Season Words: A Simple Skill for Haiku-Powered Agents

Where this fits

You're building an agent that generates haiku for a daily poetry bot, a meditation app, or a creative writing assistant. The output feels flat—no sense of time or place. You need a seasonal touch, but hardcoding a list of kigo (season words) bloats your prompt. This skill solves that by providing a concise, curated set of seasonal references your agent can pull from on demand.

Why agents benefit

• Zero-prompt pollution: Instead of stuffing a long list into your system prompt, the agent can call the skill only when a haiku demands a seasonal cue.
• Context-aware suggestions: The skill returns the right season's words based on the user's request or the current date, making the haiku feel anchored.
• Parsable output: The skill's data is clean and structured, so your agent can reliably extract a word and weave it into the poem's syntax.
• Lightweight and fast: At under 100 tokens, it doesn't slow down inference or eat context window.
• Customizable: Developers can fork the skill to add their own regional or cultural kigo without touching the agent's core logic.

Practical scenarios

1. A daily haiku generator

Your agent writes a new haiku each morning. By calling season-words, it picks a current-season word (e.g., "cicada" in summer) and builds the poem around it—no need to update the agent when seasons change.

2. A poetry prompt builder for classrooms

Teachers use your agent to generate writing prompts. The skill lets the agent offer season-specific challenges, like "write a haiku about the first frost," making the activity more engaging and educational.

3. A cultural archive bot

A bot that curates historical haiku wants to tag poems by season. The skill provides a standardized vocabulary, enabling consistent metadata and searchable tags across a large corpus.

Add it to your agent workflow

Install with one command:

npx skills add fastagent-sh/fastagent --skill season-words

Then in your agent's tool config, expose it as a simple lookup:

// Example: using the skill in a haiku generation step
const season = new Date().getMonth() >= 2 && new Date().getMonth() <= 4 ? "spring" : "summer";
const kigoList = await callSkill("season-words", { season });
const kigo = pickRandom(kigoList);
const haiku = await generateHaiku({ theme: kigo });

This tiny integration keeps your poetry agent fresh without hardcoding a seasonal lexicon.

Compare before adopting

Before you commit, compare this skill against alternatives. Look at quality signals—are the kigo poetic and authentic, or just generic? Check maintenance freshness: is the repo actively updated (the fastagent-sh project has 56 stars and recent commits)? Consider alternatives like hardcoding your own list or using a larger poetry package; the skill wins on simplicity. Finally, assess workflow fit: does the skill's output format match your agent's tool-calling pattern? If you only need a few words, this is perfect; for deep poetry analysis, you might need more.

Why it is worth tracking

This skill is a great example of how a focused, single-purpose dataset can make an agent dramatically better at a specific task. With 56 stars and a clean README, it's young but shows community interest. Track it as a model for building structured knowledge skills—and check back as fastagent-sh expands into other domains. For more skills like this, visit OpenAgentSkill.