Business & Operations

> Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection. Turn departed colleagues into working AI Skills. Feed in chat logs, docs, emails, or screenshots — get back a Skill that writes code in their style, answers questions in their voice, and knows when they'd deflect blame.

> Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection. `clawchief` is an opinionated starter kit that turns [OpenClaw](https://openclaw.dev) into a founder/chief-of-staff OS. It separates prioritization policy, resolution policy, live task state (Todoist), and recurring orchestration (cron) into discrete, composable layers. ---

> Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection. A Python CLI for BOSS 直聘 (boss.zhipin.com) that enables job searching, personalized recommendations, application management, and recruiter messaging via a reverse-engineered API. Supports 10+ browsers for cookie extraction, QR login, structured JSON/YAML output for agent pipelines, and anti-detection rate limiting.

Professional automated trading bot for Binance, Bybit, and OKX Futures with multi-strategy engine, Telegram/TradingView signal integration, and real-time P&L dashboard.

Expertise in Aglais XQVM, a hardware-agnostic Rust quantum virtual machine for QUBO/Ising binary optimization models targeting quantum annealers.

Watch named companies for material news; cited digests.

Use when an agent needs AgentMail CLI email inboxes.

Use when pointing Hermes at a local or remote Ollama.

WiFi cracking, evil twin, deauth attacks, WPA2/WPA3.

RAG-backed. Measure and improve explicit standalone-pad testpoint coverage through a guarded DipTrace PCB transaction. Use when the user says “Plan guarded fixture testpoints for these PCB nets.”

RAG-backed. Design, build, modify, and review electronic devices and schematics through DipTrace MCP with source-backed engineering decisions. Use for architecture, schematic capture, and engineering review; coordinate PCB and production work through pcb-design-workflow when requested. Use when the user says “Design or modify this DipTrace schematic.”

RAG-backed. Produce an explicit evidence-based PASS or BLOCKED decision from implemented DipTrace review profiles and disclosed missing checks. Use when the user says “Run the final evidence-based release gate for this design.”

RAG-backed. Inventory a bounded DipTrace project, its document identity, models, rules, connectivity, unknowns, and evidence before planning changes. Use when the user says “Inventory this DipTrace project before we plan work.”

RAG-backed. Take a DipTrace board through requirements, source evidence, schematic, PCB, production handoff, bring-up, and revisions using existing project skills and explicit build gates. Use for a full design cycle, a new board specification, or resuming a PCB build; «полный цикл платы», «ТЗ на плату», «продолжи разработку». Use when the user says “Take this board through the complete design and production cycle.”

RAG-backed. Collect reviewable DipTrace evidence with native headless PCB acceptance when supported, open/save/close for all four editors and supported native capture; for unsupported actions guide an operator through quarantined source/open-save/re-export capture, dry-run ingest, MCP validation, explicit confirmation, and metadata recording. Use when the user says “Guide an operator through a reviewable DipTrace round-trip capture.”

RAG-backed. Plan and optionally commit one bounded critical-net or differential-pair route in DipTrace with explicit rules and post-checks. Use when the user says “Route this explicitly named critical PCB net.”

Plan and place physical PCB test points (standalone probe pads) on a DipTrace board through the DipTrace MCP server — coverage audit, free-grid candidate selection, guarded dry-run placement, stub routing, and post-checks. Use when the user asks to add or place testpoints on a PCB, improve probe access or testability, plan fixture/bed-of-nails points, or audit PCB test-point coverage.

Improve Coval trace quality after basic ingestion works. Use when traces are sparse, missing useful STT/LLM/TTS/tool spans, missing attributes needed for Coval built-in metrics, or when a customer wants maximum debugging and observability value from agent traces.

Delegate a read-only Coval evaluation, simulation, monitoring, product-how-to, or troubleshooting subtask to Sofia through the official Coval MCP consult_sofia tool. Use when the user needs Coval-specific FDE judgment, analysis of organization data, metric or test-set recommendations, or a diagnosis grounded in Coval runs and conversations.

Launch a specific Coval evaluation with explicit cases and execution bounds. Use when resources are already selected; for result analysis use quick-eval.

Select and configure a Coval metric for a concrete product criterion, choosing transcript, audio, trace or deterministic evidence and testing the result. Use for metric creation or scoring design, not for final human calibration.

Analyze development-set disagreements between human annotations and one Coval text LLM judge, then propose a focused prompt revision. Use coval-calibrate-metric for independent trust measurements.

Compare before/after Coval runs using matched cases, stable metric versions and inspected conversation evidence. Use to assess a regression or proposed improvement; does not automatically launch or tune anything.

Validate one Coval judge against independent human labels, with grouped development/test separation, class-specific errors and uncertainty. Use for trust claims or calibration; without real labels, prepare review rather than inventing ground truth.