Read, reproduce and change the candidate
The portable starting directory contains README.md,
run_checks.py, models/,
toy_agents/ and domains/. In the working
repository that directory is papers/07-release-packet. In
the download it is mcrp-prototype.
Read without installing anything
Open index.html from the extracted download in a
browser. All reading pages, figures, styles, controls and saved traces
are local; there are no analytics, remote fonts or network calls.
Interactive controls evaluate the three stated formulas. They do not
execute the Python simulation. Saved results are also provided as JSON
and CSV beside their source code.
The download includes research fixtures with deliberately vulnerable
baseline code, clearly labeled in reviews/red-runtime. They
reconstruct the original packaging counterexamples using public sentinel
strings. Use surfaces/build.py and
surfaces/verify_export.py for the repaired packaging
tools.
Reproduce the experiments
Use Python 3.9 or later. From the portable starting directory:
python3 run_checks.pyNo third-party Python package, network, credentials, model inference
or external data is needed for this command. It runs the model suites
and independent adversarial regressions, then regenerates synthetic
outputs. The terminal reports each check group and the final total.
results/validation.json records success, test counts,
Python version, source/input hashes, saved-result hashes and the full
log inventory. Inputs are captured before and after execution; a changed
source or fixture makes the run fail. These checks bind evidence to a
run, not the scientific truth of its content.
This is a research run, not a production readiness assessment. Successful negative controls mean the specified failure is exposed, not that it has been eliminated. Random-number implementation differences across Python versions may change sampled trajectories; deterministic finite arithmetic and invariant tests are separate.
Run on a working copy: regenerated timings, logs and environment records will change some files. An export’s original manifest describes the original snapshot; it is not expected to certify your modified reproduction directory afterward. Preserve the original download if you want to compare results or verify integrity.
Choose a smaller entry point
| Question | Command from the portable directory |
|---|---|
| Can an existing review record enter the toy runtime honestly? | python3 -m adapters.demo |
| How much could a tiny human-interface study establish? | python3 models/human_pilot/run_design.py |
| What happens to a scoped decision after amendment? | python3 -m toy_agents.run |
| What does publication approval bind in the separate toy cycle? | python3 models/release_cycle.py --output results/release-cycle.json |
| What are the exact panel, repair and audit bounds? | python3 models/math/run_experiments.py |
| What changes across allocation, completion and reliance? | python3 models/coupled/run_experiments.py |
| Does recognition feedback beat uniform routing? | python3 -m models.ecology.run |
| Do promised inspections actually get funded and delivered? | python3 models/funded_audits/run_experiments.py |
| Can correction credit reward manufactured work? | python3 -m models.ecology.correction_game |
| What does the biology or legal example actually calculate? | python3 domains/fixtures/domain_models.py |
| Can domain examples issue and amend real toy receipts? | python3 domains/fixtures/replay_receipts.py |
Change one parameter or one premise, preserve the old result, and explain what changed. A failed invariant is useful evidence. A new parameter result is not a new theorem. Include the full offered-work and unfinished-work denominators.
Optional figure and reading-page generation
The core tests are standard-library-only. Scientific figure regeneration additionally uses Matplotlib (the saved figure manifest records the version):
python3 surfaces/make_figures.pyWhen a different environment changes those saved result bytes, regenerate figures before building a new export so their input hashes agree. Merely reproducing the core models does not require Matplotlib.
Figures read the retained coupled/ecology results. Their manifest binds source, input tables and output bytes. The ecology whiskers are seed ranges, not confidence intervals. The selection figure shows pooled stage shares rather than independent observations from people.
Reading-page generation additionally requires Pandoc available on
PATH:
python3 surfaces/build.py ../mcrp-public-candidate
python3 surfaces/verify_export.py ../mcrp-public-candidateThe output must be outside the source packet. The builder stages a fresh candidate, rejects symlinks and unexpected pre-existing output, then replaces only a recognized unchanged prior export. It does not publish, deploy or change repository visibility. The verifier checks exact file and ZIP membership, hashes, local links/fragments, validation-evidence references and four declared disclosure patterns. It cannot establish that every private fact or rights issue has been discovered.
The file-map digest and ZIP digest identify a candidate. Neither is a signature, license, approval or statement that source claims are true. A release decision must identify the responsible maintainer, adopted rights terms and destination for those exact bytes.
The optional eight-page synthesis brief uses ReportLab, Pillow and pypdf:
python3 surfaces/build_brief.pyIt writes results/mcrp-release-brief.pdf and a manifest
binding its builder and figure input. Its PDF metadata is fixed for
reproduction; metadata dates are not release timestamps. The saved PDF
can be read without these packages.