Agent Customization

Organization

aspenkit

agent-customization

LLM-powered injection of project context into installed agent templates via `aspens customize agents`

Overview

Publisher	aspenkit
Repository	`aspens`
Skill name	`agent-customization`
Stars	102
Forks	7
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by aspenkit on GitHub. Read the source before you install it.

Installation

Install the Agent Customization AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/aspenkit/aspens/tree/main/.agents/skills/agent-customization
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/aspenkit/aspens.git /tmp/aspens
mkdir -p .claude/skills
cp -r /tmp/aspens/.agents/skills/agent-customization .claude/skills/agent-customization

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Customization in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agent Customization on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agent Customization is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

You are working on agent customization — the feature that reads a project's skills and AGENTS.md, then uses Claude CLI to inject project-specific context into generic agent files in .claude/agents/.

Domain purpose

aspens customize agents makes generic, bundled agent templates project-aware. It pulls the repo's skills + AGENTS.md as ground truth and asks Claude to add a tech-stack line, 3-5 project conventions, and real commands into each agent — without touching the agent's core logic.

Business rules / invariants

Claude-only feature. Throws CliError for Codex-only repos (config.targets === ['codex']). Codex CLI has no agent concept.
Base skill is required. Pre-flight throws CliError("Run 'aspens doc init' first — base skill is required for agent context.") if .agents/skills/base/SKILL.md is missing.
Skills (.claude/skills/**) are the single source of truth for project context. The prompt must not invent other context directories.
Read-only tools only. Claude is invoked with allowedTools: ['Read', 'Glob', 'Grep'] — no edits/writes from the LLM itself.
Output paths restricted to .claude/. parseFileOutput() rejects anything else; writeSkillFiles(..., { force: true }) does the actual write.

Non-obvious behaviors

Frontmatter preservation is split across LLM + code. The prompt instructs Claude to preserve YAML frontmatter verbatim (including NOT adding a skills: line). Then maybeInjectBaseSkill() post-processes each returned file to add skills: [base] into the frontmatter — this keeps agents valid even when installed via aspens add agent without a prior doc init.
--reset semantics: without --reset, agents that already declare skills: are left alone; with --reset, any existing skills: line is overwritten to skills: [base]. Used to roll out v0.8 upgrades to previously-customized agents.
## Project context block is verbatim-preserved by the prompt — it carries conditional read instructions for code-map / domain skills.
AGENTS.md is truncated at 3000 chars in gatherProjectContext(); skills are passed in full.
Agent discovery: findAgents() recursively walks .claude/agents/, extracts name: via regex, falls back to filename if missing.
Default timeout 300s via resolveTimeout(options.timeout, 300); ASPENS_TIMEOUT env var honored with warning on invalid value.

Critical files (purpose, not inventory)

src/commands/customize.js — orchestrator: preflight, agent discovery, context gathering, per-agent Claude calls, post-LLM skills: [base] injection, write.
src/prompts/customize-agents.md — system prompt; enforces frontmatter + ## Project context preservation and bans file-inventory / hub-ranking output.

Critical Rules

Never let the LLM emit a skills: line — the prompt forbids it and the code adds it. If you change one, change both.
Never weaken path sanitization — only .claude/ paths may be written.
Never duplicate file-inventory or hub-ranking output in customized agents — the graph hook supplies that dynamically.
Do not bypass the base-skill preflight — agents without base context regress to generic behavior.

Last Updated: 2026-05-11

Frequently asked questions

What does the Agent Customization AI skill do?

LLM-powered injection of project context into installed agent templates via `aspens customize agents`

Why use Agent Customization on TypingMind?

Because you install it once and use it with any model. Agent Customization is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agent Customization in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aspenkit/aspens/tree/main/.agents/skills/agent-customization. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Agent Customization?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agent Customization?

As many as you like. As long as a model supports skills, you can use Agent Customization with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agent Customization AI skill free?

Yes. It is published on GitHub by aspenkit under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Domain purpose

Business rules / invariants

Non-obvious behaviors

Critical files (purpose, not inventory)

Critical Rules

Frequently asked questions

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