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/miaoge-ge/coding-agent-skills/competitive-programming-expertnpx skills add Miaoge-Ge/coding-agent-skills --skill competitive-programming-expertgit clone --depth 1 https://github.com/Miaoge-Ge/coding-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/miaoge-ge/coding-agent-skills/competitive-programming-expert)<a href="https://agentmods.dev/skills/miaoge-ge/coding-agent-skills/competitive-programming-expert"><img src="https://agentmods.dev/badge/skills/miaoge-ge/coding-agent-skills/competitive-programming-expert.svg" alt="Measured on agentmods" 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 | $0.00067 | $0.00939 |
| Opus 5 | $0.00034 | $0.00469 |
| Sonnet 5 | $0.00013 | $0.00188 |
| Haiku 4.5 | $0.00007 | $0.00094 |
Grade A, and why
competitive-programming-expert 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 5d 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.
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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitive Programming Problem Solver
Description
Solve competitive programming problems with optimal solutions, complexity analysis, and complete code implementation.
When to Use
- User provides problem link or description from LeetCode/Codeforces/AtCoder/ACM-ICPC platforms
- User requests "solve this algorithm problem" or "optimize this solution"
- User asks for specific algorithm/data structure implementation (e.g., "how to implement segment tree")
- User's code encounters TLE/MLE/WA and needs debugging
- User asks for solution templates or patterns for certain problem types
When NOT to Use
- User only asks about algorithm concepts or theory without specific problem
- User needs algorithm design for software engineering, not competitive programming
- User is doing system design or architecture problems
- User only needs code completion or syntax help without algorithmic logic
Input
{
problem: string // Problem description or link
platform?: string // Platform name (leetcode/codeforces/atcoder, etc.)
language?: string // Preferred language (default: C++ or Python)
userCode?: string // User's existing code (for optimization/debugging)
constraints?: { // Problem constraints
timeLimit?: string // e.g., "1s", "2s"
memoryLimit?: string // e.g., "256MB"
inputSize?: string // e.g., "n ≤ 10^5"
}
}
Output
{
analysis: {
type: string // Problem type (DP/Graph/Greedy/Number Theory, etc.)
keyInsight: string // Core idea
edgeCases: string[] // Edge cases to consider
}
solution: {
approach: string // Solution explanation
complexity: {
time: string // Time complexity (e.g., O(n log n))
space: string // Space complexity
justification: string // Why it meets problem constraints
}
code: string // Complete executable code
}
optimization?: string // Optional optimization suggestions
}
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.
- 5d ago First seen · 102 lines · 67 tokens per session scan A 2c96dfc885e4
competitive-programming-expert is a skill published in the GitHub repository Miaoge-Ge/coding-agent-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 67 tokens to every session and 939 once invoked, about $0.0003 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
lean
Dense answers: cut filler, keep substance. Prose only compression, Laravel/PHP aware. Open REFERENCE.md only when asked how lean decides.
typescript_mastery
Curated Knowledge API for AI Agents — 68 MCP tools, 200+ skill packs, 46K chunks, semantic search over 670K vectors, 5-layer validation pipeline. Works with Claude Code, Cursor, Cline, Windsurf.
change-quiz
Generate one droppable self-contained HTML report (never a Cursor canvas) explaining a change set, ending with a quiz the user must pass before merging. Use when the user says "quiz me", "考考我", "change quiz", "变更测验", or, after a large change or session, wants to verify they truly understand it — e.g. "merge…
ai-prompt-evaluator
Activate when designing, evaluating, red-teaming, and refining LLM system prompts, agent instructions, structured JSON schemas, and defense boundaries against prompt injections and hallucinations — trigger phrasings include "evaluate my system prompt", "red-team this AI prompt", "improve my prompt to prevent…
springboot-patterns
Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend work.
python-patterns
Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust, efficient, and maintainable Python applications.