Data & Analytics skills

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

Build, debug, and optimize Claude API / Anthropic SDK apps. Apps built with this skill should include prompt caching. Also handles migrating existing Claude API code between Claude model versions (4.5 → 4.6, 4.6 → 4.7, retired-model replacements). TRIGGER when: code imports `anthropic`/`@anthropic-ai/sdk`; user asks for the Claude API, Anthropic SDK, or Managed Agents; user adds/modifies/tunes a Claude feature (caching, thinking, compaction, tool use, batch, files, citations, memory) or model (Opus/Sonnet/Haiku) in a file; questions about prompt caching / cache hit rate in an Anthropic SDK project. SKIP: file imports `openai`/other-provider SDK, filename like `*-openai.py`/`*-generic.py`, provider-neutral code, general programming/ML.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

4 business growth agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Customer success (health scoring, churn), sales engineer (RFP), revenue operations (pipeline, GTM), contract & proposal writer. Python tools (stdlib-only).

Analyzes sales pipeline health, revenue forecasting accuracy, and go-to-market efficiency metrics for SaaS revenue optimization. Use when analyzing sales pipeline coverage, forecasting revenue, evaluating go-to-market performance, reviewing sales metrics, assessing pipeline analysis, tracking forecast accuracy with MAPE, calculating GTM efficiency, or measuring sales efficiency and unit economics for SaaS teams.

Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.

Monitors customer health, predicts churn risk, and identifies expansion opportunities using weighted scoring models for SaaS customer success. Use when analyzing customer accounts, reviewing retention metrics, scoring at-risk customers, or when the user mentions churn, customer health scores, upsell opportunities, expansion revenue, retention analysis, or customer analytics. Runs three Python CLI tools to produce deterministic health scores, churn risk tiers, and prioritized expansion recommendations across Enterprise, Mid-Market, and SMB segments.

Financial leadership for startups and scaling companies. Financial modeling, unit economics, fundraising strategy, cash management, and board financial packages. Use when building financial models, analyzing unit economics, planning fundraising, managing cash runway, preparing board materials, or when user mentions CFO, burn rate, runway, fundraising, unit economics, LTV, CAC, term sheets, or financial strategy.

Assembles comprehensive board and investor update decks by pulling perspectives from all C-suite roles. Use when preparing board meetings, investor updates, quarterly business reviews, or fundraising narratives. Covers structure, narrative framework, bad news delivery, and common mistakes.

Generate format-controlled research reports with evidence tracking, citations, source governance, and multi-pass synthesis. This skill should be used when users request a research report, literature review, market or industry analysis, competitive landscape, policy or technical brief. Triggers: "帮我调研一下", "深度研究", "综述报告", "深入分析", "research this topic", "write a report on", "survey the literature on", "competitive analysis of", "技术选型分析", "竞品研究", "政策分析", "行业报告". V6 adds: source-type governance, AS_OF freshness checks, mandatory counter-review, and citation registry. V6.1 adds: source accessibility (circular verification forbidden, exclusive advantage encouraged).

Optimize CLAUDE.md files using progressive disclosure. Goal: Maximize information efficiency, readability, and maintainability. Use when: User wants to optimize CLAUDE.md, information is duplicated across files, or LLM repeatedly fails to follow rules.

Finds and recovers content from Claude Code session history files. This skill should be used when searching for deleted files, tracking changes across sessions, analyzing conversation history, or recovering code from previous Claude interactions. Triggers include mentions of "session history", "recover deleted", "find in history", "previous conversation", or ".claude/projects".

Evidence-driven investigation for network, streaming, and protocol-layer bugs. Use when debugging connection resets (ECONNRESET, HTTP/2 RST_STREAM, INTERNAL_ERROR), SSE or long-polling stalls, fixed-time connection drops, CDN/proxy/CGNAT idle timeouts, or any incident where symptoms do not match the obvious cause. Applies falsification-first methodology — layered isolation experiments to pin down the responsible network layer, env-gated runtime instrumentation for non-invasive observation, and counter-review agent teams to challenge single-cause assumptions. Strongly trigger on "socket closed unexpectedly", "stream interrupted", "ECONNRESET", "HTTP/2 INTERNAL_ERROR", "fails after N seconds", "works sometimes but not always", "upstream silent for X seconds", or any scenario where the investigator might jump to conclusions before evidence. Generalizes to any multi-layer system investigation where assumption-first thinking is the failure mode.

Recover actionable context from local `.claude` session artifacts and continue interrupted work without running `claude --resume`. This skill should be used when the user provides a Claude session ID, asks to continue prior work from local history, or wants to inspect `.claude` files before resuming implementation.