Repo-wide sweep of every user-facing string: frontend components, routes,
config and stores; API details and route docs; shared definitions and
models; stage config help; report prose; MCP, toolbox, interest and
connector text; notification and worker messages.
Descriptions that explained, reassured, justified or restated their title
are deleted. Confirm dialogs name what is removed and stop. Failed actions
read "<Noun> not <verbed>", successes "<Noun> <verbed>". No reader address,
no product-as-subject, no em-dashes or parentheticals in prose.
Mirrors updated on both sides: EPSS band help, compare refusal reasons,
interest labels. Four tests asserting on old wording follow the new text.
The rules are condensed into CLAUDE.md under Writing.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01SK5o8xR96cbSnAfjYSTPSe
The first cut was rejected outright, and fairly. Four things were wrong.
The running head and foot sat 1.4mm from the physical sheet: vertical-align:top
on the @top-* margin boxes pins text to the paper, not to the text block. They
now hang off the block with RUNNING_CLEAR of air on the inside edge.
Severity was five saturated hues, restated by every theme and slightly
different in each. It is now one reserved ramp defined once, light rather than
heavy, with lightness carrying the rank so it survives deuteranopia; it clears
the CVD and normal-vision floors all-pairs on white paper. A dark page picks
up the dark restep automatically, so a dark theme carries no severity block at
all. shared/utils/color.py converts through OKLCH, so a theme names one colour
and the document derives the wash a badge sits on and the ink that sits on the
wash — every badge clears 7:1, including one from a theme a user uploads.
Badges are pills, never saturated slabs, and never inline-flex, which
WeasyPrint lays out as a block so the badge stretched its whole column.
Mono is for machine values now — hostnames, evidence, hashes. Labels, table
headers and the running head are the body face, and uppercase_labels finally
does something: the CSS had hard-coded uppercase and ignored the token.
Prose fills the text column, justified and hyphenated, instead of sitting in a
narrow measure with dead space beside it. Chapters still start a new page, but
a document may now ask them to run on, and the page estimate knows the
difference: 52 pages against 52, and 48 against 48.
Two defects the redesign surfaced: the risk summary never passed the variables
its own template reads, so that severity table had always printed empty; and
the standalone HTML export had no margins at all, because @page geometry does
not apply on screen.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01AW5pitnosX8LEFEYxH8gFS
reNgine 2 could produce a PDF. This produces a deliverable, and it is built
the way scan engines are built: sections are plug-and-play directories under
reports/, each with a pydantic config model that IS the source of truth. That
model feeds GET /reports/catalog, the builder renders its own form from it, and
the API validates against it. Adding a section is a directory. Scan Engine is to
stages what Report Template is to sections.
WeasyPrint 69 renders it, chosen over Chromium and Typst after measuring what
each can actually do. Only real CSS Paged Media gives a table of contents with
true page numbers, running headers, a PDF outline and footnotes; SysReptor
reaches the same verdict and pipes Chromium's HTML into WeasyPrint for exactly
that reason. reNgine drops the Chromium hop because it templates in Jinja and
draws its charts as SVG in Python, so a browser buys nothing and costs 400 MB
per report. Typst was rejected because a user-uploadable theme would then have
to be Typst code rather than CSS.
A theme is data. shared/definitions/report_theme.py is the schema, six themes
ship as YAML, and a user uploads their own; there is no markup in a theme, so
there is no injection surface. Fonts are vendored so an offline instance still
renders in Latin, Greek and Cyrillic.
Everything the document claims is computed once, in reports/analysis/engine.py:
a posture score whose every deduction is named, weaknesses ranked by the signals
behind the rank rather than severity alone, attack paths that chain observations
into a route, a remediation plan ordered by risk removed, per-dimension change
against the previous run, and caveats that state what was never assessed. Two
narrators read that one brief. Without AI the report still argues its case; with
AI the prose is better and the model never sees a row, only the brief, capped and
cached per check. An AI failure falls back and the report still completes.
Generation is a job. POST /reports queues, the worker walks progress over SSE,
and four formats come out of one render: PDF, self-contained HTML, Markdown and
JSON. The estimate reads each section's own limits, so the page count it promises
is close to the one it delivers.
AI moves out of Settings into its own top-level page: connection, a model per
tier, what it may be used for, what it has cost, and the narrative cache.
Verified on a 1,379-host gov.cy scan: 124 pages in 19.5s across 19 sections,
all six themes, and a broken key still producing a complete report.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_017f2Mf2HGwFaTRnui4UxpRd
