Transformers
K-Dense-AI/scientific-agent-skills
Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks.
Transform technical jargon into clear explanations using before/after comparisons, metaphors, and practical context
$ npx skills add try-works/role-model --skill eli5 -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install try-works/role-model eli5 --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/try-works/role-model.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/eli5 .claude/skills/eli5 && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "eli5" agent skill from https://github.com/try-works/role-model/tree/dev/.agents/skills/eli5 into .claude/skills/eli5/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eli5", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/try-works/role-model/tree/dev/.agents/skills/eli5Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add try-works/role-model --skill eli5 -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install try-works/role-model eli5 --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/try-works/role-model.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/eli5 .agents/skills/eli5 && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "eli5" agent skill from https://github.com/try-works/role-model/tree/dev/.agents/skills/eli5 into .agents/skills/eli5/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eli5", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add try-works/role-model --skill eli5 -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install try-works/role-model eli5 --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/try-works/role-model.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/eli5 .cursor/skills/eli5 && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "eli5" agent skill from https://github.com/try-works/role-model/tree/dev/.agents/skills/eli5 into .cursor/skills/eli5/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eli5", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/try-works/role-model.git --path .agents/skills/eli5--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add try-works/role-model --skill eli5 -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install try-works/role-model eli5 --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/try-works/role-model.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/eli5 .gemini/skills/eli5 && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "eli5" agent skill from https://github.com/try-works/role-model/tree/dev/.agents/skills/eli5 into .gemini/skills/eli5/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eli5", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install try-works/role-model eli5Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add try-works/role-model --skill eli5 -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/try-works/role-model.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/eli5 .github/skills/eli5 && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "eli5" agent skill from https://github.com/try-works/role-model/tree/dev/.agents/skills/eli5 into .github/skills/eli5/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eli5", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add try-works/role-model --skill eli5 -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install try-works/role-model eli5 --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/try-works/role-model.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/eli5 .opencode/skills/eli5 && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "eli5" agent skill from https://github.com/try-works/role-model/tree/dev/.agents/skills/eli5 into .opencode/skills/eli5/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eli5", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
eli5Transform technical jargon into clear explanations using before/after comparisons, metaphors, and practical context
Eli5 is an agent skill from try-works/role-model. Transform technical jargon into clear explanations using before/after comparisons, metaphors, and practical context
Its SKILL.md is about 7.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `README.md`, `references/EXAMPLES_REFERENCE.md` and `references/content-type-guide.md`). Compatibility notes: opencode
The repository describes itself as: role-model is a protocol for assigning the right model for the right job. Use local and cloud AI together, or route between several cloud providers. The licence is MIT.
6 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit de1c04a. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash and markdown).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
opencode
From compatibility in the SKILL.md frontmatter.
Eli5 loads about 7.1k tokens when it runs, and up to ~29k if it reads all its reference files. Until then it costs about 30 tokens; SKILL.md has 3,578 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from try-works/role-model at commit de1c04a, republished under its MIT licence (© try-works). 3,578 words, ~7,080 tokens.
.claude/skills/eli5/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.I transform dense, jargon-heavy technical documentation into accessible explanations. Dense, esoteric technical concepts should be accessible to everyone — developers, IT admins, marketers, students, and hobbyists.
Key capabilities:
Technical writing often prioritizes precision over clarity: jargon without context, missing "why", unstated assumptions, and condescending simplification ("simply," "just," "obviously"). ELI5 fixes this through:
Audience: Readers are intelligent but lack specific context. Never write for the "lowest common denominator." Assume smart people who are unfamiliar with this particular domain.
Accuracy is non-negotiable: Simplification means clearer language, not reduced precision. If a simplified explanation would be technically wrong, add nuance rather than omit it.
Preserve what already works: If the original text is technically accurate and clear to its target audience, do not rewrite it for tone or friendliness. Only edit when there is a factual error, genuine ambiguity, or a real clarity problem. Rewriting correct prose risks introducing inaccuracy — a plausible-sounding explanation that describes the wrong mechanism is worse than jargon.
Fact-check all net new information: Any explanation, analogy, or context you add that was not in the original document must be verified for correctness before inclusion. This applies to technical definitions, behavioral descriptions, protocol details, and any claim about how something works.
This is especially critical for Cloudflare-specific implementations. Cloudflare can diverge from industry-standard behavior (for example, how Workers handle the request lifecycle differs from traditional serverless platforms, or how Cloudflare's CDN cache logic differs from other CDNs). Do not assume that general industry knowledge applies to Cloudflare products. When adding commentary about Cloudflare-specific behavior:
Tone: Clear, direct, professional. Not condescending, not overly casual, not hyperbolic. Never use "simply," "just," "obviously," "clearly," "as everyone knows," or "it's easy to."
Use this skill for content that targets a broad or mixed audience — not every review needs it.
Good candidates:
Skip or deprioritize for:
Use your judgment for everything else. Ask: "Would a reasonable reader of this page already know these terms?" If yes, this skill adds little value. On the other hand, if the following are true, this skill could provide significant value.
1. Accept File Path
/eli5 path/to/documentation.mdSupported: .md, .mdx
2. Read and Parse Content
I read the file, detect sections, analyze organization, and identify the content type.
Content types: Overview, Concept, How To, Reference, Tutorial
Detection signals:
After detection, I ask you to confirm the content type. Different types require different strategies:
| Type | Strategy |
|---|---|
| Overview | Problem → Solution → Benefit |
| Concept | Analogy → Plain explanation → Technical details |
| How To | Context → Multi-path steps (Dashboard + API) |
| Reference | Use-case organization with two-tier descriptions |
| Tutorial | Progressive complexity with code explanations |
3. Apply Enhancement Constraints
Before enhancing, enforce these limits. Target 1.5-2x expansion (not 5-10x). Enhance existing content with context, not replace it.
Maximum additions per document:
Preserve: All existing content, structure, diagrams, code examples, component usage, and flow.
Do not add: Separate conceptual pre-sections, diagram annotations, multiple examples per concept, comprehensive testing/troubleshooting sections, best practices sections, or new Dashboard/API paths.
Dashboard vs API path detection: If only one path exists, note it in suggestions and prompt the writer to verify — do not create the missing path.
4. Ask Which Sections to Simplify
Present these options and wait for a response:
5. Analyze Selected Sections
For each section, I identify:
6. Extract Terminology
I compile a deduplicated list of all terms that may need glossary definitions or cross-links:
For each term I report: the term, where it appears (line number), whether it is defined in-context, and a suggested action (add glossary tooltip, add cross-link, or add inline definition).
GlossaryTooltip quality gate: Before suggesting a GlossaryTooltip for any term, read the actual glossary definition (in src/content/glossary/). Evaluate it against these criteria:
When a glossary entry fails any of these checks, report it in the Terminology Index with the action "Flag glossary entry for review — [reason]" instead of "Add glossary tooltip."
Always include the Terminology Index in the output. If no terms need action, state that explicitly.
7. Generate Comparison
I produce a comparison with:
8. Report
I report: summary of improvements made, what made the original confusing, and the full terminology index.
Then proceed immediately to Step 9 (Adversarial Review). Do not prompt the user for next steps until the review is complete.
9. Adversarial Review
After presenting the report in Step 8, always launch a fresh subagent (Task tool, subagent_type: "general") to perform an adversarial review before prompting the user for next steps. Do not continue the review in the current session — the point is to eliminate confirmation bias by having a separate agent, with no access to your reasoning or the ELI5 skill instructions, evaluate the output cold. Do not skip this step.
Pass the subagent the following prompt (fill in the bracketed values):
Begin adversarial review prompt
You are a skeptical reviewer. Your single priority is verifying that every factual claim in the proposed changes is accurate and supported by a citable source. You assume claims are unsupported until proven otherwise.
You are NOT a style checker or formatter. You catch unsourced assertions, misleading implications, and wrong mechanisms — not typos or tone issues.
Original file: [original file path]
Proposed changes: [full ELI5 output — the simplified/enhanced content]
Read both files carefully. Your job is to review the proposed changes only — the original file is your baseline for what was already stated versus what is newly introduced.
Any statement in the proposed changes that a reader could reasonably question:
Opinions, definitions created by the doc itself, and procedural steps ("Select Save") are not claims.
These are the highest-risk categories when documentation has been simplified. Prioritize them:
Simplified mechanism descriptions — Any "how it works" explanation added during simplification that was not in the original. These carry the highest risk: a plausible-sounding explanation that describes the wrong mechanism is worse than the original jargon. Verify the actual mechanism against the source docs in this repository.
Misleading nuance — Statements that are not outright wrong but flatten important nuance, creating a wrong mental model. Example: "Cloudflare generates a robots.txt file that instructs AI crawlers to stay away from your content" is misleading — robots.txt is a per-path allow/disallow mechanism, not a blanket block. The sentence omits that it specifies where crawlers may and may not go. Flag any statement where the simplification loses a meaningful distinction.
Net-new claims — Any explanation, context, or framing added during simplification that was not present in the original document. Every piece of new information requires a citation. If the original said "zones pair with resolver policies" and the simplification adds "based on source IP, user identity, or domain," verify that all three of those selectors are actually supported.
Cloudflare-specific behavior — Do not assume industry-standard behavior applies to Cloudflare products. Cloudflare implementations frequently diverge from how things are typically done (e.g., Workers request lifecycle vs. traditional serverless, Cloudflare CDN cache logic vs. other CDNs, how Cloudflare Tunnel health checks work vs. generic health check patterns). Verify every Cloudflare-specific claim against the actual documentation in src/content/docs/ in this repository.
Over-generalization across categories — When a simplification says "all records," "the IP address" (singular), or "every request," verify whether the claim actually applies universally. DNS record types (A, AAAA, CNAME, MX, TXT, NS) have different proxying rules. Cloudflare returns multiple anycast IPs, not one. Protocol behaviors, plan-level features, and configuration defaults frequently vary by record type, plan, or product tier. Check that quantifiers ("all," "every," "any") and articles ("the" implying singular) are accurate. A statement that is true for A records may be false for MX records; a feature available on Enterprise may not exist on Free.
src/content/docs/) to find the strongest available citation:[file path]:[line number]"| # | Claim (exact text) | Source | Status |
|---|---|---|---|
| 1 | "Workers KV supports keys up to 512 bytes" | src/content/docs/kv/api/write-key-value-pairs.mdx | ✅ sourced |
| 2 | "Latency is under 50 ms globally" | — | ❌ unsourced (high) |
| 3 | "instructs crawlers to stay away from your content" | src/content/docs/bots/robots-txt.mdx — source says per-path allow/disallow, not blanket block | ⚠️ misleading (critical) |
| 4 | "zones pair with resolver policies" | present in original — path/to/file.mdx:34 | ✅ sourced (original) |
⚠️ misleading and quote the relevant part of the source.❌ unsourced and state what you searched.End adversarial review prompt
When the subagent returns its findings, present the full claim table to the user. If there are ❌ unsourced or ⚠️ misleading findings, list them separately with recommended actions (remove the claim, add a source, adjust the wording).
Then ask: What would you like to do next?
Should I simplify a term?
Should I add content?
Should I spell out a consequence or implication?
Should I add a GlossaryTooltip?
Should I add synonyms or aliases for a term?
Should I remove content?
Before finalizing, verify:
These are patterns that feel like improvements but consistently make documentation worse. They were identified from human review of AI-generated edits.
1. Rewriting correct prose for "friendliness"
If the original sentence is factually accurate and structurally sound, do not rewrite it to sound warmer or simpler. Rewrites introduce risk of mechanical inaccuracy. Only touch sentences that have a concrete problem (wrong fact, ambiguous referent, undefined term, broken logic).
2. Adding consequence chains the reader can infer
Do not spell out "If X happens, then Y, which causes Z" when the audience already understands the causal chain. Example: telling a network engineer that blocked health checks cause tunnels to go unhealthy is stating the obvious. Ask: "Would a reasonable reader of this page already know this consequence?" If yes, omit it.
3. Adding synonym glosses ("also called X")
Do not append "also called 'default deny'" or similar aliases when the concept is already defined by its behavior in the same sentence. One definition is enough. Synonym stacking clutters without adding understanding.
4. Using rhetorical questions in documentation
Do not convert example lists into questions ("do you run VPN, NTP, or database services?"). State examples as examples. Documentation is not a conversation.
5. Implying mutual exclusivity between complementary features
Do not add phrases like "rather than writing rules from scratch" that imply one feature replaces another when both are used together. When two features complement each other, cross-reference them instead of contrasting them.
6. Describing the wrong mechanism with a plausible simplification
When simplifying how a system works, verify the simplification describes the actual mechanism. For example, saying "a Custom rule can change a Managed rule's action" is wrong if Custom rules actually take precedence due to evaluation order. A plausible-sounding but mechanically incorrect explanation is worse than the original jargon.
7. Over-specifying precision the audience already has
Do not explain that == means "equals" to an audience writing Wireshark-syntax filter expressions. Calibrate the level of inline definition to the actual audience of the page, not to a hypothetical beginner.
8. Using casual register in formal docs
"Let you" is too casual for Cloudflare docs. Use "allow you to" or state the action directly. Match the existing voice of the documentation, not a conversational ideal.
9. Conflating related but distinct concepts in a single statement
When simplifying, do not merge two separate concepts into one sentence in a way that implies they are the same thing or that one requires the other. Example: "CNAME flattening resolves the chain and returns a Cloudflare anycast IP" conflates CNAME flattening (a DNS resolution behavior) with proxying (a traffic-routing decision) — you can have CNAME flattening with proxy off, in which case no Cloudflare IP is returned. Similarly, "Full setup means Cloudflare is your only DNS provider" conflates the setup type (using Cloudflare authoritative nameservers) with exclusivity (having no other provider). Each concept should be introduced on its own terms, even if they often appear together. If two features interact, describe them separately and then explain the relationship.
Produce output following this template exactly. All sections are required.
# ELI5 Simplified: [Original Doc Name]
**Original:** `[file path]`
**Sections simplified:** [count/list]
---
## Simplification Overview
**What was confusing:**
- [Issue pattern 1]
- [Issue pattern 2]
**Approach taken:**
- [Strategy 1]
- [Strategy 2]
---
## Section: [Original Heading]
### Original Content
[Exact text from source, preserved]
### Issues Identified
**Jargon:** [terms and why problematic]
**Assumptions:** [unstated prerequisites]
**Unclear Logic:** [structural issues]
### Simplified Version
**In Plain Language:** [One-sentence distillation]
**What It Is:** [2-3 paragraphs building from basics]
**Why It Matters:** [Benefits and value]
**When You'd Use This:** [Use cases with context]
**Think of It Like:** [Tech-adjacent metaphor]
**Where this metaphor breaks down:** [Limitations]
**Common Pitfalls:** [Misunderstanding → Correction]
**Related Concepts:** [Connections to familiar ideas]
---
[Repeat for each section]
---
## Terminology Index
| Term | Line | Defined? | Suggested Action |
| ---- | ---- | -------- | ---------------- |
| [term] | [line number] | Yes/No | Add glossary tooltip / Add cross-link to [page] / Add inline definition |
---
## Summary & Recommendations
**Key improvements made:** [list]
**Patterns noticed:** [meta-analysis]
## Suggestions for Enhancement
Line-numbered recommendations for further improvements:
| Line(s) | Current Approach | Suggested Enhancement | Why | Priority |
| ------- | ---------------- | --------------------- | --- | -------- |
| [lines] | [what exists] | [what to change] | [why it improves accessibility] | High/Medium/Low |references/content-type-guide.mdreferences/pattern-library.mdEXAMPLES_REFERENCE.md© try-works, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 5 other files (references) in .agents/skills/eli5 of try-works/role-model.
Open the folder on GitHubat commit de1c04a
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in try-works/role-model, which our catalogue first saw on October 7, 2026.
Eli5 next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Eli5 this skilltry-works/role-model | 118 | 1 repos | ~7.1k | Automated safety check: Pass | MIT | |
| TransformersK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~2.8k | Automated safety check: Notes | Apache-2.0 | |
| Hugging Face Transformers Usagedavila7/claude-code-templates | 32k | 12 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Transformers JSsickn33/agentic-awesome-skills | 47k | 1 repos | ~444 | Automated safety check: Pass | Apache-2.0 | |
| Eli5DreambigOu/ELI5 | 1.7k | — | ~2k | Automated safety check: Pass | MIT | |
| Fp Data Transformssickn33/agentic-awesome-skills | 47k | 2 repos | ~2.4k | Automated safety check: Pass | MIT |
K-Dense-AI/scientific-agent-skills
Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks.
davila7/claude-code-templates
Loads pre-trained Hugging Face Transformers models for text, vision and audio tasks, runs inference with pipelines and fine-tunes on custom datasets.
sickn33/agentic-awesome-skills
Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript.
DreambigOu/ELI5
Explain any topic, code, concept, or error tailored to a specific audience's level of understanding.
sickn33/agentic-awesome-skills
Everyday data transformations using functional patterns - arrays, objects, grouping, aggregation, and null-safe access
coldteadotai/pr-lens
WHAT: Explains a codebase, a folder, a feature, a command or a pull request to someone who knows nothing about it, as a PR Lens canvas whose walkthrough builds the picture one part at a time.
try-works/role-model
Master end-to-end testing with Playwright and Cypress to build reliable test suites that catch bugs, improve confidence, and enable fast deployment.
try-works/role-model
React UI component systems with TailwindCSS + Radix + shadcn/ui.
try-works/role-model
Apply a Swiss International Style design system using Tailwind CSS.
try-works/role-model
A skill your agent uses when contributing to the Cloudflare Docs repository — writing or editing documentation pages, choosing content types or components, adding changelog entries, reviewing docs…
try-works/role-model
A skill your agent uses when migrating a codebase from Effect v3 to Effect v4, upgrading effect or any @effect/ package across the v3/v4 boundary.
try-works/role-model
Set up Cloudflare Turnstile end-to-end in a project — scan the codebase, create the widget via the Cloudflare API, deploy the managed siteverify Worker, write the frontend snippets, validate, and…
Transform technical jargon into clear explanations using before/after comparisons, metaphors, and practical context. Eli5 is an agent skill from try-works/role-model.
Run `npx skills add try-works/role-model --skill eli5 -a claude-code`. Or copy the skill folder (.agents/skills/eli5 in try-works/role-model) into .claude/skills/eli5 in your project. Claude Code loads it when a task matches its description.
Run `npx skills add try-works/role-model --skill eli5 -a codex`. Or copy the skill folder (.agents/skills/eli5 in try-works/role-model) into .agents/skills/eli5 in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add try-works/role-model --skill eli5 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/eli5, .gemini/skills/eli5, .github/skills/eli5 and .opencode/skills/eli5 in your project.
SKILL.md names no scripts, command-line tools or credentials: Eli5 is instructions for the agent only. Compatibility (from SKILL.md): opencode.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Eli5 is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 7.1k tokens (SKILL.md is roughly 28k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 22k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Eli5: Transformers (K-Dense-AI/scientific-agent-skills, 48k stars), Hugging Face Transformers Usage (davila7/claude-code-templates, 32k stars), Transformers JS (sickn33/agentic-awesome-skills, 47k stars) and Eli5 (DreambigOu/ELI5, 1.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
try-works (a GitHub user) maintains it in try-works/role-model, which has 118 GitHub stars. The repository holds 19 skills in this directory. The repository was last updated on October 7, 2026.
Source: try-works/role-model on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.