A collection of agent skills that give AI agents structured, reusable workflows for tackling complex problems.
概览
A collection of agent skills that give AI agents structured, reusable workflows for tackling complex problems. These skills go beyond simple prompting to deliver consistently higher-quality results. Skills like evo-search and tournament-search generate and evaluate multiple candidate responses across several rounds. Certain decorators in prompt-decorators also add extra reasoning or refinement steps. This increases token consumption significantly compared to a single plain prompt. The benefit is higher response quality, but it is not free. If you are on a metered subscription, running these skills can cost noticeably more. Consider using lighter configurations (for example, fewer iterations, a smaller population, or simpler decorators) when your token budget is limited. Solves complex, open-ended problems using a .
README
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Agent Skills by Mostapha Kalami Heris
A collection of agent skills that give AI agents structured, reusable workflows for tackling complex problems. These skills go beyond simple prompting to deliver consistently higher-quality results.
More skills will be added over time.
Table of Contents
Skills
Note on token usage: Skills like
evo-searchandtournament-searchgenerate and evaluate multiple candidate responses across several rounds. Certain decorators inprompt-decoratorsalso add extra reasoning or refinement steps. This increases token consumption significantly compared to a single plain prompt. The benefit is higher response quality, but it is not free. If you are on a metered subscription, running these skills can cost noticeably more. Consider using lighter configurations (for example, fewer iterations, a smaller population, or simpler decorators) when your token budget is limited.
evo-search
Solves complex, open-ended problems using a genetic-algorithm-style search loop.
It generates a diverse initial population of candidate answers, scores each one against a weighted rubric, and then repeatedly applies selection, crossover, and mutation to produce stronger solutions. The final output includes the top 3 solutions with scores, a contrast table, and an evolution trace.
When this skill is triggered:
- The user asks for an “evolutionary search”, “genetic algorithm”, “evolve an answer”, or “breed solutions”
- The user says “give me multiple approaches and refine the best one”
- The problem is complex or open-ended with no single correct answer, and the user wants a deeply explored result
Key parameters (set in plain language):
| Parameter | Default | Effect |
|---|---|---|
population |
6 | Candidates per generation |
iterations |
5 | Evolution cycles |
mutation_rate |
0.2 | Fraction of offspring mutated |
top_k |
3 | Final solutions shown in full |
Install:
- CLI tools: run in your terminal:
npx skills@latest add smkalami/skills/evo-search - AI assistant platforms: download and upload
evo-search.skill
Example usage:
Use evo-search to invent a new programming paradigm that blends constraint propagation
with biological growth patterns. Something that does not exist yet but could realistically推荐工具
换一个关键词，或者移除筛选条件。
安装
npx skillfish add smkalami/skills