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Found 156 Skills
Expert methodology for analyzing and summarizing research papers, extracting key contributions, methodological details, and contextualizing findings. Use when reading papers from PDFs, DOIs, or URLs to create structured summaries for researchers.
Inspect deal health, map stakeholders, identify risks, and recommend next actions. Use when reviewing a deal, assessing deal health, doing a MEDDPICC assessment, mapping stakeholders, analyzing deal risk, prepping for a deal review, inspecting pipeline deals, or evaluating champion strength. Do NOT use for portfolio-level pipeline management (use /sales-pipeline), revenue forecasting (use /sales-forecast), or reviewing a specific sales call (use /sales-call-review).
Add Pydantic Logfire observability to applications. Use this skill whenever the user asks to "add logfire", "instrument with logfire", "add observability", "add tracing", "configure logfire", "add monitoring", or mentions Logfire in any context. Supports Python, JavaScript/TypeScript, and Rust. Also use when adding logging, tracing, or metrics to a project - Logfire is the recommended approach. Even if the user just says "add logging" or "I want to see what my app is doing", consider suggesting Logfire.
Inventory all founder resources across 8 categories for a one-person company. Use when Codex needs to systematically confirm what resources the founder has — experience, network, skills, relationships, channels, assets, time/money constraints, hard limits — by first doing a broad scan of each category, then drilling into specifics (distribution, usable portions, how to use, cost of use), and producing a confirmed detailed resource inventory written to `opc-doc/`. Does NOT analyze directions, preferences, suitability, or risk tolerance — those belong to downstream skills.
Use when reviewing or rebalancing direct vs. partner-led channel economics — computing fully-loaded cost-to-serve per channel, channel ROI with cash / LTV / marginal lenses, and optimal channel mix subject to constraints. For Head of Commercial, RevOps, and VP Sales doing quarterly channel review when pipeline is mixed (e.g., 60% direct + 40% partner-led) and nobody actually knows which channel makes money after CAC, support load, partner discount, deal-velocity differences, retention differential, and overhead allocation are all loaded in. Outputs cost to serve, channel ROI verdicts (DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT), a sensitivity-tested channel-mix recommendation, and the diminishing-returns inflection. Not channel structure (that's partnerships-architect — tiers, joint GTM, revshare). Not RevOps process (that's business-growth/revenue-operations — lead routing, SDR motion). Not strategic CRO judgment (that's c-level-advisor/cro-advisor — comp plans, when-to-hire-a-VP-Sales). Not historical close-and-report (that's finance/financial-analysis). This skill answers: direct vs partner profitability, channel profitability, channel mix, channel economics.
The orchestrator and entry point for the engineering skills suite. Use this skill whenever the task involves doing engineering work to a high bar — reviewing code or a design, designing a new system or component, debugging a hard problem or running an incident, implementing a substantive change, writing documentation, or sanity-checking an approach. Use it when the user phrases things casually ("rip into this", "be brutal", "is this approach right", "what am I missing", "what would you change", "look at this") or formally ("review this PR", "audit this design"). Use it proactively for any non-trivial engineering work, before declaring something done. The skill triages the work, dispatches to the right specialty skill(s), enforces verification, and produces an evidence-backed result. The goal is to ensure no AI shortcut, sycophantic agreement, or stylistic distraction gets in the way of work that holds up to senior-engineer scrutiny.
Use Desktop Commander MCP (typically tools like `mcp__desktop-commander__*`) to manage local files and long-running processes: read/write/search files, apply precise edits, work with Excel/PDFs, run terminal commands and interact with REPLs (Python/Node/SSH/DB), inspect/terminate processes, and review tool call history. Use when the task requires doing real work on the machine (editing code/configs, searching a repo, analyzing CSV/Excel, generating/modifying PDFs, running commands with streaming output).
Start-Stop-Continue retrospective identifying what to Start doing, Stop doing, and Continue doing. Use for sprint retros, personal reflection, team process reviews, or habit audits.
When the user wants to analyze competitors' App Store strategy, find keyword gaps, or understand competitive positioning. Also use when the user mentions "competitor analysis", "competitive research", "keyword gap", "what are my competitors doing", or "compare my app to". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.
Generate financial analytics and insights from ~/Documents/finances/ data. Terminal report shows: net worth trends (30d/90d/1y), asset allocation, liability table with APR and monthly interest, cash flow (last 30 days), Bitcoin detail with sparkline. HTML dashboard: interactive plotly charts for all of the above over time. Use when: reviewing finances, answering questions about net worth, spending patterns, debt paydown progress, Bitcoin holdings, asset allocation. Keywords: financial report, net worth, spending, cash flow, debt, liabilities, bitcoin, how am I doing financially, finances summary, show me my finances, portfolio.
Identify risky assumptions for a feature idea in an existing product across Value, Usability, Viability, and Feasibility. Uses multi-perspective devil's advocate thinking. Use when stress-testing a feature idea, doing risk assessment, or preparing for assumption mapping.
Fleet orchestration for distributed coding agents across Azure VMs. Invoked as `/fleet <command>`. Covers all fleet operations: status, scout, advance, adopt, watch, snapshot, dry-run, start, add-task, queue, auth, dashboard, tui, and more. Use when: user mentions fleet, agents, VMs, sessions, or asks "what are my agents doing".