Technology · Agentic → Guardrails · Open Source · wiki:deep

Headroom

Headroom is a human-in-the-loop firewall for AI coding agents and a measurement study of when to escalate to humans. A worker agent proposes actions; a guardian (deterministic rules + LLM risk score) classifies each as safe / approval-required / blocked. Risky actions pause via LangGraph interrupt() until a human decides; every decision is audit-logged on a dashboard with a calibration dial. Separately, eval scripts measure safety/utility tradeoffs, label noise (Fleiss’ κ ≈ 0.52 on a persona proxy), and an inverted-U “oversight capacity” story. Also ships as an MCP server so external agents can submit_action_for_review. MIT; small research repo.

Why it matters here

Policy gates that escalate everything burn reviewer attention until dangerous actions slip through rubber stamps. Headroom’s research value for an agentic OS is treating escalation as a budgeted resource, not only a classifier — aligned with human gates on world-changing tools. Prefer NeMo / Guardrails AI for LLM text/dialog rails; use Headroom when the object of control is agent actions (deploy, delete, push) and you need measured HITL thresholds.

How it works

Worker proposes → guardian scores → SAFE runs, BLOCKED denies, APPROVAL pauses for human → resume/abort → append-only audit log. Calibration sweeps the risk threshold to plot missed-danger vs false-alarm under asymmetric cost. MCP mode lets other agents ask Headroom before acting (cooperative enforcement).

  1. Run dashboard (uvicorn headroom.api:app) or MCP server.
  2. Agent submits actions for review.
  3. Guardian returns allow / block / pending.
  4. Humans approve on the dashboard; logs feed calibration evals.

Related: guardrails-ai · llm-guard · nemo-guardrails · topics/13-governance-policy

Flow

Scroll inside the canvas to pan

When to reach for it

  • Use when: coding/ops agents need HITL action gates with calibrated escalation, or you are researching oversight fatigue.
  • Skip when: you only need prompt/output validators (guardrails-ai, nemo-guardrails) or archived scanners (llm-guard).
  • Prefer instead: NeMo/Guardrails AI for conversational I/O rails; production IAM/policy products for enterprise SSO — Headroom is measurement + firewall research.

Limits

  • Cooperative MCP: agents must ask — not a hard sandbox/host hook (roadmap notes enforcement ladder).
  • Tiny star / research scope: applied measurement project, not a novel-theory paper or enterprise product.
  • LLM judge cost/noise: calibration depends on labels and models — re-run on your action set.
  • Not the ledger: approvals are gates, not declared company configuration.

Linked from

What we checked

Claims below are backed by science sources on disk.

HITL firewall / measurement framing

turangenesis/headroom · MODERATE

Open Policy Agent (OPA) is an open source, general-purpose policy engine.

LangGraph interrupt pattern

LangGraph interrupt contrast · MODERATE

Open Policy Agent (OPA) is an open source, general-purpose policy engine that enables unified, context-aware policy enforcement across the entire stack.

Autonomy / oversight contrast

Earned Autonomy Protocol contrast · MODERATE

The Earned Autonomy Protocol is a governance framework for AI systems in consequential domains: trust is earned through evidence, not assumed at deployment.

In this research stack

Features and peers linked from the catalog map — not a second product surface.

Features it supports

Same cell

Stack

Document management

No DM vendor crosswalk edges yet.

Source

Primary repo github.com/turangenesis/headroom · Open Source

technologies/headroom/README.md

Research inventory

9 tags · 12 out · 14 in · 3 artifacts · 0 gaps · 33 corpus docs

Catalog tags

landscape.layer
Agentic
landscape.subcategory
Guardrails
license_tag
Open Source
maps.dm
present
maps.features
9
one_liner
Guardrails
review.depth
science
slug
headroom
title
Headroom

Artifacts

  • dm_map · present · technologies/headroom/document-management.md
  • features_map · present · technologies/headroom/features.md
  • readme · present · technologies/headroom/README.md

Out · alternative_to

Out · maps_to

In · alternative_to

In · in_stack

In · maps_to

Corpus tags

category
Agentic → Guardrails
dedication
open-source
feature
access-vs-authority
autonomy-levels
emergency-control
exception-first-participation
human-oversight-guardrails
r2-13-governance-policy
r2-16-approval-calibration
security-identity-governance
wt-human-policy
kind
company_review
map_edge
tech_features
tech_quote
tech_readme
tech_science_source
tech_section
needs_deepen
false
quality
ok
section
Evidence
Features map
GitHub map
How it works
Limits & failure modes
Links
Scientific notes
What it is
When to use / skip
Why it matters here
slug
headroom
source_id
earned-autonomy-contrast
headroom-github
langgraph-interrupt
surface
interface-review
technology
headroom

Corpus documents (33)

company_review · 2

  • Headroom · interface review
  • Headroom

map_edge · 9

  • headroom → access-vs-authority
  • headroom → autonomy-levels
  • headroom → emergency-control
  • headroom → exception-first-participation
  • headroom → human-oversight-guardrails
  • headroom → r2-13-governance-policy
  • headroom → r2-16-approval-calibration
  • headroom → security-identity-governance
  • … +1 more

tech_features · 1

  • Headroom · features

tech_quote · 7

  • Headroom · earned-autonomy-contrast
  • Headroom · earned-autonomy-contrast
  • Headroom · earned-autonomy-contrast
  • Headroom · headroom-github
  • Headroom · headroom-github
  • Headroom · langgraph-interrupt
  • Headroom · langgraph-interrupt

tech_readme · 1

  • Headroom

tech_science_source · 3

  • Headroom · earned-autonomy-contrast
  • Headroom · headroom-github
  • Headroom · langgraph-interrupt

tech_section · 10

  • Headroom · Evidence
  • Headroom · Features map
  • Headroom · GitHub map
  • Headroom · How it works
  • Headroom · Limits & failure modes
  • Headroom · Links
  • Headroom · Scientific notes
  • Headroom · What it is
  • … +2 more