Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add sequenzia/agent-alchemy/plugin install agent-alchemy-cs-toolsWrote 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/sequenzia/agent-alchemy/solve)<a href="https://agentmods.dev/skills/sequenzia/agent-alchemy/solve"><img src="https://agentmods.dev/badge/skills/sequenzia/agent-alchemy/solve/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/sequenzia/agent-alchemy/solve"><img src="https://agentmods.dev/badge/skills/sequenzia/agent-alchemy/solve.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 | $0.00063 | $0.01600 |
| Opus 5.5 | $0.00025 | $0.00640 |
| Sonnet 5.5 | $0.00013 | $0.00320 |
| Haiku 4.5 | $0.00006 | $0.00160 |
Grade A, and why
solve 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 1mo 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 — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitive Programming Problem Solver
Solve competitive programming and LeetCode-style problems with clear educational explanations, step-by-step walkthroughs, and verified Python solutions.
CRITICAL: Complete ALL 4 phases. Do not stop after classification or skip the agent.
Phase 1: Parse Input
Goal: Extract and understand the problem statement.
If $ARGUMENTS is provided, parse the problem statement from it. Extract:
- Problem description and objective
- Input/output format
- Constraints (N, M, value ranges)
- Example test cases with expected outputs
- Any special conditions (modular arithmetic, multiple test cases, interactive)
If $ARGUMENTS is empty or unclear, use AskUserQuestion to request the problem:
AskUserQuestion:
question: "Please provide the problem statement. You can paste the full text, describe it in your own words, or provide a link."
options:
- label: "Paste problem text"
description: "Paste the full problem statement including constraints and examples"
- label: "Describe the problem"
description: "Describe what the problem asks in your own words"
If the problem statement is ambiguous or missing key information (constraints, examples), ask for clarification before proceeding.
Phase 2: Classify Problem
Goal: Determine the algorithmic category, technique, and difficulty.
Analyze the problem to determine:
2.1 Primary Category
Match to one of:
- Dynamic Programming — optimization over subsequences, counting ways, overlapping subproblems
- Graph Algorithms — connectivity, shortest paths, traversal, network problems
- Search and Optimization — binary search, two pointers, greedy, interval problems
- Data Structures — specialized structures needed (heap, trie, segment tree)
- Math and Combinatorics — number theory, counting, modular arithmetic, game theory
- String Algorithms — pattern matching, palindromes, hashing
2.2 Sub-pattern
Identify the specific technique within the category (e.g., "0/1 Knapsack", "Dijkstra", "Sliding Window").
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.
- 1mo ago First seen · 165 lines · 63 tokens per session scan A fe7a65f2abbb
solve is a skill published in the GitHub repository sequenzia/agent-alchemy (45 stars, last pushed 4mo ago), licensed MIT. It adds 63 tokens to every session and 1,600 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
Other skills, from other repositories
ccc-research
Research before you build: cited multi-source research, spec interviews, cross-model review, literature reviews, competitive and trend analysis, and large-document or large-codebase ingestion. Use when the user wants options compared, prior art found, a spec defined, or something too big summarized.
add-didactic-comments
Comment tagged files so the user learns the APIs they are studying, with a doc link in every comment.
gan-zhong-xue
A learning workflow that makes an AI explain code changes through questions, evidence, and underlying principles. It is designed to help developers understand work they asked an AI to do, rather than merely accept the result.
bro
Use when the user says an explanation was unclear, too technical, or full of jargon, or asks for plain language.
formal-methods-guide
A reference guide to formal methods, which use mathematics to describe and check how software should behave, with a focus on the VDM-SL specification language. It explains VDM-SL types, conditions, invariants, and proof obligations in developer-friendly terms.
quiz-me
Use right after writing or editing code or files for the user — before ending your turn — to quiz them on what was just built and confirm they actually understand it. Also triggers on "quiz me", "test my understanding", "check what I learned", "comprehension check", or recovering the understanding that vaporizes when…