agentsclimarketplace

Plan antislop

Skill kensaurus/cursor-kenji/skills/plan-antislop

πŸ¦–Curated Cursor AI agent skills, slash commands, MCP configs, subagents & rules for full-stack dev β€” React 19, Next.js 15, Supabase, Tailwind v4, TypeScript

Install
npx -y skills add kensaurus/cursor-kenji --skill plan-antislop

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 6 stars6 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Audit a codebase, UI, or copy for machine-generated tells across prose, visual/UI, code, and structure/IA, then produce a phased de-slop burndown. Use when the user says "feels AI-generated", "looks like AI slop", "reads like ChatGPT", "feels generic/soulless", or wants an authenticity/voice pass before launch. Plan only β€” nothing rewritten until each phase is approved. Pairs with enhance-web-ux, enhance-web-landing, design-frontend. Do NOT use for functional bugs (debug-*), security (plan-security-audit), or net-new design.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

11.4 KB, ~2.8k tokens by cl100k_base, as published. Nobody here has run it

Anti-Slop Audit + Authenticity Burndown Plan

Role: Senior editor + product designer + staff engineer (authenticity lens).

Task: Inventory machine-generated tells across prose, visual/UI, code, and structure/IA. Score each finding by recognizability Γ— effort, cluster into phased burndowns, emit plan-antislop.md. Audit & plan only β€” no rewrites until each phase is approved.

Find the AI tells. Plan their removal. Change nothing until approved.

"Slop" is content that is recognizably machine-generated: technically fine, semantically empty, and uniform in a way no human hand would produce. This skill is the audit-and-plan half of de-slopping. It inventories slop across four surfaces, ranks each finding by recognizability Γ— effort, and emits a phased burndown the user approves before any rewrite happens.

This skill never rewrites. It produces plan-antislop.md. Execution is handed to enhance-web-ux, enhance-web-ui, enhance-web-landing, design-frontend, audit-i18n, or docs-writer after approval β€” same contract as every plan-* skill in this repo.


When this fires

Trigger phrases: "this feels AI-generated", "de-slop this", "reads like ChatGPT", "make it sound human", "every page looks identical", "it's generic/templated/soulless", "strip the AI smell before launch", "voice and authenticity pass".

Do not fire for: functional bugs (debug-*), security/RLS (plan-security-audit), missing tests (plan-test-coverage), or designing a new surface from scratch (design-frontend). Slop is about recognizability, not correctness β€” code can be 100% working and still be 100% slop.


The four slop surfaces

Audit each surface the codebase actually has. Skip surfaces that don't apply (a backend-only repo has no visual surface).

1 Β· Prose & copy slop

The most detectable surface. Scan all user-facing strings, marketing copy, READMEs, microcopy, error messages, and comments for:

  • Cadence tells β€” "It's not just X, it's Y." / "In today's fast-paced world…" / "Let's dive in." / "The result? …" / "But here's the thing:" / rhetorical question β†’ one-line answer.
  • Filler vocabulary β€” delve, tapestry, realm, landscape, leverage, seamless, robust, elevate, unlock, empower, navigate, foster, testament, bustling, vibrant, game-changer, at the end of the day.
  • Hedge-and-pad β€” "it's important to note that", "it's worth mentioning", "in conclusion", triple-adjective stacks, sentences that restate the heading.
  • Punctuation tics β€” em-dash overuse, "β€”and that's the point.", emoji as bullet points, Title Case Everywhere, bolded every other phrase.
  • Empty symmetry β€” three benefits that are the same benefit, "Fast. Simple. Powerful." triads, conclusions that summarize a 2-paragraph page.

Output for each: file/line, the tell, why a human wouldn't write it, and a direction for the fix (not the fix itself).

2 Β· Visual & UI slop

The "I've seen this exact app 400 times" surface:

  • Default-palette tell β€” untouched shadcn violet/zinc, the default Tailwind blue-600 CTA, no brand color anywhere.
  • Card-grid monotony β€” every section is a 3-up grid of identical rounded cards with an icon, a bold title, and two lines of gray text.
  • Centered-everything β€” every section center-aligned, max-w-2xl, same vertical rhythm, no asymmetry, no intentional focal point.
  • Iconography slop β€” a lucide icon on every feature whether it means anything or not; emoji in headings.
  • No hierarchy β€” all sections weighted equally; nothing is the hero, nothing recedes; uniform spacing top to bottom.
  • Generic motion β€” fade-in-on-scroll on everything, or no motion at all.

Cross-check against the project's design tokens if audit-uiux-design-system data or a tokens file exists β€” slop is often divergence from the design system plus convergence toward the framework default.

3 Β· Code slop

Working code that no engineer would have left as-is:

  • Placeholder residue β€” // TODO: implement, // your logic here, foo/bar/data/handleClick naming, lorem ipsum, commented-out scaffolding, console.log('here').
  • Comment slop β€” comments restating the code (// increment i by 1), docstrings that paraphrase the function name, banner comments around trivial blocks.
  • Over-abstraction β€” a factory + interface + strategy for one concrete case; utils/helpers/index.ts dumping grounds; premature generics.
  • Copy-paste uniformity β€” five near-identical components that should be one parameterized component; the same try/catch boilerplate everywhere.
  • Defensive theater β€” if (!data) return null guards that can't trigger; empty catch blocks; types widened to any to silence the compiler.

This overlaps audit-code-quality β€” here the lens is specifically "looks auto-generated", not general correctness. Flag, don't fix.

4 Β· Structure & IA slop

The shape of the thing:

  • Listicle-brain β€” everything is a bulleted list because the model defaults to lists; no prose, no flow, no argument.
  • Symmetrical IA β€” every page has identical Hero β†’ Features β†’ Testimonials β†’ CTA scaffolding regardless of purpose.
  • README slop β€” emoji-headers, a feature table no one asked for, "## Getting Started" boilerplate, badges that don't link anywhere, a "Contributing" section on a solo throwaway.
  • Empty completeness β€” sections that exist because the template had them (FAQ with invented questions, "Roadmap" with placeholder quarters).

Procedure

  1. Scope. Identify which of the four surfaces exist. State assumptions. If the user pointed at a specific route/file, scope to it; otherwise sweep the user-facing surface area.
  2. Inventory. Walk each in-scope surface. Collect concrete findings with path:line (or route + screenshot region for visual). Quote the minimum needed to identify the tell β€” never paste whole files.
  3. Score. Rate each finding Recognizability (how loudly it screams "AI wrote this": High / Med / Low) Γ— Effort (S / M / L). High-recognizability + Small-effort items are the top of the burndown β€” biggest authenticity gain per minute.
  4. Cluster into phases. Group findings so each phase is independently shippable and maps to one execution skill. Suggested default ordering:
    • Phase 1 β€” Copy pass (docs-writer / audit-i18n): kill cadence tells & filler vocab. Highest signal, lowest risk, no visual regression.
    • Phase 2 β€” Visual identity (enhance-web-ui / design-frontend): break the default palette, introduce hierarchy and one intentional focal point per view, de-monotonize the card grids.
    • Phase 3 β€” UX & flow (enhance-web-ux / enhance-web-landing): fix IA, replace symmetrical scaffolding with purpose-driven structure.
    • Phase 4 β€” Code cleanup (audit-code-quality / workflow-refactor): placeholder residue, comment slop, over-abstraction.
  5. Emit the report. Write plan-antislop.md (template below). End the turn. Do not start Phase 1. Wait for explicit approval per phase β€” the composer-2.5-execution.mdc handoff contract applies.

Guardrails

  • Plan only. No rewrites, no edits, no "while I'm here" fixes. The deliverable is the report.
  • Slop β‰  broken. Don't flag working code as slop just because it's simple. Simple-and-intentional is the goal, not a defect. The test is "would a human engineer/writer have left this exact thing?" β€” not "could this be fancier?"
  • Voice is the user's, not yours. Recommend directions ("warm up the CTA copy to match the conversational tone of the docs"), never ghost-write the replacement in the plan. The whole point is to remove generic voice, so don't inject a different generic voice.
  • Don't over-correct into anti-slop slop. Forced quirkiness, ironic lowercase, gratuitous em-dashes-the-other-way, and "edgy" copy are also slop. Flag the tendency; aim for intentional, not performative.
  • Cite the design system. When flagging visual slop, reference the project's actual tokens/brand if they exist. "Diverges from your defined --brand-500" is actionable; "use nicer colors" is not.
  • Minimal quoting. Identify tells by location and short excerpt; never reproduce large blocks of the source.

Report template β€” plan-antislop.md

# Anti-Slop Burndown β€” <repo/route>

_Audit-only. Nothing changes until each phase is approved._

## Scope
- Surfaces audited: [ ] Prose  [ ] Visual  [ ] Code  [ ] Structure
- Out of scope / assumptions: …

## Slop score (at a glance)
| Surface    | Findings | High-recognizability | Top quick win |
|------------|----------|----------------------|---------------|
| Prose      | n        | n                    | …             |
| Visual     | n        | n                    | …             |
| Code       | n        | n                    | …             |
| Structure  | n        | n                    | …             |

## Findings
### Prose & copy
| # | Location | Tell | Why it reads as AI | Recog | Effort | Direction |
|---|----------|------|--------------------|-------|--------|-----------|
| P1 | hero/page.tsx:24 | "It's not just a tracker, it's a companion" | dual-clause hype cadence | High | S | state the concrete benefit plainly |

### Visual & UI
| # | Route/region | Tell | Recog | Effort | Direction |
|---|--------------|------|-------|--------|-----------|

### Code
| # | path:line | Tell | Recog | Effort | Direction |
|---|-----------|------|-------|--------|-----------|

### Structure & IA
| # | Location | Tell | Recog | Effort | Direction |
|---|----------|------|-------|--------|-----------|

## Phased burndown
- **Phase 1 β€” Copy pass** β†’ `docs-writer` / `audit-i18n` β€” items P1, P3, P7…
- **Phase 2 β€” Visual identity** β†’ `enhance-web-ui` / `design-frontend` β€” V1, V2…
- **Phase 3 β€” UX & flow** β†’ `enhance-web-ux` / `enhance-web-landing` β€” S1, S4…
- **Phase 4 β€” Code cleanup** β†’ `audit-code-quality` / `workflow-refactor` β€” C2…

## Execution handoff
Approve a phase to run it. Suggested order maximizes authenticity-per-effort.
Re-run `plan-antislop` after execution to confirm the burndown closed.

Chains with

  • Six-skill plan loop β€” slots beside plan-uiux-unification; run after it so visual-slop findings inherit the design-system burndown.
  • Execution: enhance-web-ux, enhance-web-ui, enhance-web-landing, design-frontend, audit-i18n, docs-writer, workflow-refactor.
  • Verify: after execution, test-playwright (does it still work?) and a second plan-antislop pass (did the slop actually drop?).

Plan with a strong reasoning model; execute with composer-2.5-execution.mdc riding along. The plan says which slop to remove; the rule constrains how.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 326,970. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.