tigerless-labs/autoharness
Autoharness — a self-learning skill layer for Claude Code — distills skills from your real sessions, updates them as you work, and prunes the ones that stop getting used. No daemon, no benchmark.
ARCHETYPE
Pragmatist
A balanced, no-drama setup: some rules, some tools, nothing extreme.
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# review before running: this installs third-party code $ npx degit tigerless-labs/autoharness/agents ./rig-autoharness/agents $ npx degit tigerless-labs/autoharness/skills ./rig-autoharness/skills $ npx degit tigerless-labs/autoharness/hooks ./rig-autoharness/hooks
MCP servers are added to Claude Code at local scope; env vars are shown as YOUR_… placeholders — we never store values. Files are fetched with degit into a separate folder so you can review before merging.
$ npx degit tigerless-labs/autoharness/skills/learn .claude/skills/learn $ curl -fsSL --create-dirs -o .claude/agents/curator.md https://raw.githubusercontent.com/tigerless-labs/autoharness/main/agents/curator.md $ curl -fsSL --create-dirs -o .claude/agents/reflector.md https://raw.githubusercontent.com/tigerless-labs/autoharness/main/agents/reflector.md
This rig commits no guardrails. Here is the community baseline instead — the deny/ask rules most often found across all 6,413 rigs:
{
"permissions": {
"deny": [
"Read(~/.ssh/**)",
"Read(**/.env)",
"Bash(rm -rf *)",
"Read(./.env)",
"Bash(rm -rf /)",
"Bash(git push --force:*)",
"Bash(sudo *)",
"Read(**/*.pem)",
"Bash(rm -rf /*)",
"Read(~/.aws/**)",
"Bash(rm -rf:*)",
"Read(.env)",
"Bash(git push --force*)",
"Read(**/*.key)",
"Read(./.env.*)",
"Read(**/.env.*)",
"Bash(sudo:*)",
"Bash(git reset --hard*)",
"Bash(git reset --hard:*)",
"Read(.env.*)"
],
"ask": [
"Bash(git push:*)",
"Bash(git push *)",
"Bash(git commit:*)",
"Bash(rm *)",
"Bash(rm:*)",
"Bash(wget *)",
"Bash(npm publish:*)",
"Bash(gh pr merge *)",
"Bash(chown *)",
"Bash(docker *)"
]
}
} MCP servers (1)
| server | source | est. tokens |
|---|---|---|
| stage_skill env: PYTHONPATH | local / custom | 2.5k |
Skills (1)
Subagents (2)
| curator model: haiku | Periodic consolidation pass — fold narrow agent-created skills into class-level umbrellas. Proposes intents only, never writes to disk. |
| reflector model: haiku | Distill a finished episode into skill changes aligned with the existing library. Compare-first preference, generation stays open; proposes intents only, never writes to disk. |
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