First-time workspace setup and agent-roster operations for a Daimon workspace — working repo, keys, skills, MCP servers, routines, and which changes need an admin.
Keep channels clean after posting. Use when a post, reply or status card of yours is out of date, empty, wrong, duplicated or failed, before posting a correction or a new status, when a thread you opened is finished, and when someone asks you to tidy a thread.
Publish interactive marimo notebooks via the daimon MCP server. Mint a one-time upload URL with create_notebook_upload_url, get the .py into a sandbox file, and curl -X PUT --data-binary it to the URL — source never goes through a tool argument, which…
Work in a person's own Microsoft 365 from Teams (OneDrive and SharePoint files, Excel, mail, calendar, OneNote). Use only when the microsoft_* tools are in your tool list and someone asks about their files, inbox, meetings or notes, or asks to connect or…
Apply PyMC Labs' house style to every artifact you produce — reports, PDFs, slide decks, charts, images, notebooks. Use whenever you generate something a person will look at, before you deliver it.
Read images and large files without destroying the conversation. Use before reading any image — a screenshot you took, a chart you rendered, a photo the user sent — and before reading a file you have not sized. Reading an oversized image ends the conversation…
Publish a finished report as a page a named set of people can read and ask questions about. Covers gathering recipients and a cap, building the one archive the reading room expects, the size discipline for a large bundle, and the mint-then-upload-then-share…
Use when the user asks about team context, project status, decisions, or discussions that live in Slack or Discord, or names a daimon. Routes the question to the right daimon servers and merges their answers.
Answer questions about a published report from the analysis bundle mounted in this session. Covers unpacking the bundle, tracing a number back to its source table, model or raw data, refitting a model on request, and rebuilding and re-uploading the report.…
Mutate data without destroying the evidence — dedup, dtype coercion, missing-value decisions, outlier flagging, category and unit normalisation, joins, pivots and aggregations to a new grain, and columns the source does not contain — appending a row to…
Load whatever the request points at — one CSV or Excel export, twelve related tables, a folder of 500 emails, a 4 GB log you never load, a warehouse table you query in place — and record every source in run/manifest.json with the grain one row represents, the…
Decide whether data is fit to analyze before anyone analyzes it. A phase-1 pass runs in seconds — dtypes, the grain one row claims to represent, referential gaps between tables, plausibility ranges, coverage — and emits run/validation.json with a…
Turn a finished analysis into something a person reads and acts on — lead with the finding that settles the question or moves the decision, trace every number back to a run/findings.jsonl, run/changelog.jsonl or run/manifest.json record, and cut the rest.…
Profile and interrogate data before anyone makes a claim about it — a cleaned frame, a folder of parquet parts, a warehouse table you query in place, or an index frame over a corpus of documents. Summary statistics do not identify a distribution — Anscombe's…