claude-skills

Discover, find, compare, audit, repair, adapt, and design repeatable AI-agent loops with explicit triggers, actions, verification, stopping conditions, guardrails, and handoffs. Use when a user asks to analyze a codebase for potential loops, mine coding-thread history for work done more than once, turn repeated engineering work into a loop, find or recommend a published loop, create a recurring agent workflow or automation cadence, turn an outcome into a bounded copy-ready loop, or review an existing loop for weak checks, unsafe authority, unbounded repetition, stale state, or unclear stopping behavior.

Use for any C++ networking code with Boost.Asio or standalone Asio (TCP/UDP, SSL, timers, strands, io_context, co_spawn, awaitable, completion handlers), before writing or reviewing it. Applies lifetime, strand and cancellation rules that avoid the classic async bugs.

Use when delegating grunt work to free opencode workers instead of spending Claude tokens: one worker or a scout, coder and tester swarm in worktrees. Triggers on 'spawn a worker', 'swarm', 'delegate to opencode' or /oc.

Write the least code: no over-engineering, fewer dependencies. Use whenever the user wants it simpler; applies a ladder first: YAGNI, reuse, stdlib, native platform, existing deps.

Use when the user says 'no hallucinations', 'verify APIs' or 'don't invent functions', or code depends on a library version you have not checked. Requires proof that every method, import and variable exists in the installed version before using it.

Use when someone learning Swedish wants a learning path or YouTube clips and podcasts matched to their CEFR level and skill (SFI, Lätt Svenska, Radio Sweden på lätt svenska).

Use when the user asks to deeply read a book, article, PDF, or document set; extract claims and evidence; build a knowledge map; or learn through Feynman explanation and recall. Covers quick, deep, map, Feynman, and whole-book reading modes.

Use when someone wants to build, launch, grade or schedule a Claude Managed Agent in their own Anthropic account ('build me an agent', 'run this nightly'). Reads the session goal, routes with goal_router.py and compiles the loop with loop_compiler.py.

Use when a launched managed agent needs grading against a rubric and improving ('grade my agent', 'is it good enough'). Builds the outcome with outcome_builder.py, reads verdicts with verdict_reader.py and runs held-back evals from eval_scaffold.py.

Use when someone has an agent idea to scope before launch ('help me scope an agent'). Interviews them about the one job and writes a build sheet with build_sheet_builder.py, checked by primitives_validator.py; no API key needed.

Use when a graded managed agent should run on a schedule, on an event trigger or on demand ('run it every morning'). Validates cron with cron_validator.py and builds the deployment with deployment_builder.py.

Use when a managed-agent build sheet is ready to launch ('launch it', 'deploy the agent'). Generates and validates API payloads with payload_generator.py and payload_validator.py and writes a resumable curl script with launch_script_writer.py that uses the user's own key.

Use when closing out a launched managed agent ('wrap up', 'what do I own now'). Inventories primitives with primitives_inventory.py, regenerates the overview with overview_page.py and suggests next upgrades with upgrade_suggester.py.

Use when a growth request needs routing between customer-success-manager, sales-engineer, revenue-operations and contract-and-proposal-writer.

Use when drafting a freelance contract, proposal, SOW, NDA or MSA for US, EU, UK or DACH jurisdictions. Writes structured Markdown with docx conversion steps; not legal advice.

Use when reviewing customer accounts for health, churn risk or expansion. Scores health with health_score_calculator.py, churn with churn_risk_analyzer.py and upsell with expansion_opportunity_scorer.py.

Check sales pipeline and forecasts: pipeline coverage, forecast accuracy, magic number, CAC payback. Use whenever the user asks if pipeline is enough or how good forecasts are.

Use for pre-sales work: RFP coverage gaps, competitive feature matrices or planning and scoring a proof of concept. Runs rfp_response_analyzer.py, competitive_matrix_builder.py and poc_planner.py.

Route internal operations requests to the right BizOps skill: process, vendors, capacity, internal comms, SOPs, procurement. Use whenever the user asks where the bottleneck is or about vendor health.

Size an ops or support team and plan headcount: Erlang C queue models, utilization risk, hiring order. Use whenever the user asks how many agents or staff they need, if the team is overloaded, or who to hire first.

Use when announcing a reorg, tool rollout, policy change, leadership change, layoff or acquisition internally. Builds the announcement with change_announcement_builder.py and sequences it with comms_calendar_builder.py.

Use when writing, checking or cleaning up SOPs and runbooks. Generates them with sop_generator.py, checks 5W2H completeness and links with runbook_validator.py and ingests an existing knowledge base with kb_ingester.py.

Use when documenting an end-to-end business process (procurement, onboarding, handoffs) and finding where work waits. Maps it with process_documenter.py, measures stages with cycle_time_analyzer.py and finds bottlenecks with bottleneck_detector.py.

Cut spend on software and suppliers: SaaS audit, category spend review, slow purchasing cycles, supplier consolidation. Use whenever the user asks which tools or vendors to cut, where money goes, or why buying takes so long.

Use when scoring or auditing vendors: scorecards, SLA compliance and service credits, third-party risk tier or a tier-1 vendor review. Runs vendor_scorer.py, sla_compliance_tracker.py and vendor_risk_classifier.py.

Use when C-suite advisor agents need to call each other or run a multi-role meeting. Defines invocation syntax, loop prevention, isolation and response formats.

Use when a founder wants to document or design a whole company as version-controlled markdown (company as code, a company wiki agents can read, an OKF bundle). Runs a 12-phase interview, scaffolds with scaffold_bundle.py and checks it with okf_linter.py.

Use when building a board deck, investor update or QBR from all C-suite perspectives. Structures the narrative and how to deliver bad news.

Use for /c-level-agents:boardroom or a strategic question that needs a structured multi-executive deliberation. Runs six phases: context, isolated C-suite views, critic, synthesis, founder review and decision.

Find which C-level advisor fits a question: 14 C-suite roles, board meetings, culture, M&A. Use whenever the user asks which advisor to use.

Advice for a CEO or founder on running the company: board and investor trouble, raise or cut, strategy bets, org and culture. Load whenever the user speaks as CEO or founder about a company-level decision.

Startup finance: runway and burn, unit economics (LTV, CAC, payback), fundraising and dilution. Load whenever the user asks how long the cash lasts, if burn is too high, or shares cash, ARR or CAC numbers.

Use when rolling out a reorg, pivot, tool switch, leadership change or product kill. Plans it with ADKAR, communication templates and resistance patterns.

Use for AI strategy decisions: API vs fine-tune vs build, EU AI Act or US state risk classification, when self-hosting pays off, or AI hiring order. Runs model_buildvsbuy_calculator.py, ai_risk_classifier.py and ai_cost_economics.py.

Use for retention strategy, customer segmentation or CS team sizing decisions (GRR vs NRR, churn causes, pooled vs named CSMs). Runs retention_decomposition_analyzer.py, customer_segmentation_designer.py and cs_coverage_calculator.py.

Use for data strategy decisions: training models on customer data, warehouse vs lakehouse vs mesh, valuing data for a raise or M&A, or data hiring order. Runs ai_training_data_audit.py, data_product_strategy_picker.py and data_asset_valuator.py.

Use when a founder question needs routing to the right C-suite advisor, or a cross-functional decision needs a board meeting convened. Loads company context, synthesizes the answers and tracks decisions.

People strategy: hiring plans, comp bands, org structure, performance, retention. Use whenever the user asks who to hire, what to pay, how to structure teams or why staff leave.

Use for security leadership decisions: a security program, budget justification in dollars, SOC 2 vs ISO 27001 vs HIPAA roadmap, or board security reporting. Quantifies risk with risk_quantifier.py and tracks compliance with compliance_tracker.py.

Marketing leadership: positioning, product-led vs sales-led vs community-led growth, budget split across channels, marketing team design. Use whenever the user asks how to grow, which go-to-market fits or where to spend.