Skip to main content

Deterministic conduct verdicts for live tabletop sessions — CI for running a game. Findings cite the table charter; ambiguity produces silence, never accusations.

Project description

dmcheck

Deterministic conduct verdicts for live tabletop sessions — CI for running a game.

Feed it a session transcript (and optionally an engine event ledger) plus a table charter, and it returns named findings — the player whose question was never answered, the dice roll nobody acknowledged, the turn that began without anyone being told, the spoiler that leaked into the channel, the five-minute dead air. Every finding cites the charter rule it violates, with the evidence attached.

The design contract: a false accusation is the unforgivable bug. A rule fires only when the transcript provably shows the violation — ambiguity produces silence, never noise. The verdict path is model-free and deterministic: same transcript, same findings, every time.

30 seconds to a refereed session

$ pip install dmcheck          # stdlib only, no dependencies
$ dmcheck run session.jsonl --gm "Greta"
{
 "messages": 9,
 "findings": [
  {"rule": "R2", "summary": "unconsumed-roll: a dice result was never followed by any GM message",
   "charter": "roll_ack_within_messages=4",
   "detail": "dice result from DiceBot never followed by a GM message",
   "evidence": {"index": 6, "author": "DiceBot", "content": "Bram rolls 1d20+4: [18] = 22"}},
  ...
 ],
 "counts": {"R1": 1, "R2": 1, "R6": 1, "R7": 1, "R8": 1}
}

Transcript formats: JSONL of {ts, author, content}, or a JSON array of Discord-API-shaped messages ({timestamp, author: {username}, content}) in either order.

The rule set (each one paid for by a real table failure)

Rule Fires when Origin story
R1 a player's question got no GM response within threshold a player asked the DM a lore question; another player ended up answering
R2 a dice result was never followed by any GM message "did I hit?" — a player's successful attack roll sat unacknowledged
R3 an engine event was never narrated to the table the state engine resolved a hit the table never heard about
R4 a turn began and the GM never addressed the actor by name "isn't it her turn?" — asked by a player, which is one player too many
R5 someone acted out of initiative (needs the ledger) engine rejected it silently; the table never knew
R6 a configured hidden term appeared in a GM message a module's secret state names leaked into narration
R7 GM dead air beyond threshold while a player waited 30 seconds reads as thinking; five minutes reads as absence
R8 the session ended with open R1–R3 findings in its tail sessions should end in a defined state — that's what makes the next one possible

These came from running a hybrid table — human and AI players, an AI GM — on Discord, where every one of these failures actually happened and got codified the same week. They apply equally to human GMs: run dmcheck over your own exported game log and see what your table's transcript says.

The charter is config, not code

charters/default.json ships thresholds and conventions derived from a real table's protocol. Override any of it — cue conventions, dead-air tolerance, dice-bot names, hidden-term lists — and version it. A league or organized-play program could publish a charter the way they publish a player's guide; dmcheck then referees any table against it.

$ dmcheck run session.jsonl --charter our-table.json --ledger events.jsonl
$ dmcheck rules            # the rule set with definitions
$ dmcheck --schema         # machine-readable I/O contract

For agents

  • tool.json at the repo root; --schema; exit codes: 0 clean · 1 findings · 2 charter/input unusable.
  • MCP server: dmcheck-mcp (stdio) with tools run and rules.
  • Findings are structured JSON with rule id, charter citation, human-readable detail, and an evidence span — built to be consumed by a GM agent that fixes its own procedure between beats.

What it does NOT do (on purpose)

  • No rules adjudication — whether the attack was legal is srdcheck's job.
  • No character math — that's charactercheck. (srdcheck judges the rules, charactercheck derives the actor, dmcheck referees the table.)
  • No narrative-quality judging — whether the prose was good is taste, and taste is not checkable. dmcheck checks procedure only.
  • No model calls, no scores — deterministic findings per rule, never a blended "DM grade."

Credits

The rule set was distilled from live hybrid (human + AI) table sessions; the Router+Detector pattern in native-gaming-harness independently converged on the same idea, which we take as evidence it's the load-bearing piece. dmcheck is game-system-agnostic and unaffiliated with any publisher.

mcp-name: io.github.chaoz23/dmcheck

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dmcheck-0.1.0.tar.gz (12.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dmcheck-0.1.0-py3-none-any.whl (12.0 kB view details)

Uploaded Python 3

File details

Details for the file dmcheck-0.1.0.tar.gz.

File metadata

  • Download URL: dmcheck-0.1.0.tar.gz
  • Upload date:
  • Size: 12.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.5

File hashes

Hashes for dmcheck-0.1.0.tar.gz
Algorithm Hash digest
SHA256 8e71043ba9af4341f5fb03a1b1b33713c325c53ba434e2bbeb050fba70240964
MD5 0c311ab408621e4c6d5be03b5ec0f3be
BLAKE2b-256 891b57b5b026473dc7efdcdebd8ffd0f305fd6e3e4fab4ca2642f7c068956023

See more details on using hashes here.

File details

Details for the file dmcheck-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: dmcheck-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 12.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.5

File hashes

Hashes for dmcheck-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 c8896d11068552a0737bbaea3993b1a1f063b341681cf444584ffb4be911b6b3
MD5 5e66e75ca9e4562b678da414090a0cba
BLAKE2b-256 ccb4b2cf09d07dd86aae3cd40189f3dd4039c62903988cd57bdbe6db7148ea38

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page