Render a finished BS report as a self-contained HTML page — score hero, filterable claims, readable on a phone, prints to a clean PDF. Use when the user wants to open, share, print, or show a report to someone who is not going to read a markdown table, or asks for "the HTML version", "something I can send", "a shareable page", or "make this readable".
npx skills add https://github.com/SerhiiKorniienko/bullshit-detector --skill report-card
Turn bs-report-<slug>-<date>.md into one HTML file anybody can open.
The markdown is the artifact and stays the artifact — it is what tally.py checks, what gets
diffed against a later run, and what gets committed. This skill adds a reader-facing view of
that same file. It renders; it never edits, recounts, or adds. Every number on the page is copied
from the markdown verbatim.
A BS report is a five-column claims table. On a laptop that is fine. On a phone — which is where a
shared link is actually opened — the Evidence column is unreadable, and the reader's first
question ("what's wrong with it?") means scrolling twenty rows to find the two that matter.
uv run <this-skill-dir>/scripts/render_report.py ~/.bullshit-detector/reports/<YYYY>/bs-report-<slug>-<date>.md
Writes bs-report-<slug>-<date>.html beside the markdown. -o <path> puts it elsewhere. No install
step, no dependencies — the script is stdlib-only, runs under plain python3 as well as uv run,
and the page it produces makes no network requests. That combination is what lets it work in a
code-execution sandbox, where the HTML is the only thing the user can take away.
--open shows the page in the default browser. Where there is no browser — a sandbox, a headlesshost — it says so and the file is still written. It is skipped when the page already exists,
because re-rendering is normal (the run line gets finalised after a first pass) and every open
spawns another tab — three consecutive real runs left the user with two. The file updates in
place; reload the tab you have.
--reopen opens even when the page existed — for picking a report back up in a later session. Never treat that as a failure.--quiet prints only the output path, for scripting.By default the script prints the block that ends a detector run:
BS score 4/10 · Mostly fine
the macro data is real and mostly checks out; the narrative glue is crypto-Twitter.
Tally: 35 claims extracted, 34 individually source-checked — 22 confirmed, 5 plausible,
5 misleading, 2 false. 1 not checked.
run: 16m30s, searches 35, tools 65, coverage 1, per claim 29s
markdown file:///Users/…/bs-report-japans-money-is-collapsing-2026-07-31.md
page file:///Users/…/bs-report-japans-money-is-collapsing-2026-07-31.html
opened in your browser
Paste it; don't rebuild it. Every figure came out of the report that tally.py had just
recounted. A summary retyped from memory of what you wrote is wrong in the direction that flatters
the run — the same failure mode as the tally and the search count, one level up.
The paths are file:// URLs on purpose: terminals linkify a bare URL, so both files are one
cmd-click from opening. Don't shorten them to ~/… or hide them behind link text.
Before rendering, the script runs the report through the detector's tally.py and **refuses to
render a report that fails it**:
REFUSED: bs-report-our-solar-system-2026-07-31.md does not pass tally.py.
✗ run line: 25 claims individually source-checked from 21 searches — every claim
carrying a verdict needs its own search, so this reports more verification than
was performed
Exit 3. This is the point of the gate: a page this presentable, built from a report that fails its
own arithmetic, launders a broken report into something that looks authoritative. Fix what the gate
names and re-run.
--force renders anyway and prints the failures as warnings.--no-check skips the gate — for markdown that isn't a BS report.--tally <path> or $BULLSHIT_DETECTOR_TALLY if it can't be found automatically.If tally.py isn't installed at all — this skill can be installed without the detector — the
script warns and renders. A missing validator is a reason to warn, not a reason to stop someone
viewing a report they already have.
--og-image <absolute-url> adds a link-preview image. Only useful once the page is hosted
somewhere; skip it for local files.
Then tell the user the path and that it opens in any browser. On macOS open <path> does it.
Mostly fine / Hype-heavy / Mostly bullshit / Fabricated), with the one-line verdict beside it.
Problems shows only ❌ and 🟠. Load-bearing only hides theincidental table. This is the whole reason a non-technical reader gets through the report.
Filters are deliberately ignored when printing: a filtered PDF is a report that quietly dropped
rows, which is the one artifact this tool must never produce.
<title> — N/10 and the verdict line instead of abare URL.
re-render. Never correct it in the HTML.
view, and only the markdown is what tally.py validated.
--force to make a refusal go away. The gate is naming a real defect in thereport. Rendering past it produces a page that looks more trustworthy than the thing behind it,
which is the failure this whole tool exists to catch.
internal docs and things they were sent in confidence. Writing a local file is not publishing;
putting it on the internet is a separate decision that belongs to the user, per report.
with a note on the page saying which fields were missing. That is a viewer's job. tally.py is
the strict one, and the two must not swap roles.
| # | Claim | Type | Verdict | Evidence | shape — the # columnis how the renderer tells a claims table from any other table, and the verdict glyph is read from
its own cell, never from anywhere else in the row.
share.
Phylogenetic tree toolkit (ETE). Tree manipulation (Newick/NHX), evolutionary event detection, orthology/paralogy, NCBI taxonomy, visualization (PDF/SVG), for phylogenomics.
Foundational plotting library. Create line plots, scatter, bar, histograms, heatmaps, 3D, subplots, export PNG/PDF/SVG, for scientific visualization and publication figures.
Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.
Phylogenetic tree toolkit (ETE). Tree manipulation (Newick/NHX), evolutionary event detection, orthology/paralogy, NCBI taxonomy, visualization (PDF/SVG), for phylogenomics.
Create institutional-quality equity research initiation reports through a 5-task workflow. Tasks must be executed individually with verified prerequisites - (1) company research, (2) financial modeling, (3) valuation analysis, (4) chart generation, (5) final report assembly. Each task produces specific deliverables (markdown docs, Excel models, charts, or DOCX reports). Tasks 3-5 have dependencies on earlier tasks.
Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.
Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.
Delegate complex, long-running tasks to Manus AI agent for autonomous execution. Use when user says 'use manus', 'delegate to manus', 'send to manus', 'have manus do', 'ask manus', 'check manus sessions', or when tasks require deep web research, market analysis, product comparisons, stock analysis, competitive research, document generation, data analysis, or multi-step workflows that benefit from autonomous agent execution with parallel processing.
Take serhiikorniienko/report-card from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.