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Automated structural risk reports for CDP stablecoins: analyst rulings made once, enforced by code on every run
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FinancePython · HTMLGitHub @amohazabOnlineOwner unconfirmed
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The maker's introduction consists of the line above. Read the repository README for more details. Repository README ↗
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Read the full README ↗An automated factory for structural risk reports on stablecoins: it reads each token's backing on-chain at one pinned block, scores how far that backing can be verified, and stress-tests it with a model of the token's own liquidation mechanism. The thesis is that judgment belongs at design time: an analyst rules once per archetype and once per token, and code enforces those rulings on every run. Numbers never originate from a model: every figure comes from the data table, through one formatter. The rulings, the gates and the record of decisions are the artifact; the reports are samples of what it produces.
Site: https://amohazab.github.io/stablecoin_dashboard/
| token | last published block | prose written by | open notices on the page |
|---|---|---|---|
| LUSD | 26060799 | the local model, under the figure guard | none |
| crvUSD | 25974925 | API models, September evaluation runs | 3 kinds: gate failure, harness error, judge instability |
| GHO | 25974932 | API models, September evaluation runs | 4 kinds: freeze coverage below target, off-venue share 92.4%, gate failure, harness error |
Windows Task Scheduler on the author's laptop runs everything unattended. Weekly, it
refreshes the behavioral tier (peg, liquidity and holder data fetched from Webacy) and
rebuilds the site. Monthly, it runs the full chain for one token per night: on-chain reads,
the verifiability tree, the stress model, the report. Each run commits its record and pushes,
and a push that changes the site deploys it to GitHub Pages. A run that fails still commits
its evidence. The click-through is in docs/scheduler.md.
96 registered rubric checks run in four stages: S0 config integrity (3), S1 adapter output before analysis (23), S2 verifiability and stress output (41), and S3 the rendered report (29). Every trigger declares a severity:
Every firing goes into a public log. Some things the checks and the loop actually caught:
Python 3.12 with uv. Keys come from the environment or from .env at the repo root, by name:
ETH_RPC_URL (an archive node), ETHERSCAN_API_KEY, and WEBACY_API_KEY (behavioral tier).
uv run python -m factory.run <TOKEN> # pinned reads, S0/S1 gates, the bundle
uv run python -m factory.tree <TOKEN> # the verifiability tree (no RPC)
uv run python -m factory.stress <TOKEN> # the stress cells (reads at the bundle's block)
uv run python -m factory.report <TOKEN> # table, pages, report-stage gates
uv run python -m factory.site # the selector and methodology pages
<TOKEN> is crvUSD, GHO or LUSD. factory.report <TOKEN> --llm writes the prose with a
local Ollama server running qwen3.5:9b. Without --llm the run is a
rehearsal, and its pages stay in out/rehearsal/. Tests: uv run python -m pytest; lint:
ruff check src tests.
docs/context/: the design record, read in order. The brief sets the project; the CDP
archetype memo makes the class-level rulings; the intake sheets instantiate them per token;
the evaluator rubric (rubic_v1.md, filename as-is) owns every check and trigger.PROGRESS.md: one entry per confirmed decision, in order. Start at the Step 7 and Step 8
status lines near the top. The AS-COUNTED lines record errors on both sides, the builder's
and the design layer's.USDe, as the second archetype (a synthetic, delta-hedged dollar), with its report reconciled against a manual benchmark. Then more tokens, chosen by archetype coverage.
MIT; see LICENSE.