pymc-labs/daimon

workspace-setup

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.

cli-auth

Obtain CLI access tokens via the daimon MCP server's get_cli_token tool.

daimon-context

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.

report-publish

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…

report-reader

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.…

data-cleaning

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…

data-ingestion

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…

data-validation

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…

eda-storytelling

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.…

exploratory-data-analysis

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…

file-handling

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…

marimo-notebooks

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…

pymc-artifact-style

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.