What are some things you've automated using Axe?
I have a few flows I'm using it for and have a growing list of things I want to automate. Basically, if there is a process that takes a human to do (like creating drafts or running scripts with variable data) I make axe do it. 1. I have a flow where I pass in a youtube video and the first agent calls an api to get the transcript, the second converts that transcript into a blog-like post, and the third uploads that bl…
Show HN: Axe – A 12MB binary that replaces your AI framework
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#138Earlier quoted context omitted.
I was looking at something similar. What does your agent-lib.sh look like?
Something like this: https://github.com/craigjperry2/tiny-agents/blob/main/lib/ag...
Would love to see your tiny agents project. But understand that it might contain something sensitive and will therefore stay private.
Re: Show HN: Axe – A 12MB binary that replaces your AI framework
#139This is what I've been trying to get nanobot to do, so thanks for sharing this. I plan to use this for workflow definitions like filesystems. I have a known workflow to create an RPG character with steps, lets automate some of the boilerplate by having a succession of LLMs read my preferences about each step and apply their particular pieces of data to that step of the workflow, outputting their result to successive…
Where is the nanobot approach not working for you?
Re: Show HN: Axe – A 12MB binary that replaces your AI framework
#140Earlier quoted context omitted.
Something like this: https://github.com/craigjperry2/tiny-agents/blob/main/lib/ag...
Bump. Would love to see your tiny agents project. But understand that it might contain something sensitive and will therefore stay private.
#!/usr/bin/env bash # agent-lib.sh — shared plumbing for all claude -p agents
AGENTS_DIR="${AGENTS_DIR:-$HOME/Code/github.com/craigjperry2/tiny-agents}" SKILLS_DIR="$AGENTS_DIR/skills" CLAUDE_OPTS="${CLAUDE_OPTS:-}"
# Build a system prompt by concatenating skill files # Usage: load_skills core/unix-output.md domain/git.md output/plain-text.md load_skills() { local combined="" for skill in "$@"; do local path="$SKILLS_DIR/$skill" if [[ -f "$path" ]]; then combined+=$'\n\n'"$(cat "$path")" else echo "[agent-lib] WARNING: skill not found: $skill" >&2 fi done echo "$combined" }
# Core invocation: reads stdin, prepends system prompt, calls claude -p # Usage: run_agent [extra claude opts...] run_agent() { local system_prompt="$1" shift local stdin_content stdin_content=$(cat) # buffer stdin
if [[ -z "$stdin_content" ]]; then
echo "[agent] ERROR: no input on stdin" >&2
exit 1
fi
# Combine system prompt with stdin as user message
printf '%s' "$stdin_content" \
| claude -p \
--system-prompt "$system_prompt" \
--output-format text \
$CLAUDE_OPTS \
"$@"
}# Run agent then pipe through a guard # Usage: run_agent_guarded run_agent_guarded() { local guard="$1" shift local system_prompt="$1" shift
local output
output=$(run_agent "$system_prompt" "$@")
local agent_exit=$?
if [[ $agent_exit -ne 0 ]]; then
echo "$output"
exit $agent_exit
fi
# Pass through guard
echo "$output" | "$AGENTS_DIR/guards/$guard"
exit $?
}# For structured output: run agent then validate with jq run_json_agent() { local system_prompt="$1" shift run_agent "$system_prompt" --output-format text "$@" | guard-json-valid }