Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add oaustegard/claude-skills/plugin install media-processingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/oaustegard/claude-skills/reading-business-cards)<a href="https://agentmods.dev/skills/oaustegard/claude-skills/reading-business-cards"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/reading-business-cards/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/oaustegard/claude-skills/reading-business-cards"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/reading-business-cards.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00148 | $0.02534 |
| Opus 5 | $0.00074 | $0.01267 |
| Sonnet 5 | $0.00030 | $0.00507 |
| Haiku 4.5 | $0.00015 | $0.00253 |
Grade A, and why
reading-business-cards scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reading Business Cards
Turn photos or scans that pack many business cards into one image into a clean contact list. The job is two stages, in order: preprocess with the script, then read the tiles it produces. Read the tiles, not the original sheet — the original is too low-resolution per card once the model downscales it.
Why preprocess first
The model downscales any input image to ~1568px on the long edge before it sees
it. A phone photo of 50-60 cards is often 4000-6000px; downscaled to one image,
each card lands ~150px wide — unreadable, which forces you onto a more expensive
model. The script cuts the sheet into overlapping tiles, each near the
downscale cap (~1300px), so every card in a tile keeps 500px+ of real
resolution. That resolution recovery is what lets a cheaper model (Sonnet) read
cards that only the expensive one (Opus) could read before — and it lets Opus
read cards from far fewer tiles. The grid is sized to the reader model (see
Stage 1): pass --model and the script tiles aggressively for Haiku, moderately
for Sonnet, and least for Opus, because a stronger reader has a lower resolution
floor. The floor is set by the pixels, not the model's intelligence: at
~220px/card (a whole dense sheet) even Opus reads only company and some names,
not phone/email — so even Opus needs a few tiles for fine print on dense sheets.
De-glaring (illumination flattening + local contrast) is applied to each tile. It corrects uneven lighting and the haze off glossy cards and plastic binder sleeves. It cannot recover text where glare has clipped pixels to pure white — that data is gone (see Limits).
Stage 1 — Tile the sheets
The person only provides the images and the goal ("read these cards"). Derive every parameter yourself; do not ask them to choose grid sizes or flags.
Real sheets are messy: cards scattered at angles, packed in binder sleeves, overlapping, piled. Detecting individual card boundaries fails on all of these. Tiling ignores card boundaries — it slices the sheet into a grid of overlapping rectangles. Each tile holds a few cards at high resolution; the overlap means a card split by one tile's edge is whole in its neighbour.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago Changed 84966d46fd7d
- 9d ago First seen · 186 lines · 148 tokens per session scan A 82305162667e
reading-business-cards is a skill published in the GitHub repository oaustegard/claude-skills (148 stars, last pushed yesterday), licensed MIT. It adds 148 tokens to every session and 2,534 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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