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You can extend Hiroshi with any capability by creating a custom skill folder under ~/.hiroshi/skills/. Skills can be written in Python, Bash, PowerShell, or any language that reads from stdin and writes to stdout. Hiroshi picks them up automatically the next time it starts — no configuration changes required.
Skills run with your user account’s filesystem permissions. Review any third-party skill code carefully before adding it to your skills directory.

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Creating a skill

1

Create a skill folder

Create a new directory inside ~/.hiroshi/skills/ using the name you want the agent to call:
mkdir -p ~/.hiroshi/skills/my_skill
2

Create a SKILL.md manifest

Inside the folder, create a SKILL.md file with YAML frontmatter. Hiroshi parses this file to register the skill name, description, and expected input schema:
---
name: my_skill
description: "What this skill does in one sentence"
schema: '{ "param1": "string", "param2": "number" }'
---
# My Skill

Extended description of the skill for the agent.
The body text below the frontmatter is available for additional context but the three frontmatter fields are what Hiroshi reads at registration time.
3

Create the executable script

Add an executable script to the same folder. The filename can be anything — Hiroshi picks up the first non-SKILL.md file it finds. Give the file an extension that matches the runtime you want to use (.py, .sh, .ps1, .bat/.cmd), or place a compiled binary with no extension.For example: ~/.hiroshi/skills/my_skill/my_skill.py
4

Restart Hiroshi

Skills are loaded at startup. Restart Hiroshi to pick up the new skill, and it will be available to the agent immediately.

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SKILL.md format

The SKILL.md frontmatter block must open and close with ---. Hiroshi reads three fields:
FieldRequiredDescription
nameYesThe identifier the agent uses to call the skill. Must match the folder name.
descriptionYesShown to the agent as the tool description. Write this carefully — the agent uses it to decide when to call the skill. Be specific about what the skill does and what it returns.
schemaYesA JSON object (as a string) describing the input parameters the script expects. The agent uses this to construct valid arguments.
If name is missing or empty, Hiroshi falls back to the folder name as the skill name.

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Script interface

Your script communicates with Hiroshi through standard input and output:
  • Input — Hiroshi writes the arguments as a JSON object to the script’s stdin. Read and parse it with json.loads(sys.stdin.read()) (Python) or jq (Bash).
  • Output — Write results to stdout. Everything written to stdout is captured and returned to the agent.
  • Exit codes — A non-zero exit code is treated as an error. The agent will receive both the stdout and stderr output along with the error status.
  • Timeout — Scripts have a 10-second execution timeout. If your script does not exit within 10 seconds, Hiroshi kills the process and reports a timeout error to the agent.
  • Working directory — The script’s working directory is set to the sandbox_path defined in your config (~/.hiroshi/workspace by default).

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Complete Python example

The following skill counts the words in a text string. It demonstrates the full structure: a SKILL.md manifest paired with a Python script that reads JSON from stdin and writes a plain-text result to stdout.
SKILL.md
---
name: word_count
description: "Counts the number of words in a given text string."
schema: '{ "text": "string" }'
---
# Word Count Skill

Counts words in the provided text.
word_count.py
import sys
import json

def main():
    try:
        args = json.loads(sys.stdin.read())
        text = args.get("text", "")
        count = len(text.split())
        print(f"Word count: {count}")
    except Exception as e:
        print(f"Error: {e}")

if __name__ == '__main__':
    main()
Place both files at: 
~/.hiroshi/skills/word_count/
├── SKILL.md
└── word_count.py

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Bash skill example

Bash skills work identically — read JSON from stdin if you need parameters, or skip stdin entirely for skills that take no input.
SKILL.md
---
name: disk_usage
description: "Reports disk usage of the current workspace directory."
schema: '{ }'
---
disk_usage.sh
#!/bin/bash
du -sh . 2>/dev/null || echo "Could not check disk usage"

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Tips

Write descriptions that are specific and action-oriented. The agent reads your description field to decide when to call each skill — vague descriptions lead to missed or incorrect invocations.
Test your skills manually before relying on them inside a conversation. Pipe a sample JSON payload directly to the script:
echo '{"text": "hello world"}' | python ~/.hiroshi/skills/word_count/word_count.py
Keep scripts fast. Skills run synchronously during an agent turn, so a slow script blocks the entire response. Aim to complete well within the 10-second limit — consider offloading heavy work to a background process and having the skill return a job ID instead.