remediate

A command that scans an existing website interface for visual signs that it was produced from generic AI design patterns. It uses browser screenshots and page facts to produce a ranked list of suggested changes, with an optional apply mode.

In plain words
What is it for?
Use it to inspect one or more website routes, review the ranked findings, and optionally apply only the listed high-confidence, low-risk fixes.
Why use it?
It helps identify repetitive or unmotivated visual choices that can make an interface look AI-generated, without relying only on a manual review.

Command

Part of the damu plugin — 1 skill, 2 commands shipped together

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.

agentmods
npx agentmods add commands/alphabravo-oss/guild/remediate
Clone the repo
git clone --depth 1 https://github.com/alphabravo-oss/guild

Or install damu, the plugin that ships this one along with the rest of its 1 skill, 2 commands.

Per session 49 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,763 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original 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.

ModelPer sessionOnce invoked
Fable 5 $0.00049 $0.03763
Opus 5 $0.00024 $0.01881
Sonnet 5 $0.00010 $0.00753
Haiku 4.5 $0.00005 $0.00376

Measured 3d ago against content hash 5b767531817b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

remediate 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 3d 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.

plugins/damu/commands/remediate.md · 224 lines

How it starts

The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.

damu — remediate (scan an existing UI for AI slop)

You are the damu orchestrator. The user wants their already-built UI scanned for the tells that make it read as AI-generated, with concrete fixes. The catalog of tells lives at ${CLAUDE_PLUGIN_ROOT}/skills/slop-catalog/SKILL.md — read it before you start; it governs everything.

Your job has four phases: capture (you drive Playwright), judge (a bundled Workflow engine does the analysis — you do NOT judge the UI yourself), render, and — only with --apply — a careful, HIGH-confidence-only fix pass. Playwright is stateful and lives in your context, so you capture the artifacts; the Workflow agents work off the saved screenshots + facts, never the live browser.

Arguments

$ARGUMENTS

Parse: a URL or comma-separated routes; --apply (run the fix pass after the report); --headed (visible browser, else headless is fine); --routes=... explicit route list.

PHASE 0 — preflight

  1. Playwright MCP present? The mcp__plugin_playwright_playwright__* tools must be available. If not, tell the user to run /e2e:init (or add the playwright server to .mcp.json) and restart Claude Code, then stop.
  2. Git repo? git rev-parse --is-inside-work-tree. Needed for --apply (atomic commits) and for anchoring findings to source files. A scan can run without git, but --apply cannot — say so.
  3. For --apply: clean tree. git status --porcelain must be empty. If dirty, refuse the apply pass (you'll still produce the report) — like tidy, every fix is one atomic commit away from a revert, which only works from a clean base.
  4. Target URL. If none in args, ask with AskUserQuestion: the dev server URL (they type it). Do not guess a port. If they give a base URL, you'll discover routes in Phase 1.

Create the run dir:

mkdir -p .damu/runs/$(date -u +%Y%m%d-%H%M%S)/shots

Use that path as RUNDIR throughout.

PHASE 1 — capture (you drive Playwright)

Read the full file on GitHub · 224 lines

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.

  1. 3d ago First seen · 224 lines · 49 tokens per session scan A 5b767531817b

Subscribe to this mod's changes

remediate is a command published in the GitHub repository alphabravo-oss/guild (2 stars, last pushed 3d ago), licensed MIT. It adds 49 tokens to every session and 3,763 once invoked, about $0.0002 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 2026-08-31.