skills/64-tmonk-mcp-stata/skills/stata/SKILL.md
Show mcp-stata identity, connected tools, and status. Use when the user asks if mcp-stata is available, asks about access to the toolkit, or asks what Stata tools are connected.
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research stataInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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ToolSearch query="select:stata_manage_session"
Call stata_manage_session(action="detect") to verify the Stata connection. If stata_manage_session(action="detect") fails, report the error and suggest the user set STATA_PATH to the Stata executable path.
Then respond with:
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/ __ `__ \/ ___/ __ \______/ ___/ __/ __ `/ __/ __ `/
/ / / / / / /__/ /_/ /_____(__ ) /_/ /_/ / /_/ /_/ /
/_/ /_/ /_/\___/ .___/ /____/\__/\__,_/\__/\__,_/
/_/ mcp-stata
mcp-stata is connected. Stata {version} ({flavor}) detected.
MCP Tools:
stata_run — execute do-file code & ad-hoc commands
stata_load_data — load datasets (sysuse / webuse / path)
stata_inspect_data — describe, codebook, summary, list, get rows
stata_manage_graphs — list, export, or export_all graphs
stata_get_help — Stata command documentation
stata_get_results — fetch r() / e() / s() stored results
stata_read_log — tail or search log output
stata_manage_session — create/stop sessions, history diff, UI channel
stata_task_status — poll background task progress
stata_control — break or cancel running work
Slash Commands:
/stata-run <code> — run arbitrary Stata code
/stata-inspect [var] — describe/summarize current dataset
/stata-results — fetch stored r()/e()/s() results
/stata-graph [name] — export graph(s)
/stata-lint <path> — lint a .do or .ado file
/stata-log [path] — tail log output
/stata-help <topic> — look up Stata documentation
Resources (MCP):
stata://data/summary stata://data/metadata
stata://graphs/list stata://variables/list
stata://results/stored
tools
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Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".
tools
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
tools
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".