AI Agent Skills

The Arbor research-coordinator protocol: the OBSERVE -> IDEATE -> SELECT -> DISPATCH -> DECIDE cycle over a durable Idea Tree. Preloaded automatically on /auto-research…

The Arbor executor workflow: clone the repo from the git bundle your brief hands you, implement and evaluate exactly ONE hypothesis with the file tools, then report stru…

DECIDE-phase doctrine for an Arbor research run: when to merge, prune, combine, or finalize; how the held-out merge gate works; and the rule that the final report uses T…

CLI-backed web search. Use when the user explicitly invokes this skill, needs CLI-only controls or saved JSON output, or no Parallel web_search MCP tool is available. Wh…

Post-interview review — reconstructs the Q&A from transcript or memory, captures interviewer intel and next-round forecasts, and turns the round into a revision list for…

Runs a realistic mock interview in chat — builds an interviewer persona from the intel file, asks one question at a time with pressure follow-up chains, then scores the…

Author and optionally direct-launch a two-node loop-graph run that compares feasible technical approaches with open-source evidence, primary research, and controlled exp…

Deconstructs a job description and builds interview intelligence — JD-to-evidence matching, company and product research, interviewer profiling, recruiter-vs-team discre…

Mines the candidate's real experience into a reusable story bank — fact-based story cards with sourced numbers, repackaged per role type. Use when the user wants to orga…

Solve coding, debugging, research, analysis, planning, and other agentic work with the smallest verified solution, adaptive effort, minimal tool and token cost, and evid…

Generates industry and role reference reading (行业与岗位通识) for a target job — landscape, role expectations, must-know concepts, high-frequency interview topics, quotable vi…

Writes verbatim, speakable interview scripts (逐字稿) — spoken-style answers the candidate can read aloud, organized in modules with quick-reference anchors, with every num…

A Google Play Store API alternative on fetcher.sh — pay-per-call in USDC via x402, or prepaid credits with a Bearer key, no Google Play Console access. Use when

Research an issue deeply and present all context to the user. but the user writes the code. The LLM investigates code paths, finds relevant files, explains patterns, and…

Handle PR review feedback - understand reviewer comments, research their concerns, and help the user address them. The LLM explains what reviewers want and why; the user…

Skill-driven exploration, targeted reading, web research, and deep-dive analysis for delegate agents. Use when the primary delegates investigation or information gatheri…