The foundational reference for attention-based multiple-instance learning in pathology. Multiple-instance learning combines predictions from many smaller image regions to make a slide-level prediction, while attention helps weight the more relevant regions.

Use it when discussing or citing attention-based MIL, including comparisons with later methods such as CLAM, TransMIL, DSMIL, and DTFD-MIL.

It provides the original source when a pathology model uses attention to aggregate region-level information.

abmil-2018 — Skill for Claude Code and Codex by Bokai-Zhao

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add Bokai-Zhao/Pathology-Wiki --skill abmil-2018

Clone the repo

git clone --depth 1 https://github.com/Bokai-Zhao/Pathology-Wiki

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/bokai-zhao/pathology-wiki/abmil-2018/github.svg)](https://agentmods.dev/skills/bokai-zhao/pathology-wiki/abmil-2018)

Your own site

<a href="https://agentmods.dev/skills/bokai-zhao/pathology-wiki/abmil-2018"><img src="https://agentmods.dev/badge/skills/bokai-zhao/pathology-wiki/abmil-2018/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/bokai-zhao/pathology-wiki/abmil-2018"><img src="https://agentmods.dev/badge/skills/bokai-zhao/pathology-wiki/abmil-2018.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 363 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin unknown No closer match found in the catalogue.

Token cost

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	$0.00000	$0.00363
Opus 5.5	$0.00000	$0.00145
Sonnet 5.5	$0.00000	$0.00073
Haiku 4.5	$0.00000	$0.00036

Measured 2mo ago against content hash cd48c6cc273b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

abmil-2018 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 2mo 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.

skills/articles/abmil-2018/SKILL.md · 38 lines

The source is not reproduced here

No licence file

Read it on GitHub

Changes

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.

2mo ago First seen · 38 lines · 0 tokens per session scan A cd48c6cc273b

Subscribe to this mod's changes

abmil-2018 is a skill published in the GitHub repository Bokai-Zhao/Pathology-Wiki (4 stars, last pushed 5mo ago), with no licence file. It costs nothing until one of its globs matches a file; then it loads 363 tokens. 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 2026-08-31.

Scientific

abmil-2018 next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
abmil-2018Bokai-Zhao/Pathology-Wiki	Skill	4	5mo ago	none	A	0	Claude Code, Codex
instrument-data-to-allotropeanthropics/knowledge-work-plugins	Skill	35k	3d ago	Apache-2.0	A	123	Claude Code
exploratory-data-analysisK-Dense-AI/scientific-agent-skills	Skill	56k	4d ago	MIT	A	83	Claude Code
matlabK-Dense-AI/scientific-agent-skills	Skill	56k	4d ago	MIT	A	44	Claude Code
phylogeneticsK-Dense-AI/scientific-agent-skills	Skill	56k	4d ago	MIT	A	71	Claude Code, Codex
research-engineerdavila7/claude-code-templates	Skill	33k	yesterday	MIT	A	43	Claude Code, Codex
mapping-to-snomedmaziyarpanahi/openmed	Skill	5.8k	yesterday	Apache-2.0	A	205	Claude Code