skills/querying-notion-programmatically/SKILL.md
Run Notion MCP searches for pages/blocks and fetch page comments via mcpc-backed Python wrappers. Use when Codex needs deterministic, file-backed Notion queries (filters come later).
npx skillsauth add aufrank/agent-skills querying-notion-programmaticallyInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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python <CODEX_HOME>/skills/querying-notion-programmatically/scripts/notion_query.py --query "AI ML" --prettypython <CODEX_HOME>/skills/querying-notion-programmatically/scripts/notion_comments.py --page-id <page-id-or-url>python <CODEX_HOME>/skills/querying-notion-programmatically/scripts/notion_call_tool.py --tool notion-search --arg query:="AI" --refresh-cacheMCPC_BIN="<TOOL_HOME>" (optional POWERSHELL_EXE).mcpc on PATH; Python 3.11+.mcpc https://mcp.notion.com/mcp login --profile <name> (default default).@notion session, server https://mcp.notion.com/mcp, profile from MCP_PROFILE or default.MCPC_BIN="<TOOL_HOME>" (PowerShell bridge). Optional POWERSHELL_EXE to point at a specific PowerShell.templates/plan.query.json.scripts/notion_query.py for search or scripts/notion_comments.py for comments.results/ (JSON + optional pretty stdout). Reuse files instead of re-running.progress.log if maintaining a trail; keep payloads out of chat.notion-search (pages/blocks/users).--query (required), --query-type internal|user (default internal), --ids-only, --pretty, --output (default results/query.search.json), --session (default @notion), --profile, --server. Writes parsed payload; prints summary or IDs.--page-id (required), --output (default results/comments.json), --session, --profile, --server. Writes comments payload and pretty-prints concise lines.mcp_tools/tools-list.json and mcp_tools/<tool>.json.--tool <name> (required), repeatable --arg key:=value, --output (default results/<tool>.json), --refresh-cache, --session/@notion, --profile, --server. Warns if tool missing from cached list; always writes output JSON.tools-list), mcpc path resolution, file writers. Auto-creates output parent dirs.templates/plan.query.json: Lightweight plan scaffold (query text, query_type, intended outputs). Duplicate/edit per run; keep alongside results/.references/usage.md: Quick reminders on commands, outputs, and resuming.mcp_tools/ (optional, create when needed): Cache tool schemas via mcpc --json @notion tools-get notion-search > mcp_tools/notion-search.json to avoid large payloads in context.results/ (JSON, optional ID text). Keep payloads on disk; cite file paths in chat.results/query.search.json or results/comments.json; re-run scripts only if inputs change.python <REPO_ROOT>/skills/creating-mcp-code-mode-skills/scripts/package_skill.py <REPO_ROOT>/skills/querying-notion-programmatically disttools
Build and execute modular DAG workflows for long-context processing using slice/map/reduce/recurse/compact/filter operators. Use for one-shot batch jobs, standalone map-reduce pipelines, or when the context-dag plugin is not installed. Trigger when input exceeds the model's context window, when reproducible logged pipelines are needed, or when multi-level recursive processing is required. If context-dag is installed, the plugin's bundled dag_runner.py provides the same capability with persistent artifact storage.
documentation
Write in Austin Frank's voice and style. Use this skill whenever generating text that should sound like Austin — strategy docs, charters, proposals, business cases, vision documents, staffing requests, stakeholder updates, cover letters, mission statements, org design documents, or any professional prose where the user wants Austin's distinctive voice. Also use when the user asks to review, edit, or improve a draft for voice consistency, or when they reference "my style", "my voice", "write like me", or "Austin's style".
tools
Use mcpc to interact with the Notion MCP server: connect sessions, search workspace content, fetch pages/databases, and run helper scripts for common Notion actions.
tools
Decide between a scripted workflow and an autonomous agent harness, then scaffold the chosen path. Use when scoping new agentic systems or tool integrations.