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 agentmods add skills/codemie-ai/codemie-code/codemie-html-reportnpx skills add codemie-ai/codemie-code --skill codemie-html-reportgit clone --depth 1 https://github.com/codemie-ai/codemie-codeWhat 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 | $0.00193 | $0.03475 |
| Opus 5 | $0.00097 | $0.01737 |
| Sonnet 5 | $0.00039 | $0.00695 |
| Haiku 4.5 | $0.00019 | $0.00347 |
Grade C, and why
codemie-html-report scanned grade C with 1 finding 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 2d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf "<OUT>" How it starts
The opening of the file, as written. The whole thing — 365 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CodeMie HTML Report Builder
You are building a standalone HTML page that visually matches the CodeMie (EPAM AI/Run) product UI. The design system is a dark-first, professional theme with Inter font, subtle borders, and semantic color tokens. Every page you produce should feel like a native screen of the CodeMie platform.
Step 1 — CSS placeholder
Do NOT read any CSS files. Do NOT inline any CSS yourself.
In the <style> block write exactly this one token as the only content:
/* __CODEMIE_CSS__ */
A post-processing script will replace this token with the full design system CSS after you write the file. All component classes are documented in Steps 3 and 4 — use them freely without reading the source files.
Step 1.5 — Data placeholders (analytics pipeline only — skip for standalone use)
Backwards compatibility: This step applies only when this skill is invoked from the codemie-analytics skill as part of its report pipeline. If you are generating a standalone HTML page directly for a user request, skip this step entirely and embed any data inline as regular JS variables.
When invoked from codemie-analytics, all JS data arrays must use
/*__DATA:name__*/ placeholders instead of inline values. The analytics skill's
inject-data.js step replaces these after the HTML file is written.
<script>
/* Data is injected by inject-data.js after this file is written — do NOT hardcode arrays */
const LEADERBOARD = /*__DATA:leaderboard-top__*/;
const SUMMARIES = /*__DATA:summaries__*/;
const LLM_DATA = /*__DATA:llms-usage__*/;
</script>
Rules for analytics-pipeline placeholders:
- The placeholder name must exactly match the JSON filename without the
.jsonextension./*__DATA:leaderboard-top__*/is only replaced whenleaderboard-top.jsonexists. Wrong name → the placeholder is silently skipped byinject-data.js. - Every JS variable populated from an API response must use a placeholder.
- Hardcoded lookup tables (tier colours, dimension labels, etc.) are fine as regular JS.
- Never mix placeholders with inline data in the same variable declaration.
What ships with it
12 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.md 2.0 KB
- scripts/inject-css.js 1.3 KB runs code
- scripts/inject-data.js 2.0 KB runs code
- style-guide/css/base.css 4.2 KB
- style-guide/css/bundle.css 47 KB
- style-guide/css/buttons.css 5.9 KB
- style-guide/css/components.css 15 KB
- style-guide/css/forms.css 12 KB
- style-guide/css/layout.css 8.9 KB
- style-guide/css/tokens.css 12 KB
- style-guide/css/typography.css 3.9 KB
- style-guide/css/utilities.css 9.1 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.
- 2d ago First seen · 365 lines · 193 tokens per session scan C 6a2defde3f51
codemie-html-report is a skill published in the GitHub repository codemie-ai/codemie-code (276 stars, last pushed 3d ago), licensed Apache-2.0. It adds 193 tokens to every session and 3,475 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.