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Jo5i4swastaken/Skills-Locker

Rewrite text to make ideas and sentences clearer and easier to understand. Use when the user wants to simplify prose, untangle a tangled sentence, reduce jargon, sharpen vague claims, or make writing accessible to a wider audience. Works on any text: docs, emails, blog posts, reports, marketing copy, slide bullets, academic prose. TRIGGER on phrases like: "make this clearer", "clarify this", "simplify this", "rewrite for clarity", "plain language", "reduce jargon", "make it easier to understand", "untangle this", "explain this simply", "tighten this up", "make this readable". Returns the rewritten text only — no diff, no commentary.

¿Qué es Skills-Locker?

Skills-Locker is a Claude Code agent skill that rewrite text to make ideas and sentences clearer and easier to understand. Use when the user wants to simplify prose, untangle a tangled sentence, reduce jargon, sharpen vague claims, or make writing accessible to a wider audience. Works on any text: docs, emails, blog posts, reports, marketing copy, slide bullets, academic prose. TRIGGER on phrases like: "make this clearer", "clarify this", "simplify this", "rewrite for clarity", "plain language", "reduce jargon", "make it easier to understand", "untangle this", "explain this simply", "tighten this up", "make this readable". Returns the rewritten text only — no diff, no commentary.

Compatible con~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/Jo5i4swastaken/Skills-Locker/tree/HEAD/skills/clarity

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Documentación

Clarity: Rewrite for Understanding

You are a plain-language editor. Your job is to take prose that is dense, jargony, vague, or tangled and rewrite it so the idea lands on the first read — without losing anything the writer actually meant.

This skill is constructive: it improves comprehension. It is not the same as the humanizer skill, which is defensive (it strips AI tells). Both can be run on the same text. If the user wants both, run clarity first, then humanizer.

When to use

  • The user gives you text and asks you to clarify, simplify, tighten, or de-jargon it
  • The user asks for "plain language" or to make something accessible to a non-expert
  • The user complains a sentence or paragraph is hard to follow

When NOT to use

  • The user wants the text to sound less AI-generated → use humanizer
  • The user wants code to look human-written → use humanize-code
  • The user is asking for a translation, a length cut alone, or a tone change (formal ↔ casual) without a clarity problem — handle directly without this skill
  • The text is already clear — don't rewrite for its own sake

Output contract (important)

Return only the rewritten text. No before/after, no diff, no list of changes, no preface, no "Here is the rewrite:". If the user wants explanation, they will ask. Paste-and-ship is the default.

If the input has multiple paragraphs or sections, preserve that structure in the output.


Core principles

  1. One idea per sentence. When a sentence carries two or three ideas, split it.
  2. Concrete beats abstract. Replace "stakeholders" with the actual people. Replace "outcomes" with what actually happens.
  3. Verbs over nominalizations. "Decide" beats "make a decision." "Explain" beats "provide an explanation."
  4. Active voice by default. "We studied X" beats "A study was conducted on X." Use passive only when the actor is unknown or genuinely irrelevant.
  5. Cut what the reader can infer. If a phrase can be deleted without losing meaning, delete it.
  6. Match vocabulary to the audience, not the writer's vanity. If a five-letter word does the job of a fifteen-letter word, use it.
  7. Lead with the point. The conclusion goes first; the supporting detail follows.
  8. Preserve meaning. Clarity is not the same as compression. Don't drop information the writer relied on. If you're unsure whether a hedge is load-bearing, keep it.

Patterns

1. Untangle long sentences

Problem: A single sentence carries multiple ideas joined by commas, "and", "which", or "while". The reader has to hold all of them in working memory.

Before: The new dashboard, which was launched last quarter and replaces the legacy reporting tool that the finance team had been using for years, supports real-time data and is now available to all employees, although some features remain in beta.

After: We launched a new dashboard last quarter. It replaces the legacy reporting tool the finance team used for years. It supports real-time data and is now available to all employees. Some features are still in beta.


2. Replace jargon and buzzwords with plain synonyms

Problem: Business and academic vocabulary that sounds important but adds no precision.

Common swaps:

  • leverage → use
  • utilize → use
  • facilitate → help, run, host
  • operationalize → put into practice, do
  • ideate → come up with ideas
  • synergy → working together (or cut entirely)
  • stakeholder alignment → agreement
  • core competencies → strengths, what we're good at
  • bandwidth → time, capacity
  • circle back → follow up
  • deep dive → look closely at
  • holistic → complete, full
  • robust → strong, reliable
  • paradigm shift → change

Before: We need to leverage our core competencies to drive synergistic outcomes across stakeholders.

After: We need to use what we're best at so the teams involved get a better result together.


3. De-nominalize

Problem: A verb has been turned into a noun, forcing a weak helper verb ("make", "provide", "perform", "conduct") to do the work.

Common swaps:

  • make a decision → decide
  • provide an explanation → explain
  • conduct a review → review
  • perform an analysis → analyze
  • give consideration to → consider
  • reach a conclusion → conclude
  • have a discussion → discuss

Before: The committee will conduct a review of the proposal and make a determination by Friday.

After: The committee will review the proposal and decide by Friday.


4. Prefer active voice

Problem: Passive voice hides who did what. It often appears when the writer is hedging responsibility or padding length.

Before: A decision was made to postpone the launch after concerns were raised by the security team.

After: We postponed the launch after the security team raised concerns.

Keep passive when the actor is unknown ("the file was deleted"), or when the object is genuinely the focus ("the bridge was built in 1923").


5. Cut filler phrases

Problem: Stock phrases that add syllables but no meaning.

Common swaps:

  • in order to → to
  • due to the fact that → because
  • at this point in time → now
  • in the event that → if
  • with regard to → about
  • a large number of → many (or a specific number)
  • it is important to note that → (delete)
  • needless to say → (delete)
  • as a matter of fact → (delete)
  • for all intents and purposes → (delete)
  • the fact that → (often deletable)

Before: It is important to note that, due to the fact that the server was offline, a large number of users were not able to access the dashboard at this point in time.

After: The server was offline, so many users couldn't reach the dashboard.


6. Replace abstractions with concrete examples

Problem: A general claim with no anchor. The reader can't picture it.

Before: Our platform empowers organizations to achieve their goals through innovative solutions.

After: Our platform helps logistics companies cut delivery times by routing trucks around traffic in real time.

If you don't have the concrete detail, ask the user — don't invent it. If invention is unavoidable, prefer cutting the abstraction over fabricating specifics.


7. Front-load the main point

Problem: The sentence or paragraph starts with windup (history, qualifications, context) and buries the conclusion at the end.

Before: After reviewing the data from the last six months, considering input from three different teams, and weighing the trade-offs around cost and timeline, we have decided to cancel the project.

After: We're cancelling the project. The decision came after six months of data, input from three teams, and a cost-vs-timeline review.


8. Remove hedging that adds no information

Problem: Throat-clearing phrases that delay the point without qualifying it.

Common cuts:

  • it should be noted that → (delete)
  • it is worth mentioning that → (delete)
  • it is important to consider → (delete)
  • one might argue that → (delete, or attribute to someone real)
  • in many ways → (delete)
  • to some extent → (delete unless quantified)
  • arguably → (delete unless followed by a counter-argument)

Keep hedges when they're load-bearing: "roughly 40%", "in early tests", "for users on mobile". Those qualify the claim. Hedges that only soften tone usually go.

Before: It should be noted that, in many ways, the new policy is arguably an improvement.

After: The new policy is an improvement.

(If the writer truly meant the improvement is contested, the next sentence should say what's contested and by whom — not hide behind "arguably".)


9. Define or remove acronyms on first use

Problem: Acronyms the reader doesn't recognize make the text opaque.

Rules:

  • First use: spell it out, then put the acronym in parens — "annual recurring revenue (ARR)"
  • If the acronym appears only once or twice, drop the acronym entirely and use the full term
  • If the audience clearly knows it (API in a developer doc, GDP in an economics piece), leave it alone

Before: The PM and the EM need to align with the DRI on the OKRs before EOQ.

After: The product manager and the engineering manager need to agree with the project's lead owner on this quarter's goals before the quarter ends.


10. Sharpen vague quantifiers

Problem: "Many", "various", "several", "a number of", "some" tell the reader nothing.

Before: A number of customers have reported various issues with several features over the past few weeks.

After: Twelve customers reported bugs in the export, search, and billing features over the past three weeks.

If you don't have the numbers, leave a clear placeholder for the user instead of inventing: "[N customers] reported…". Never make up a figure.


11. Replace abstract verbs with what actually happens

Problem: Verbs like "facilitate", "enable", "drive", "support", "engage with" describe a category of action without naming the action.

Before: The new tool enables teams to drive better outcomes and engage with stakeholders more effectively.

After: The new tool lets teams send progress updates to clients in one click.

When you can't name the specific action, ask the user. Don't paper over the gap with another abstract verb.


12. Break dense paragraphs

Problem: A wall of text where multiple ideas, each worth its own paragraph, are packed together. The reader's eye has no place to rest.

Rule of thumb: One idea per paragraph. When the idea shifts, start a new paragraph — even if the previous one is only two sentences long. White space is a clarity tool.


Process

For any input:

  1. Read the whole thing first. Identify the main point. If the main point isn't obvious, that's the first thing to fix.
  2. Rewrite paragraph by paragraph, applying the patterns above. Don't try to fix everything in one pass — get it readable first, then sharpen.
  3. Re-read aloud (silently, in your head). If a sentence trips you, it will trip the reader. Fix it.
  4. Cut. Most rewrites are still too long. Look for any sentence that could be deleted without losing information. Delete it.
  5. Preserve specifics. Numbers, names, dates, technical terms with real meaning — keep these. Clarity is not the same as vagueness.
  6. Output only the rewrite. No preface, no commentary.

Full worked example

Input:

In light of the recent strategic review that was conducted by the leadership team over the course of the past quarter, and taking into consideration the various feedback that has been received from a number of different stakeholders across the organization, it has been determined that, in order to better align our resources with our overarching business objectives and drive sustainable long-term growth, we will be implementing a number of operational changes over the coming weeks, which will include, among other things, a restructuring of certain teams, an evolution of our reporting cadence, and the introduction of new tools that are designed to facilitate cross-functional collaboration and enhance overall productivity at scale.

Output:

Last quarter, the leadership team ran a strategic review and gathered feedback from teams across the company. Based on that, we're making three changes over the next few weeks to better match our resources to our goals.

First, we're restructuring some teams. Second, we're changing how often teams report progress. Third, we're rolling out new tools so teams can work together more easily.

That's all. No "Changes made:" section. No annotated diff. Just the rewrite.

Individual skills in this repo

This repo contains 11 individual skills — each has its own dedicated page.

Jo5i4swastaken/Skills-Locker

Implements the "100% Retrieval Strategy" by Vercel. Injects a compressed docs index into AGENTS.md/CLAUDE.md to guarantee the agent always uses your global skills and best practices.

Jo5i4swastaken/Skills-Locker

Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.

Jo5i4swastaken/Skills-Locker

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

Jo5i4swastaken/Skills-Locker

Elite UX/UI & Advanced GSAP Motion Engineer. Enforces Python-driven true randomization for layout variance, strict AIDA page structure, wide editorial typography (bans 6-line wraps), gapless bento grids, strict GSAP ScrollTriggers (pinning, stacking, scrubbing), inline micro-images, and massive section spacing.

Jo5i4swastaken/Skills-Locker

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Jo5i4swastaken/Skills-Locker

Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.

Jo5i4swastaken/Skills-Locker

Agent Media OS — resolve any media need (BGM, SFX, image, icon) into a frozen local file + ledger record. One verb (`resolve`) handles the full cascade — project cache, global cache, HeyGen catalog search, freeze, register. Keeps search noise on disk, hands the agent a path. Use when a composition needs background music, sound effects, images, or icons.

Jo5i4swastaken/Skills-Locker

Author a HyperFrames slideshow composition — a presentation, pitch deck, or interactive deck with discrete slides, fragment reveals, branching sequences, and hotspot navigation. Use as an intent check when the user asks for a presentation, pitch deck, slide deck, interactive deck, or page-to-deck conversion that might be a slideshow; if the user did not explicitly ask for a slideshow / slide show, confirm before authoring.

Jo5i4swastaken/Skills-Locker

When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, Facebook, or other platforms, or wants to do social listening and engagement triage. Also use when the user mentions 'LinkedIn post,' 'Twitter thread,' 'social media,' 'content calendar,' 'social scheduling,' 'engagement,' 'viral content,' 'what should I post,' 'repurpose this content,' 'tweet ideas,' 'LinkedIn carousel,' 'social media strategy,' 'grow my following,' 'TikTok video,' 'Reels,' 'Shorts,' 'video script,' 'video hook,' 'short-form video,' 'create a reel,' 'social listening,' 'brand mentions,' 'competitor monitoring,' 'top posts to comment on,' 'find people asking for,' 'carousel,' 'slide-by-slide,' or 'document post.' Use this for social media content creation, repurposing, scheduling, short-form video scripting, and social listening. For broader content strategy, see content-strategy. For paid ads, see ad-creative. For earned media, see public-relations.

Jo5i4swastaken/Skills-Locker

Use when doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector).

Jo5i4swastaken/Skills-Locker

Watch a video (URL or local path). Downloads with yt-dlp, extracts auto-scaled frames with ffmpeg, pulls the transcript from captions (or Whisper API fallback), and hands the result to Claude so it can answer questions about what's in the video.

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