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Torus

Stock research memory for Claude Code, Claude Desktop and Codex. Torus gives Claude a memory for your equity research. Before it answers, Claude sees what you already know about a company: your theses, the sourced facts behind them, its suppliers, customers and competitors, and the ideas you ruled out. New research builds on the old, and every new fact is saved with its source. When a new SEC filing or news story threatens a thesis, Torus warns you: on your desktop as it happens, and in a daily or weekly digest by email, Slack, Discord or ntfy.

Torus graph explorer: the semiconductor value chain with NVIDIA, Micron and AMD theses, an alert from a TSMC filing, and the time slider

Ask Claude "Is NVIDIA still supply-bound?" and it starts from what you already concluded, not from scratch. Torus keeps:

  • the companies you cover and how they connect: suppliers, customers, competitors

  • claims about them, each tied to its source (a 10-K, an earnings call, an article)

  • your investment theses: bullish or bearish, the claims they rest on, and what would break them

  • ideas you ruled out, so you don't research them again

When a 10-K, 10-Q, 8-K or news item lands, Torus works out which of your theses it touches, through which supplier or customer link, and how much it matters. It also keeps the research honest (what's gone stale, what rests on one source, what a skeptic would say) and tracks how your calls did against the market.

Built for analysts, portfolio managers and serious individual investors.

  • Your model, your subscription. Torus never calls an LLM itself. Claude does the reasoning, and cheaper Haiku subagents do the bookkeeping.

  • Local-first. Your research stays in one SQLite file under ~/.torus (override with TORUS_HOME).

  • Time-aware. Every fact records when it was true and when you believed it, so you can ask what you thought on any past date. Nothing is deleted: corrections are new versions.

Torus is a research memory, not financial advice. See CHANGELOG.md for what's in each release.

Pick your app

Torus works in three apps. All of them share one graph on your machine, so you can research in one and pick up in another.

Claude Desktop

Codex (desktop app and CLI)

Claude Code

Prior research recalled before Claude answers

Yes (brief, prompted by the server's instructions)

Yes (brief, prompted by the server's instructions)

Yes, automatically on every prompt (hook)

Sources and claims recorded while researching

Yes (live capture)

Yes (live capture)

Yes (balanced capture, curator fills gaps)

"Torus recorded ..." receipt after each turn

Yes

Yes

Yes

Workflows: onboard, review alerts, challenge, memo...

Prompts in the "+" menu

Torus skills

/torus: commands

Filing and news alerts, audit, scorecard, memos, explorer

Yes

Yes

Yes

Desktop notifications and the digest (they come from the watchers, not the app)

Yes

Yes

Yes

Background Haiku subagents (mapper, curator, challenger)

No: the same steps run in the chat

No: the same steps run in the chat

Yes

Claude Desktop

pip install torus-kg
torus setup

The package is called torus-kg on PyPI; the command it installs is torus. torus setup asks for the email the SEC requires, downloads the SEC ticker list, adds Torus to Claude Desktop's settings (it keeps a .bak copy and leaves your other servers alone), and schedules the filing watchers. Restart Claude Desktop, then try the Onboard companies prompt from the "+" menu with a few tickers.

Codex

The same two commands. torus setup adds [mcp_servers.torus] to ~/.codex/config.toml (or $CODEX_HOME) and installs the Torus skills (torus-research, torus-onboard, torus-review and so on) under ~/.codex/skills. If you already wrote a [mcp_servers.torus] entry yourself, setup leaves it as it is. Restart Codex, then ask it to onboard your tickers.

Claude Code

See Getting started below. torus setup also prints the two /plugin commands.

torus setup configures the apps it finds; pass --claude-desktop or --codex to configure one anyway, or --no-codex / --no-claude-desktop to skip one. torus doctor checks each app's entry and that the server starts, and torus doctor --fix repairs what it can.

Just looking? torus demo builds a small sample graph (NVIDIA, TSMC, Micron and AMD theses, an alert from a TSMC filing, the semis starter pack) in its own folder, TORUS_HOME/demo, and opens it in the explorer. Your own graph is untouched, and every piece of sample research is marked [demo].

Related MCP server: Chronos MCP

How it works

How Torus works: you ask about a company; Torus recalls earlier research; Claude researches and records sourced claims and theses in the Torus graph. While you're away, Torus watches new SEC filings and news, raises an alert on the thesis it affects, and you review it.

Why this helps. Research done in chat is usually thrown away: the next session starts from scratch, and nothing connects new information to what you already concluded. Torus keeps the working parts of the research, not just the final report:

Without Torus

With Torus

Every session re-reads the same filings and rediscovers the same facts

Each session starts from earlier theses, claims and ruled-out ideas

A new tool starts empty, so it's useless for weeks

/torus:onboard maps your companies' suppliers, customers and competitors from their 10-Ks in minutes

A report says "TSMC capacity is the constraint", but not where that came from

Every claim links to its source, with a verbatim quote, a confidence and the date it was true

A TSMC filing arrives and nobody notices that it undermines your NVIDIA view

Impact analysis follows supplier and customer links and raises an alert on that thesis

Every routine filing pings you, so you stop looking

Alerts weigh what kind of event it is and whether it matches what you said would break the thesis

The changes in a 150-page 10-K are buried

Torus lists the new, dropped and reworded risk-factor sentences since the last filing

Old conclusions get overwritten, and wrong ones linger

Every change is versioned; the audit flags what's stale or thinly sourced; undo keeps history

Dead ends get explored again

Ruled-out ideas are recalled alongside the theses

Nobody checks whether high-conviction calls were actually right

The scorecard tracks each thesis against its stock and measures your calibration

Getting started (about 5 minutes)

You need Python 3.11+ and Claude Code.

1. Install the torus command. The plugin's hooks and MCP server run it, so this step is required:

pip install torus-kg

2. Set it up:

torus init --refresh-reference --contact you@example.com   # SEC ticker list (the SEC asks for an email)
torus config set sec_contact you@example.com               # used when reading and watching filings
torus doctor                                               # check that everything is in order

3. Add the plugin in Claude Code:

/plugin marketplace add sekhar14/torus
/plugin install torus@torus

You'll be asked for a capture mode:

Mode

What Claude records while researching

The curator (Haiku) records later

balanced (default)

theses, key claims with sources, ideas ruled out

supporting claims, extra sources, links

live

everything

anything missed

curator

theses and ideas ruled out

everything else

4. Tell Torus what you cover (recommended). In Claude Code:

/torus:onboard NVDA AMD TSM AVGO

or from a portfolio or watchlist export: torus onboard --file portfolio.csv (any CSV with a ticker or symbol column), then /torus:onboard to finish the mapping. Torus adds the companies, watches their SEC filings, suggests matching starter packs, and a Haiku subagent maps each company's suppliers, customers, competitors and customer concentration from its latest annual report, citing the filing.

5. Keep the watchers running:

torus schedule install    # checks filings, news and prices every hour

This uses Task Scheduler on Windows, launchd on macOS and cron on Linux.

6. Research as usual, e.g. "Is NVIDIA still supply-bound? Check TSMC's CoWoS plans." The next time you mention NVIDIA, Claude sees the earlier thesis, claims and ruled-out ideas before it starts. After each turn Torus tells you what it recorded ("Torus recorded 1 thesis, 3 claims and 2 sources this turn"), and /torus:undo reverts anything you don't want.

What you can ask

You don't need to remember commands; ask in plain words and Claude uses the right Torus tools.

You say

What happens

"Is NVIDIA still supply-bound?"

Claude starts from your earlier NVIDIA research, then records new claims, sources and the updated thesis

"What changed in TSMC's latest 20-F risk factors?"

Torus lists the new, dropped and reworded sentences against last year's filing

"Add this earnings call transcript to Torus"

The transcript becomes sourced claims linked to the theses it bears on

"Any news that affects my theses?"

Open alerts, each with the path that explains it, judged one thesis at a time

"What happened this week?"

The digest: new alerts by thesis, status and confidence changes, theses coming due, scorecard moves

"What happens to my theses if TSMC's Arizona fab is delayed a year?"

Every thesis the event would reach, through which links, and the likely direction

"Poke holes in my Micron thesis"

A skeptic subagent researches the counter-case; you approve any risks it proposes

"Is my research still current?"

The audit: expired assumptions, theses past their horizon, single-source claims, conflicts

"How have my calls done?"

Returns against SPY in each thesis's direction, outcomes, and how calibrated your confidence is

"Write up my NVIDIA thesis to share"

A memo with every claim traced to its source

"Undo what you just recorded about AMD"

Those records are retracted or archived; history keeps them

Commands in Claude Code

Command

What it does

/torus:onboard

Start covering companies: watch them, seed starter packs, map their links from 10-Ks

/torus:status

Theses at risk, open alerts, recent changes, graph health

/torus:review

Judge open alerts: did the event support, weaken or break the thesis?

/torus:ingest

Read a filing, transcript, PDF or page into sourced claims; or what changed since the last filing

/torus:whatif

Which theses would a hypothetical event reach, and how? Records nothing

/torus:challenge

A devil's-advocate subagent stress-tests a thesis and proposes risks and triggers

/torus:audit

Find expired, thinly sourced or conflicting research and theses past their horizon

/torus:scorecard

How your theses did against a benchmark, and whether your confidence is calibrated

/torus:memo

Write a thesis up as a sourced memo (Markdown and HTML)

/torus:undo

See what recent sessions recorded and revert any of it

/torus:distill

Have the Haiku curator add past sessions' findings to the graph

/torus:explore

Open the visual graph explorer

Behind them, the MCP server gives Claude 45 tools, from brief, recall and record_claim to filing_diff, whatif, digest and scorecard. Claude Desktop and Codex see 33 of them by default (the analyst toolset): the queue and low-level graph tools are hidden. Set TORUS_TOOLSET=full in the server's env to show them all.

Claude Desktop and Codex in detail

Neither app loads the Claude Code plugin, so the MCP server carries the workflow itself. When TORUS_HARNESS is claude-desktop or codex (torus setup sets it):

  • Instructions. The server tells the model to call brief with the user's question before researching a company, to record sources and claims as it goes (capture mode live, since no curator reads the chat later), and to end each turn with a "Torus recorded ..." receipt. The wording is model-neutral, since Codex runs OpenAI models.

  • Workflows. Each /torus: command is also an MCP prompt (Claude Desktop's "+" menu) and a Codex skill, rendered from the same source in src/torus/workflows/. Steps a Claude Code subagent would do (mapping companies from their 10-Ks, arguing the counter-case) run in the chat instead.

  • Save this chat. With no curator, the Save this chat to Torus prompt (or asking "save this chat to Torus") records whatever the chat found and didn't record yet.

  • Undo. Records are tracked per chat, so "what did you record?" and "undo that" work as in Claude Code (recent_records, undo_records).

Claude in a web browser, ChatGPT and Copilot can't use Torus: they only reach MCP servers at a public address, and Torus runs on your machine.

Configuring by hand. torus setup writes these for you. In Claude Desktop (Settings > Developer > Edit Config; %APPDATA%\Claude\claude_desktop_config.json on Windows, ~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "torus": {
      "command": "/full/path/to/torus",
      "args": ["serve"],
      "env": { "TORUS_HARNESS": "claude-desktop" }
    }
  }
}

In Codex (~/.codex/config.toml):

[mcp_servers.torus]
command = "/full/path/to/torus"
args = ["serve"]

[mcp_servers.torus.env]
TORUS_HARNESS = "codex"

Use the full path (where torus on Windows, which torus on macOS and Linux): desktop apps don't see your shell's PATH. If you set TORUS_HOME, add it under env so every app shares one graph. Other env settings: TORUS_CAPTURE_MODE (live, balanced, curator) and TORUS_TOOLSET (analyst, full). Other MCP clients (Cursor, VS Code and so on) may work with the same entry, but they aren't tested.

Reading SEC filings

Torus reads filings from EDGAR for Claude, so research cites primary sources instead of summaries of them:

  • By section. A 10-K, 10-Q or 20-F is split into its items, so Claude can read just business, risk_factors, mdna, legal, market_risk or financials (or an item number), page by page. Any earlier filing of the same form is available too.

  • What changed. Torus compares a section with the same section of the previous filing and returns the new, dropped and reworded sentences, most rewritten first.

  • Cited. Claims from a filing carry the filing's URL as evidence (kind filing) and a verbatim quote, and count as primary sources in the audit and the challenge.

Filings are downloaded once and cached as text in TORUS_HOME/sources/edgar. Reading them needs sec_contact set: the SEC asks every client for a contact email.

The visual explorer

torus explore                 # the whole graph
torus explore NVDA --hops 2   # NVIDIA and everything within two links
torus explore --no-open       # write the file without opening a browser

This writes a single self-contained HTML file (default ~/.torus/explorer.html) and opens it in your browser. It works offline and needs nothing installed, so you can share the file.

A thesis selected in the explorer: its alert with the paths that explain it, the claims it rests on with sources, its trigger and history

The screenshots use the semis starter pack plus illustrative [demo] research (scripts/seed_demo.py). In the one above, the [demo] NVIDIA thesis is selected. A TSMC 8-K raised an alert on it, and the panel shows why: the thesis has a trigger on TSMC, an assumption claim that names TSMC, and TSMC supplies NVIDIA, the thesis's subject. It also shows how the score was built: a strong graph connection, a low-materiality 8-K item (8.01, "other events"), boosted because the filing's wording matches the thesis's trigger.

  • Nodes: companies are blue circles; darker means you have research on them. Theses are squares coloured by status (green active, amber at risk, red broken). Events are diamonds, red when they have an open alert.

  • Lines: solid arrows mean supplies, dashed lines mean competes with, and a thick red line is an alert from an event to a thesis. Faint lines come from a starter pack and haven't been confirmed by your research yet.

  • Click any node for details. A company shows its links, theses, recent claims with sources, and ideas ruled out. A thesis shows what it rests on, its triggers, its history and its alerts, with the path that explains each one.

  • Move around: drag nodes, scroll to zoom, drag the background to pan, and press Fit to reset. Double-click a node to release it.

  • Search by name or ticker. Filters hide theses, events, competitor links or starter links.

  • Go back in time: drag the slider at the bottom to see the graph as it stood on an earlier date (what Torus knew then, and each thesis's status at the time), or press Replay to watch the research grow. Links retired since then don't reappear.

  • Link to a node or a date: add #select= and a name or ticker to the file's address, e.g. explorer.html#select=NVDA, to open with that node selected, or #at=2026-09-20 to open the graph as it stood that day. Combine them with &: #select=NVDA&at=2026-09-20.

The explorer set to 20 September: only the research recorded by then, with the AMD thesis still active (it broke later) and the TSMC alert

The same demo graph as it stood on 20 September: the starter pack wasn't added yet, the AMD thesis was still active (it broke in October), and the TSMC alert had just arrived.

The file is a snapshot. Run torus explore again after new research.

Starter packs and graph tools

Starter packs give impact analysis a web of widely reported links from day one. Each link is marked as a starter link until research confirms it, and never overrides a link your research recorded.

Pack

Covers

Companies

Links

semis

Chip equipment, foundry and memory, chip designers, their big buyers

23

52

software

Hyperscale clouds and the software that runs on them; databases, apps, observability, security

19

34

banks

Large US banks, card networks and issuers, payments, bank technology

18

25

energy

Integrated majors, US producers, oilfield services, refiners, pipelines, LNG

19

26

pharma

Drugmakers and biotechs, lab suppliers, wholesalers, pharmacy benefit managers

20

25

torus graph packs                      # the packs above
torus graph seed software              # add one (safe to repeat)
torus graph neighbors TSM --hops 2     # links around a company
torus graph paths ASML AMD             # how two companies connect: ASML -SUPPLIES-> TSMC -SUPPLIES-> AMD

Claude has the same tools through MCP (neighbors, find_paths, impact, seed_starter_pack). When research re-records a starter link, it becomes yours.

Watchers: filings and news become alerts

torus watch run checks once:

  • SEC EDGAR: new filings (8-K, 10-Q, 10-K, 20-F, 6-K, ...) by watched companies. New 10-K, 10-Q and 20-F events also say what changed in the risk factors since the previous filing ("Risk factors: 12 new, 8 reworded, 3 dropped sentences. New: ...").

  • RSS/Atom feeds: items that mention companies already in your graph.

  • Prices: daily closes for theses on the scorecard.

Each new item becomes an event. Torus then walks the graph (suppliers, customers, competitors) and opens alerts on theses it may affect. Review them with /torus:review. At the end of the pass, strong new alerts show up as desktop notifications, and a scheduled digest goes out if one is due.

torus watch add NVDA                            # optional: onboarded companies and open theses' companies are watched automatically
torus feed add https://example.com/semis.rss --name "Semis wire"
torus watch list                                # what is watched, and why
torus watch run                                 # one pass; exit code 1 if any source failed
torus schedule install                          # run it every hour; --every 6 for every 6 hours
torus schedule status                           # or: torus schedule remove

The first check of a company or feed looks back 7 days. After that, only new items are processed.

Alerts that matter

A routine supplier 10-Q shouldn't interrupt you; a bankruptcy filing should. Each alert scores graph score × materiality × (1 + trigger match):

  • graph score: how closely the event's companies connect to the thesis: its subject, a company its assumptions name, or a supplier, customer or competitor one or two links away.

  • materiality: what kind of event it is. 8-K items are weighted (bankruptcy 1.0, results 0.9, material agreement 0.8, shareholder vote results 0.1), a 10-Q is 0.4, and news wording raises or caps it ("export controls" 0.9, "3 stocks to buy" 0.2). Events you add yourself count fully.

  • trigger match: how much of one of the thesis's triggers the event's wording covers, so "TSMC delays CoWoS expansion" boosts a thesis whose trigger is "CoWoS capacity slips". Write triggers in the words a headline would use.

Each alert shows how its score was built, with a label to read it by: strong (1.0 and up, as much as a fully material event about the thesis's own subject), moderate (0.5 and up) or weak. To tune them:

torus alerts list                               # open alerts and how each scored
torus alerts stats --days 90                    # share judged related, by source, form, hops, materiality
torus alerts threshold 0.3                      # global minimum score (default 0.2)
torus alerts threshold 0.5 --thesis ID          # per thesis
torus alerts mute ID --entity TSM --form 10-Q   # no alerts on this thesis for TSMC 10-Qs
torus alerts mutes                              # list mutes; torus alerts unmute MUTE_ID

/torus:review suggests a mute when a thesis keeps getting the same kind of unrelated alert.

Alerts that reach you

The watchers run every hour, but an alert is no use if you only see it the next time you open a chat. Torus tells you in two ways.

Desktop notifications

When torus watch run raises a strong alert, you get a notification:

Torus: strong alert on NVIDIA data-center growth is supply-bound TSMC 8-K: CoWoS capacity expansion delayed (and 1 more)

  • One notification per thesis, at most three per pass. If more theses are hit, the third sums up the rest.

  • Only alerts from the last 24 hours, so upgrading or turning notifications on never replays old ones.

  • Windows shows a toast, macOS uses Notification Center (osascript), Linux uses notify-send. Nothing extra to install. On Linux the cron job finds your desktop session on its own.

torus notify test                    # check that notifications show up on this machine
torus config set notify moderate     # strong (default), moderate or off
torus watch run --no-notify          # one pass without notifications

torus doctor checks that the platform's notification tool is there.

The digest

torus digest writes what happened since a date, most urgent first:

  1. New alerts, grouped by thesis, with strength, score, link and whether they were judged

  2. Thesis changes: status changes and confidence moves of 10 points or more

  3. Coming due: open theses past their horizon or due within 30 days

  4. Research health: audit counts and the top high findings

  5. Scorecard: the biggest moves since then, in each thesis's direction

  6. Activity: claims, theses and events recorded

torus digest                         # the last day, as Markdown and HTML in TORUS_HOME/digests
torus digest --since 2w --open       # 12h, 1d, 2w or a date (YYYY-MM-DD); open the HTML
torus digest --json                  # the same data as JSON

In any app, ask "what happened this week?" and Claude calls the digest tool.

Sending the digest

Nothing is sent until you set a destination. Then pick a schedule; the hourly watcher run sends the digest when it's due, so there's no second scheduled task.

torus config set digest daily                # off (default), daily or weekly
torus config set digest_hour 8               # local time (default 8)
torus config set digest_weekday mon          # for weekly (default mon)

A webhook (Slack, Discord, ntfy or anything that takes JSON):

torus config set digest_webhook https://hooks.slack.com/services/...
torus config set digest_webhook https://ntfy.sh/your-private-topic   # push to your phone with the ntfy app

The format comes from the address: Slack gets plain text, Discord and ntfy get Markdown, and any other URL gets the digest as JSON. For a self-hosted ntfy server, set digest_webhook_format ntfy. Long digests are cut at a whole section, with a pointer to the full file. Webhook URLs contain a secret token, so Torus shows them masked (https://hooks.slack.com/.../AbCd) and leaves them out of torus export.

Email through your own SMTP server, with Gmail as the example:

torus config set digest_email_to you@example.com
torus config set smtp_host smtp.gmail.com
torus config set smtp_user you@gmail.com
torus digest email-password                  # asks for the password (for Gmail, an app password)

The password is never stored in the database. torus digest email-password saves it to TORUS_HOME/secrets/smtp_password, a file only you can read, or you can set TORUS_SMTP_PASSWORD instead. Torus only sends over an encrypted connection: STARTTLS on port 587 (the default) or TLS on port 465.

torus digest test-send                       # a short test message to each destination
torus digest --send                          # send now: everything since the last digest sent

A digest with nothing new isn't sent (digest_send_empty on changes that). torus doctor shows the schedule, where the digest goes, when it was last sent and the last error.

Keeping the research honest

  • Audit (torus audit, /torus:audit): assumptions past their validity date, theses past their horizon or unchanged for 90 days, assumptions resting on one non-filing source or on an unsourced opinion, claims about the same company that may conflict, inferences built on retracted claims, and starter links that alerts depend on but research never confirmed. Claude walks through the findings with you and fixes the ones you agree to. In the terminal, long runs of low findings of one kind (say, every starter link after seeding a pack) are summarised after the first three; torus audit --all lists them all.

  • Horizons are dates. A thesis's horizon ("12m", "18 months", "FY2026", "Q3 2026", "2027-06-30") is read as a due date, so the audit and the scorecard know when it's up.

  • Challenge (/torus:challenge): Torus lists a thesis's weak points (thin or expiring assumptions, strong supplier or customer links it never mentions, triggers that can't fire, opposing theses and verdicts) and a devil's-advocate subagent researches the counter-case. You approve any risks or triggers it proposes; it never changes the thesis itself.

  • What if (torus whatif "TSMC fab outage halts CoWoS" TSM, /torus:whatif): runs the alert logic on a hypothetical event and shows every thesis it would reach, through which links, and whether it would raise an alert. Nothing is recorded.

  • Receipts and undo (/torus:undo): after each turn Torus says what it recorded. Undo retracts claims (or restores the version a correction replaced), archives theses the session created, retires links (restoring a starter link it replaced) and withdraws ruled-out ideas. History keeps everything, so "what did we believe on date X" still works.

Scorecard and calibration

Track a thesis against its stock and see how the call is doing:

torus scorecard track THESIS_ID           # default: the subject's ticker, entry = the close when recorded
torus scorecard --refresh                 # fetch closes, then show returns and calibration
torus scorecard outcome THESIS_ID right   # right, wrong, unclear or clear; your call beats the automatic one
torus scorecard import NVDA prices.csv    # load closes yourself (date,close)

Each tracked thesis shows its return against a benchmark (SPY unless set) in the direction of its stance, so a bearish thesis gains when the stock lags, and its worst drawdown. Theses get an outcome when you mark them confirmed or broken, or by price when they reach their horizon. Calibration compares your initial confidence with how often you were right: a Brier score (0 is perfect; always saying 50% scores 0.25) and a table by confidence band, e.g. "your 80%+ calls were right 6 times out of 10". It covers every decided thesis, whether or not it's tracked against a price, and says so when fewer than 10 are decided: below that it's an anecdote, not a measure.

Prices come from Yahoo Finance's public chart endpoint, which needs no key but is unofficial and can change. If it fails, import closes from a CSV, or set price_source to none. The scorecard is a record of your own calls, not advice.

Memos

torus memo THESIS_ID --open (or /torus:memo) writes a thesis up as Markdown and a standalone HTML page in TORUS_HOME/memos: what it rests on, each claim with its sources and verbatim quotes, the claims inferences derive from, triggers, the events since and how they were judged, ruled-out ideas, the scorecard and the full history. In Claude Code, /torus:memo also writes a short summary from what the memo says.

Automation

  • Watchers on a schedule: torus schedule install (see above). torus doctor warns when companies are watched but nothing runs the watchers. Each run also sends the notifications and the scheduled digest (Alerts that reach you).

  • Distilling sessions: research sessions are queued when they end, and the Haiku curator adds what Claude didn't record. With auto_distill at ask (the default), Claude offers to run /torus:distill when sessions are waiting. Set it to on and a background curator runs (claude -p on Haiku, Torus tools only) when a session ends; this uses your subscription. One curator runs at a time, and its own session is never captured.

Settings

torus config set KEY VALUE (omit the value to reset; torus config get KEY to read):

Key

Default

What it does

sec_contact

Email sent to the SEC in the User-Agent (required for filings)

alert_threshold

0.2

Minimum alert score for theses without their own

auto_distill

ask

ask: Claude offers /torus:distill when sessions are queued. on: a background Haiku curator runs when a session ends. off: neither

capture_receipts

on

Tell you after each turn what Torus recorded

filing_diffs

on

Summarise risk-factor changes in new 10-K/10-Q/20-F events

benchmark

SPY

What the scorecard measures theses against

price_source

yahoo

yahoo or none

notify

strong

Desktop notifications for new alerts: strong, moderate or off

digest

off

Send a digest from the watcher runs: off, daily or weekly

digest_hour

8

Hour (0-23, local time) the digest goes out

digest_weekday

mon

Day of a weekly digest (mon to sun)

digest_send_empty

off

Send a digest even when nothing is new

digest_webhook

Slack, Discord, ntfy or JSON webhook URL (shown masked, not exported)

digest_webhook_format

auto

auto (from the URL), slack, discord, ntfy or json

digest_email_to

Address(es) to email the digest to, comma-separated

digest_email_from

smtp_user

From address

smtp_host

SMTP server

smtp_port

587

587 with STARTTLS, or 465 with TLS

smtp_user

SMTP login; the password goes in with torus digest email-password

What leaves your machine

Torus keeps your research local. It reads from these:

  • SEC EDGAR (sec.gov): the ticker list, watched companies' filing lists, and filings Claude reads or the watcher diffs. Your sec_contact email is sent as the User-Agent, as the SEC requires.

  • Your RSS/Atom feeds, if you add any.

  • Yahoo Finance, for daily closes of tracked tickers and their benchmark, if any thesis is on the scorecard and price_source isn't none.

And it sends research out only where you tell it to:

  • Your webhook (digest_webhook), if you set one: the digest's text, which includes thesis titles, alert and event titles, audit findings and scorecard moves.

  • Your SMTP server (smtp_host), if you set up email: the same digest, to digest_email_to.

Desktop notifications stay on your machine.

Claude's own web research goes through the app you use, as usual.

Maintenance

torus doctor                  # health check (schema, integrity, search index, hooks, watchers, schedule, notifications, digest)
torus doctor --fix            # fix what it flags (see below)
torus doctor --repair         # only rebuild the search index and close duplicate links
torus export                  # back up everything to TORUS_HOME/exports/*.jsonl
torus import backup.jsonl     # restore into a fresh TORUS_HOME
torus status                  # row counts and queue state

torus doctor --fix rebuilds a broken search index, closes duplicate links, saves the SEC email (it asks, or pass --contact EMAIL), downloads the SEC ticker list when it's missing or more than 30 days old, installs the watcher schedule when companies are watched but nothing runs the watchers, and rewrites a broken Claude Desktop or Codex entry (keeping a backup, and leaving a Codex entry you wrote yourself alone). It says what it did and what it skipped, then checks again.

Upgrading migrates the database automatically the next time any torus command opens it. Hook activity is logged to ~/.torus/logs/hooks.log, background curator output to ~/.torus/logs/curator.log. Hooks never block or fail your session.

Development

python -m venv .venv
.venv/Scripts/python -m pip install -e ".[dev]"   # .venv/bin/python on macOS/Linux
.venv/Scripts/python -m pytest                    # unit + integration (no network)
.venv/Scripts/python -m pytest -m perf tests/perf # performance checks on a 100k-claim graph

License

Apache License 2.0. See LICENSE.

Torus is a research memory, not financial advice.

Available Tools

45 tools
add_eventA

Record an event and raise alerts on theses it may affect (through the companies involved and their suppliers, customers and competitors).

Inputs: title (required), entities (required), occurred_at (required), uri, +3 more. Returns: event, alerts, created

alert_statsA
Read-only

How useful alerts have been: verdicts, and the share judged related (precision) by source, form, hops and materiality.

Inputs: since. Returns: open, alerts, judged, by_form, +6 more

auditA
Read-only

Health check of the research graph: expired or thinly sourced assumptions, theses past their horizon or gone stale, claims that may conflict, unconfirmed starter links, orphans. Each finding suggests a fix.

Inputs: stale_days. Returns: counts, findings, markdown, generated_at

briefA
Read-only

One-call briefing at the start of a turn: spots known companies in text, recalls prior theses, claims, open alerts and ruled-out ideas about them, and returns the graph digest.

Inputs: text. Returns: digest, recall, context, detected_entities

complete_distillationA

Finish a leased distillation job (or hand it back if it failed).

Inputs: summary (required), queue_id (required), failed. Returns: status, queue_id, remaining

complete_mappingA

Finish a leased mapping job (or hand it back if it failed).

Inputs: summary (required), queue_id (required), failed. Returns: status, queue_id, remaining

digestA
Read-only

What happened in the research over the last days: new alerts by thesis, thesis status and confidence changes, theses coming due, audit counts, scorecard moves and activity. markdown is ready to show.

Inputs: since_days. Returns: moves, since, until, activity, +7 more

filing_diffA
Read-only

What changed in a section of a company's latest filing against the previous one of the same form: new, dropped and reworded sentences.

Inputs: company (required), form, section, max_items. Returns: added, latest, changed, company, +7 more

filing_textA
Read-only

Read a company's SEC filing as text, by section, from EDGAR (cached). Long sections come in pages: pass next_offset back as offset.

Inputs: company (required), form, index, offset, +2 more. Returns: cik, url, form, text, +8 more

find_pathsA
Read-only

How two entities are connected, e.g. ASML -SUPPLIES-> TSMC -SUPPLIES-> AMD. Shortest and most confident paths first.

Inputs: source (required), target (required), max_hops, relations. Returns: paths, texts, source, target

get_entityB
Read-only

Resolve an entity and list its current relations.

Inputs: entity (required). Returns: entity, relations, resolved_by

impactB
Read-only

Dry run: which theses would an event on these entities affect, and why? Records nothing.

Inputs: entities (required), occurred_at. Returns: hits

list_alertsA
Read-only

Alerts raised by events on theses, highest score first. Each shows how its score was built: graph score x event materiality x (1 + trigger match).

Inputs: status, grouped, thesis_id. Returns: alerts, groups

list_watchesB
Read-only

What the watchers follow: the watchlist, open-thesis entities, feeds.

Inputs: no named parameters. Returns: feeds, entities

merge_entitiesB

Fold a duplicate entity into the one to keep; its links move over.

Inputs: keep (required), reason (required), duplicate (required). Returns: id, kind, name, attrs, +4 more

neighborsA
Read-only

The entity's neighbourhood: companies within hops links (suppliers, customers, competitors...), the links among them, and theses about them.

Inputs: entity (required), hops, valid_at, relations. Returns: edges, focus, nodes

next_distillationA

Lease the oldest research session waiting to be distilled into the graph.

    Returns its transcript digest, what was already recorded (don't duplicate
    it), the sources the agent looked at, and existing theses on its entities.
    Until `complete_distillation`, new records are attributed to that session.

Inputs: transcript_chars. Returns: job, remaining

next_mappingA

Lease the next onboarded company to map from its annual report. Until complete_mapping, links you record are marked as curator links.

Inputs: no named parameters. Returns: job, remaining

onboardA

Start covering companies: add them, watch their filings, suggest starter packs, and queue a mapping job for each (run by the company-mapper subagent, which reads their annual reports and records suppliers, customers and competitors).

Inputs: tickers (required), watch. Returns: companies, unresolved, suggested_packs, mapping_jobs_queued

open_explorerB

Write the interactive graph explorer HTML file (under TORUS_HOME/explorer.html) and open it in the user's browser.

Inputs: hops, focus, open_browser. Returns: path, links, events, opened, +2 more

recallA
Read-only

Prior theses, claims and rejected hypotheses about entities and/or a question.

Call this before starting research so you build on earlier work.

Inputs: as_of, limit, query, entities. Returns: as_of, query, alerts, claims, +4 more

recent_recordsA
Read-only

List what the most recent research sessions recorded (claims, theses, relations, sources, ruled-out ideas), newest session first, with each session's id and whether each record can still be undone. Read-only. Use it when the user asks what Torus saved, then pass the session id and records to undo_records to revert the unwanted ones.

Inputs: sessions. Returns: sessions

record_claimA

Save one finding about one or more entities, tied to its sources.

    Record the source first with `record_evidence` and pass its id. A fact or
    metric without supporting evidence_ids is rejected, as is an inference with
    neither evidence nor derived_from. Returns the new claim with its id, which
    theses (`record_thesis`) and relations (`record_relation`) can cite. To fix
    an existing claim use `supersede_claim`, not a second record_claim.

Inputs: text (required), claim_type (required), confidence (required), entities, +6 more. Returns: id, text, status, entities, +12 more

record_evidenceB

Record a source. Re-recording the same URI returns the existing record.

Inputs: uri (required), kind, quote, title, +2 more. Returns: id, uri, kind, quote, +7 more

record_rejected_hypothesisB

Record an idea that was checked and ruled out, so it isn't re-explored.

Inputs: text (required), reason (required), entities. Returns: id, text, reason, entity_ids, +3 more

record_relationA

Link two entities, e.g. TSMC SUPPLIES NVIDIA. Re-recording an existing link updates it (confidence, backing claim, dates) instead of duplicating it.

Inputs: rel (required), source (required), target (required), confidence (required), +3 more. Returns: id, rel, dst_id, source, +9 more

record_thesisA

Save a new investment thesis and the claims it rests on.

    Record the claims first with `record_claim` and pass their ids. Torus uses
    the assumptions, subject and triggers to decide which new filings and news
    threaten the thesis and raise alerts. Returns the thesis with its id and
    status (active). To change an existing thesis use `update_thesis`; to log
    an idea you rejected use `record_rejected_hypothesis`.

Inputs: title (required), stance (required), statement (required), confidence (required), +6 more. Returns: id, title, claims, stance, +15 more

resolve_alertA

Judge an alert after reading the event and the thesis's claims; the thesis is updated accordingly and the change logged with the alert.

Inputs: verdict (required), alert_id (required), rationale (required), status, +1 more. Returns: alert, event, thesis_title, thesis_status, +1 more

retract_claimB

Withdraw a claim that turned out to be wrong (kept in history).

Inputs: reason (required), claim_id (required). Returns: id, text, status, entities, +12 more

scorecardB

How tracked theses have done against their benchmarks, their outcomes, and calibration: did the user's confidence match how often they were right?

Inputs: refresh. Returns: theses, markdown, calibration, generated_at

seed_starter_packA

Add a curated starter pack of companies and supplier/competitor links. Never overrides links research recorded.

Inputs: pack (required). Returns: pack, links_added, companies_added, links_already_present

set_thesis_outcomeA

Record whether a thesis turned out right, wrong or unclear (overrides the automatic outcome; used for calibration).

Inputs: outcome (required), thesis_id (required), note. Returns: note, method, outcome, thesis_id, +2 more

supersede_claimB

Correct a claim: the old version stays in history, the new one is current.

Inputs: reason (required), claim_id (required), text, confidence, +1 more. Returns: id, text, status, entities, +12 more

thesis_memoB

Write a thesis up as a memo (Markdown and a standalone HTML page): what it rests on with sources and quotes, triggers, events and verdicts, ruled-out ideas and history. Saved under TORUS_HOME/memos.

Inputs: thesis_id (required). Returns: markdown, html_path, markdown_path

thesis_weak_pointsA
Read-only

Where a thesis is weakest: thin or expiring assumptions, strong supplier or customer dependencies it never mentions, triggers that can't fire on events, and opposing views already in the graph. Input for /torus:challenge.

Inputs: thesis_id (required). Returns: title, stance, subject, statement, +7 more

timelineA
Read-only

History of one entity, oldest first: claims recorded, corrected or retracted about it, theses on it created or changed, and events (filings, news) that name it. Each change has a time, kind, object id and one-line summary. Use it to see how the view on a company evolved; use what_changed for the whole graph and get_entity for its current links.

Inputs: entity (required), since, until. Returns: since, until, changes, entity_id

track_thesisB

Put a thesis on the scorecard: its return against a benchmark from an entry price and date, in the direction of its stance.

Inputs: thesis_id (required), stop, ticker, benchmark, +2 more. Returns: id, title, claims, stance, +15 more

undo_recordsA

Revert records the user doesn't want: claims are retracted (corrections go back to the earlier version), theses the session created are archived, links retired, ruled-out ideas withdrawn. History keeps everything.

Inputs: records (required), session_id (required), reason. Returns: outcomes

unwatchA

Stop watching a company you added with watch. Removes it from the explicit watchlist only: a company that is the subject or a trigger entity of an open thesis is still followed. Nothing in the graph is deleted. Returns the updated watch list, as list_watches does.

Inputs: entity (required). Returns: feeds, entities

update_thesisA

Revise a thesis: status, confidence, the claims it rests on, and its triggers, in one atomic step. Everything is kept in its history.

    Also tunes its alerts: a threshold of its own, and mutes (e.g. no alerts
    for a supplier's routine 10-Qs).

Inputs: reason (required), thesis_id (required), status, horizon, +9 more. Returns: id, title, claims, stance, +15 more

upsert_entityB

Create an entity (or merge into the one with the same canonical_key).

Inputs: name (required), kind, aliases, tickers, +1 more. Returns: id, kind, name, attrs, +4 more

watchA

Watch a company: its new SEC filings become events (on the next torus watch run). Subjects of open theses are watched automatically.

Inputs: entity (required), note. Returns: feeds, entities

what_changedB
Read-only

Everything recorded or revised across the graph since a point in time.

Inputs: since (required), until. Returns: since, until, changes, entity_id

whatifA
Read-only

What if this happened? Which theses would it reach, through which links, and would it raise alerts. Records nothing.

Inputs: entities (required), description (required), materiality, occurred_at. Returns: hits, threshold, description, materiality, +1 more

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    B3.4/5.0

    Scored across 45 tools

    Disambiguation4/5

    Most tools target a clearly distinct resource+action (record_claim vs supersede_claim vs retract_claim, watch/unwatch/list_watches, next/complete pairs for jobs), and descriptions explicitly disambiguate near-neighbours like timeline vs what_changed vs recent_records. A few pairs still blur: whatif vs impact are both dry-run reaches, and brief vs recall vs digest all surface prior context, though the descriptions do differentiate them on close reading.

    Naming Consistency3/5

    There is a solid verb_noun family (record_claim, record_thesis, update_thesis, merge_entities, resolve_alert, complete_mapping) and consistent next_/complete_ job pairs, but it sits alongside many bare single-word tools (brief, recall, search, neighbors, timeline, impact, audit, digest) and noun-phrase tools (alert_stats, thesis_weak_points, filing_diff). The mixed style is readable and roughly maps verbs to mutations and nouns to read-only views, but it is not a single predictable convention.

    Tool Count2/5

    45 tools is far above the ergonomic range and puts heavy pressure on tool selection even with distinct descriptions. The domain is broad (graph research, alerting, job leasing, filings, memos, scorecard), so each tool is plausibly motivated, but the surface would benefit from consolidation or grouping.

    Completeness4/5

    Coverage is unusually thorough: full entity/claim/thesis/relation/evidence lifecycle, corrections with history, event-driven alerts, watchlist management, job leasing for distillation and mapping, memos, explorer export, scorecard and audit. Minor gaps exist — there is no direct get_thesis or list_theses retrieval tool, with thesis inspection routed through brief, recall, thesis_memo and update_thesis.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues

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