awaf 0.1.0

Score AI agent architectures against the AWAF open specification

awaf-cli

The reference implementation of the AWAF open specification. Catch agent architecture regressions before they ship.

Runs in CI on every PR that touches agent code. Scores across 10 architectural pillars defined by the AWAF open specification. Fails the build when something regresses.

No dashboards that need a legend. No compliance jargon. One number per pillar, one finding per issue, one fix per finding.

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Install

pip install awaf

Requires Python 3.11+. Bring your own model and API key.

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Provider Support

awaf-cli is model-agnostic. Use any supported LLM provider — no vendor lock-in.

Provider	Models	Key Env Var
anthropic	claude-opus-4-5, claude-sonnet-4-5, claude-haiku-4-5	ANTHROPIC_API_KEY
openai	gpt-4o, gpt-4o-mini, o3, o4-mini	OPENAI_API_KEY
azure	Any Azure OpenAI deployment	AZURE_OPENAI_API_KEY
google	gemini-2.0-flash, gemini-1.5-pro	GOOGLE_API_KEY
litellm	Any LiteLLM-compatible model	Provider-specific

Default provider: anthropic with claude-opus-4-5. Scores are calibrated on Claude; other providers may yield slight variance.

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Quickstart

# Default: Anthropic
export ANTHROPIC_API_KEY=sk-ant-...
awaf run

# OpenAI
export OPENAI_API_KEY=sk-...
awaf run --provider openai --model gpt-4o

# Azure / GitHub Copilot
export AZURE_OPENAI_API_KEY=...
awaf run --provider azure --model gpt-4o --azure-endpoint https://your-resource.openai.azure.com --azure-deployment gpt-4o

# LiteLLM (Bedrock, Groq, Ollama, etc.)
awaf run --provider litellm --model bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0

AWAF Assessment: my-agent
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

  Overall Score    78  Near Ready
  Provider         openai / gpt-4o

  TIER 0: FOUNDATION
  Foundation        85  verified

  TIER 1: CLOUD WAF ADAPTED
  Op. Excellence    74  verified
  Security          82  verified
  Reliability       71  verified
  Performance       80  verified
  Cost Optim.       65  partial
  Sustainability    79  verified

  TIER 2: AGENT-NATIVE  (1.5x weight)
  Reasoning Integ.  71  partial
  Controllability   78  verified
  Context Integrity 80  verified

  FILES ANALYZED     12 files
  FILES NOT SCANNED  infra/iam.yaml  Cost score confidence: partial

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

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Per-Project Config

# awaf.toml
[project]
name = "my-agent"

[provider]
name = "openai"              # anthropic | openai | azure | google | litellm
model = "gpt-4o"
api_key_env = "OPENAI_API_KEY"   # defaults to provider standard env var

# Azure / Copilot specific
# name = "azure"
# model = "gpt-4o"
# api_key_env = "AZURE_OPENAI_API_KEY"
# azure_endpoint = "https://your-resource.openai.azure.com"
# azure_deployment = "gpt-4o"
# azure_api_version = "2025-01-01-preview"

# LiteLLM — any model string LiteLLM supports
# name = "litellm"
# model = "bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0"

[thresholds]
overall_fail = 60
tier2_fail = 50
regression_limit = 10
warn_only = false

[files]
agent_patterns = ["agents/**/*.py", "tools/**/*.py", "pipelines/**"]
exclude = ["tests/**", "docs/**"]

[reporting]
post_pr_comment = true
terminal_format = "compact"    # compact | full | json

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CI Integration

GitHub Actions

name: AWAF Assessment
on:
  pull_request:
    paths:
      - 'agents/**'
      - 'tools/**'
      - 'pipelines/**'

jobs:
  awaf:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: YogirajA/awaf-action@v1
        with:
          # Use whichever provider key you have
          anthropic-api-key: ${{ secrets.ANTHROPIC_API_KEY }}
          # openai-api-key: ${{ secrets.OPENAI_API_KEY }}
          # azure-openai-api-key: ${{ secrets.AZURE_OPENAI_API_KEY }}
          provider: anthropic           # anthropic | openai | azure | google | litellm
          model: claude-opus-4-5        # optional, uses provider default if omitted
          project-name: my-agent
          fail-threshold: 60
          tier2-fail-threshold: 50
          score-regression-limit: 10
          post-pr-comment: true

AWAF only runs when agent files change. Unrelated commits are skipped (exit 3).

GitLab CI

include:
  - remote: 'https://raw.githubusercontent.com/YogirajA/awaf-cli/main/integrations/gitlab/awaf-gitlab-ci.yml'

awaf:
  variables:
    ANTHROPIC_API_KEY: $ANTHROPIC_API_KEY
    AWAF_PROVIDER: anthropic
    AWAF_PROJECT_NAME: my-agent
    AWAF_FAIL_THRESHOLD: "60"

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Exit Codes

Code	Meaning
0	Passed all thresholds
1	Score below threshold or regression exceeded
2	Assessment failed (API error, ingest error)
3	No agent files changed, skipped

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CLI Reference

awaf run                                         # assess current directory
awaf run --paths agents/ tools/                  # specific paths
awaf run --ci                                    # CI mode with git context
awaf run --pillar controllability                # single pillar only
awaf run --provider openai --model gpt-4o        # override provider
awaf run --provider litellm --model ollama/llama3 # local model via LiteLLM
awaf history                                     # score history for current project
awaf compare <id1> <id2>                         # diff two assessments
awaf report --format json                        # JSON output for CI artifact upload
awaf report --coverage                           # show files analyzed and skipped
awaf providers                                   # list configured providers and status

No color codes when stdout is not a TTY. No spinners in CI mode.

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What Gets Scored

awaf-cli implements AWAF v1.0 across 10 pillars in 3 tiers. Full pillar definitions and scoring questions are in the specification repo.

Tier 0: Foundation. Can this agent run independently?

Tier 1: Cloud WAF Adapted (1.0x weight). Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, Sustainability

Tier 2: Agent-Native (1.5x weight). Reasoning Integrity, Controllability, Context Integrity

The agent-native pillars are what make AWAF distinct. Cloud infrastructure has no equivalent for them; they exist because agents are not servers. See aradhye.com for the original thinking behind this.

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What It Analyzes

awaf-cli reads what is in your repository: Python, TypeScript, Go, YAML, JSON, TOML, Markdown, and PDF files.

It can verify: trust tier enforcement in code, kill switch and cancel implementations, loop detection and budget guards, eval framework presence, sanitization at input boundaries, slice boundary documentation.

It cannot verify (flagged as partial confidence): cloud resource configs not in the repo, whether SLOs are being met in production, runtime hallucination rates, whether circuit breakers are actually firing.

When something cannot be verified, the output says so explicitly. Partial confidence with clear coverage gaps is more useful than a confident score built on assumptions.

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Score History

Every assessment is stored locally in awaf.db. Score history is tracked per project, per branch, per commit, and per provider/model.

awaf history

my-agent  last 5 assessments
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
  2026-02-27  a3f9c12  PR #47   72  -6   openai/gpt-4o       Controllability regression
  2026-02-24  8bc1a33  main     78  +3   anthropic/claude-opus-4-5  Context Integrity improved
  2026-02-21  4de92f1  main     75  +0   anthropic/claude-opus-4-5
  2026-02-18  2ab77c4  main     75  +8   openai/gpt-4o       Security and Reliability up
  2026-02-12  9ff3e21  main     67  —    anthropic/claude-opus-4-5

Six months of CI runs become your architectural changelog.

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How It Works

awaf-cli sends your architecture artifacts to the LLM provider of your choice. Each of the 10 AWAF pillars is evaluated by a separate model call running concurrently. Results are written to a local SQLite database. No central coordinator. No shared state between pillar evaluations.

Artifacts → Ingestor → Event Bus → [10 Pillar Agents concurrently] → SQLite → Terminal
                                          ↑
                              Provider Abstraction Layer
                         (Anthropic | OpenAI | Azure | Google | LiteLLM)

The tool is built to be AWAF-compliant itself: choreography over orchestration, vertical slice per pillar, blast radius bounded. See ARCHITECTURE.md.

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Environment Variables

# Provider selection (can also be set in awaf.toml)
AWAF_PROVIDER=anthropic          # anthropic | openai | azure | google | litellm
AWAF_MODEL=claude-opus-4-5       # optional model override

# API keys — use whichever provider you're running
ANTHROPIC_API_KEY=sk-ant-...
OPENAI_API_KEY=sk-...
AZURE_OPENAI_API_KEY=...
AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com
AZURE_OPENAI_DEPLOYMENT=gpt-4o
GOOGLE_API_KEY=...

# Session controls
AWAF_DB_URL=sqlite:///./awaf.db
AWAF_MAX_ARTIFACTS_TOKENS=40000
AWAF_SESSION_BUDGET_USD=1.00     # approximate; pricing varies by provider
AWAF_LOG_LEVEL=INFO

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Deployment Modes

Mode	Setup	Data	Right For
Local	pip install awaf + API key	awaf.db on your machine	Solo developers, OSS projects
Cloud	API key + AWAF_MODE=cloud	awaf.dev (coming)	Teams, dashboards, benchmarks
On-Prem	Docker Compose / Helm	Your PostgreSQL	Enterprise, regulated industries

The local mode is fully functional with no account required. Cloud and on-prem add team dashboards, cross-project score history, and industry benchmarks. On-prem: no artifacts leave your network. All model API calls use your own API key. No telemetry unless opted in.

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Score Badge

[![AWAF Score](https://img.shields.io/badge/AWAF%20Score-78%20Near%20Ready-2563EB?style=flat-square)](https://github.com/YogirajA/AWAF)

Live badge (cloud mode):

[![AWAF Score](https://awaf.dev/badge/your-project)](https://awaf.dev/your-project)

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Contributing

Bug reports, feature requests, and PRs welcome. Provider adapter contributions especially welcome — see PROVIDER_SPEC.md for the interface contract.

For changes to the AWAF specification itself (pillar definitions, scoring questions, methodology), open an issue in the AWAF specification repo. This repo is for the implementation.

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License

Apache 2.0. See LICENSE.

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Related

• YogirajA/AWAF: The AWAF open specification
• PROVIDER_SPEC.md: Provider abstraction layer spec — build your own adapter
• Are We Building AI Agents Like We Built Microservices?: The post that introduced AWAF