slim trims unless the user explicitly asks after the report.
Audits a repository's GitHub Actions workflows for CI optimization opportunities — missing caches, redundant setup, sleep-based readiness, long test jobs without sharding, full-history checkout, dead env vars, build-cache misconfig, and ~60 more patterns across caching, redundancy, parallelization, conditional execution, trigger scope, and hidden failures. Use when: (1) analyzing a repo's CI for optimization opportunities, (2) producing a prioritized report with measured wall-clock and runner-minute savings, (3) re-auditing after upstream CI changes. Do not trigger for: general CI setup help, writing new workflows from scratch, non-GitHub-Actions CI systems, or security/posture audits — use `ci-secure` for those.
Use to design, understand, tune, or audit a non-trivial model workflow, including framework-undecided designs, partial implementations, and production reviews: model-node responsibilities, input/output completeness, data-flow correctness or redundancy, model-versus-Host/workflow ownership, topology, evidence, lifecycle, concurrency, or observed execution effects. The user need not say Prompt review or name Agently. Use agently-request for one request family and agently-triggerflow for already-decided executable orchestration details.