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.
git clone --depth 1 https://github.com/XRenSiu/claude-code-forgeWrote 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/plugins/xrensiu/claude-code-forge/humanize)<a href="https://agentmods.dev/plugins/xrensiu/claude-code-forge/humanize"><img src="https://agentmods.dev/badge/plugins/xrensiu/claude-code-forge/humanize/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/plugins/xrensiu/claude-code-forge/humanize"><img src="https://agentmods.dev/badge/plugins/xrensiu/claude-code-forge/humanize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
humanize 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 1mo 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 — 36 lines — stays where its author put it; the contents beside it link to each section on GitHub.
{
"name": "humanize",
"description": "Humanize — make AI-written technical prose read like a competent human professional wrote it, at the level where readers actually get lost: discourse, not vocabulary. Three skills. `/humanize` rewrites a draft (zh/en) without changing a single fact: it targets the mechanisms behind 'every word is clear but I can't follow' — given-new inversion, broken topic strings, stress-position leakage (participle / 以实现… tails), lists replacing argument, cross-section restatement, stance flattening, generic openings, summary closers — plus the solved lexical/syntax/format layer (Wikipedia 'Signs of AI writing' + 2026 density-era tics: mannered prose, invented jargon, 'not X, it's Y') and Chinese translationese (yage.ai four classes + 余光中 欧化 catalog, CCL-2023 corpus-backed). Three non-skippable gates: humanlint.py (23 surface metrics, zh/en, 0-100 AI-flavor index, calibrated on four fixtures: AI 60/63 vs human 2/0), factdiff.py (numbers / dates / identifiers / URLs / paths zero add-or-drop, plus certainty-drift warning per Belem 2026), and a context-isolated cold-reader agent that records per paragraph where a reader who never saw the brief loses the thread (expected / got / lost_at / told_not_shown) — never self-graded in the drafting context (self-refine amplifies self-bias); verify_coldread.py recomputes the reader's verdict from its five declared rules and enforces the 2-round cap mechanically (v0.2.0). Max 2 revision rounds, then deliver with the residual named. Genre decides whether structure may move (v0.3.0): proposal / design / adr / memo may be reorganised; report / readme / reference run with --keep-structure, where structdiff.py rejects any change to the heading-level sequence, list blocks and item counts, table shapes or code blocks — only the sentences inside prose paragraphs change; humanlint gained a matching `report` threshold tier. `/techdoc` writes a proposal / design doc / ADR / postmortem / memo from a brief in the shWhat it installs
The manifest is a name and a version. 3 skills, 1 agent travel with it, and installing the plugin installs all of them — 635 tokens a session between them. Each is measured on its own page, and each can be installed alone.
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.
- 1mo ago Changed 710c86f0bf7e
- 1mo ago Changed b7272a6ce37a
- 1mo ago First seen · 36 lines scan A f2c071fba8ca
humanize is a plugin published in the GitHub repository XRenSiu/claude-code-forge (2 stars, last pushed 29d ago), licensed MIT. Its token cost is not measured: this kind of file is read by the harness, not the model. 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 2026-09-05.
Other plugins, from other repositories
han-communication
Foundational communication plugin for the Han suite. Owns the canonical readability standard, the writing-voice profile, and the explanation standard for talking to a reader who will not implement the work, plus the readability-guidance skill that surfaces the first two into a calling skill's own context for in-voice…
pedantic-coder
Zero-tolerance code pedantry — naming precision, casing law, structural symmetry, import discipline, and the obsessive details that separate clean code from correct code.
ai-infra-auto-driven-skills
Agent-ready playbooks for LLM serving benchmarks, SGLang model Day-0 support, capacity planning, profiling, code review, incidents, PR-history dossiers, and SGLang PR/article explainer videos.
git-pr
Committing, PR creation and review triage, and dependency upgrades.
code-quality
OxLint, Biome, and Prettier configuration, linting skills, and pre-commit hooks for consistent code quality.
coderabbit
CodeRabbit integration for Claude Code - local code review and PR comment management.