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.
npx skills add bestdeejay-design/agent-skills --skill repo-readme-assetsgit clone --depth 1 https://github.com/bestdeejay-design/agent-skillsWrote 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/skills/bestdeejay-design/agent-skills/repo-readme-assets)<a href="https://agentmods.dev/skills/bestdeejay-design/agent-skills/repo-readme-assets"><img src="https://agentmods.dev/badge/skills/bestdeejay-design/agent-skills/repo-readme-assets/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/skills/bestdeejay-design/agent-skills/repo-readme-assets"><img src="https://agentmods.dev/badge/skills/bestdeejay-design/agent-skills/repo-readme-assets.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00128 | $0.01707 |
| Opus 5 | $0.00064 | $0.00853 |
| Sonnet 5 | $0.00026 | $0.00341 |
| Haiku 4.5 | $0.00013 | $0.00171 |
Grade A, and why
repo-readme-assets 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 today.
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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repo Readme Assets — README + animated SVG header/footer
Use this skill to create or update a repository README and its visual header/footer
with local animated SVG assets. Zero external services: no capsule-render, no shields
generators, no URL banners. Animation is SMIL only (<animate>, <animateTransform>)
so it works inside <img> on GitHub without scripts or network requests.
When to use
- A repository needs a README with a header/footer banner (local animated SVG).
- Major change happened and the README must reflect the current project state.
- User asks for "readme header", "animated svg", "waving svg", "svg banner", "readme assets", "readme visual", "smil animation".
Do NOT use
- README is already current and the user did not request changes — do not "improve".
- A single tiny fix (e.g. one badge) — edit directly, no skill needed.
- For legal/community files (LICENSE, CONTRIBUTING, SECURITY) — use
repo-community-files. - For description/topics/Pages/community-health — use
repo-metadata-health. - For the social preview PNG — use
repo-social-preview.
Files
SKILL.md— this filescripts/generate_assets.py— deterministic generation ofassets/header.svg+assets/footer.svgscripts/extract_context.py— auto-detect name/desc/stack/colors/username from git remotescripts/validate_svg.py— validate SVG against skill rules (SMIL, mask, morphing)references/svg-animation.md— full SVG animation spec + header/footer templatesreferences/svg-presets.md— the four presetsreferences/color-tokens.md— detected values (USERNAME/PROJECT_NAME/COLD/WARM)references/canonical-patterns.md— canonical references and gaps
Scripts
| Script | Purpose | Call |
|---|---|---|
generate_assets.py |
Deterministic assets/header.svg + assets/footer.svg (presets: --preset default|minimal|dark-first|monochrome) |
python3 scripts/generate_assets.py --name X --desc Y --user Z --cold #HEX --warm #HEX [--preset default] |
extract_context.py |
Auto-detect generation context from git remote | python3 scripts/extract_context.py [--path DIR] [--gh-repo owner/repo] [--text] |
validate_svg.py |
Validate SVG rules (SMIL, mask, d-path morphing) | python3 scripts/validate_svg.py assets/ |
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- readme.ru.md 1.9 KB
- references/canonical-patterns.md 18 KB
- references/color-tokens.md 5.6 KB
- references/svg-animation.md 21 KB
- references/svg-presets.md 3.2 KB
- scripts/extract_context.py 10 KB runs code
- scripts/generate_assets.py 15 KB runs code
- scripts/validate_svg.py 12 KB runs code
- skill.json 1.8 KB
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.
- today Changed · +8 lines 24236402c0b0
- 12d ago First seen · 116 lines · 128 tokens per session scan A 98734353290a
repo-readme-assets is a skill published in the GitHub repository bestdeejay-design/agent-skills (6 stars, last pushed yesterday), licensed MIT. It adds 128 tokens to every session and 1,707 once invoked, about $0.0006 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.
Other skills, from other repositories
workflow
Use when a task is too large for turn-by-turn orchestration and should run through the big-task workflow lane: system-wide changes, large migrations, repo-wide audits, high-confidence verification, or tasks explicitly asking to run a workflow. Claude Code uses native dynamic workflows; Codex, OpenCode, and Grok use…
skill-compiler
Automatic solved-to-skill compiler — detects novel task completions and autonomously drafts new SKILL.md files. Stolen from Hermes Agent's learning loop (NousResearch, 2026-05-11).
context-compactor
9-section context compression with analysis scratchpad. Adapted from Claude Code's /compact system (2026-03-31).
daemon-loop
Autonomous recurring agent tasks — converts workflows into persistent background daemons that run on intervals. Stolen from Boris Cherny's Claude Code /loop pattern (2026-03-31).
trade-journal-analyzer
Unified post-trade analytics: journal pattern extraction + drawdown classification. Absorbs: drawdown-classifier.
Deep Research Loop
Multi-step web research, compilation, and synthesis workflow. Scrapes multiple sources, cross-references claims, and produces a structured research brief.