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description: CLI Reference API reference: Complete reference for the attune command-line interface.

CLI Reference

Complete reference for the attune command-line interface.


Quick Reference

# Workflows
attune workflow list                    # List available workflows
attune workflow info <name>             # Show workflow details
attune workflow run <name> [options]    # Execute a workflow

# Telemetry
attune telemetry show                   # Display usage summary
attune telemetry savings                # Show cost savings
attune telemetry export -o <file>       # Export to CSV/JSON

# Provider
attune provider show                    # Show current provider
attune provider set <name>              # Set provider (anthropic)

# Memory (Lessons Learned)
attune remember "lesson text"           # Save a lesson
attune forget <number-or-keyword>       # Remove a lesson
attune lessons                          # List all lessons

# Utilities
attune validate                         # Validate configuration
attune version                          # Show version

Workflow Commands

attune workflow list

List all available workflows registered in the framework.

attune workflow list

Output:

📋 Available Workflows

------------------------------------------------------------
  security-audit           Audit code for security vulnerabilities
  bug-predict              Predict potential bugs using patterns
  release-prep             Prepare release with changelog
  test-coverage            Generate tests for coverage gaps
------------------------------------------------------------

Total: 4 workflows

Run a workflow: attune workflow run <name>


attune workflow info <name>

Show detailed information about a specific workflow.

attune workflow info security-audit

Arguments:

Argument Required Description
name Yes Workflow name

attune workflow run <name>

Execute a workflow with optional parameters.

# Basic usage
attune workflow run security-audit

# With target path
attune workflow run security-audit --path ./src

# With JSON input
attune workflow run bug-predict --input '{"threshold": 0.8}'

# Output as JSON (for CI/CD)
attune workflow run security-audit --path ./src --json

Arguments:

Argument Required Description
name Yes Workflow name

Options:

Option Short Description
--path -p Target path for analysis
--input -i JSON input data
--target -t Target value (e.g., coverage percentage)
--depth Analysis depth: quick, standard, deep
--json -j Output result as JSON
--cheap Force every inherit-default subagent onto Haiku for this run (opus/sonnet-pinned subagents unaffected)

Examples:

# Security audit on src directory
attune workflow run security-audit --path ./src

# Bug prediction with custom threshold
attune workflow run bug-predict --input '{"path":"./src","threshold":0.7}'

# Test coverage targeting 80%
attune workflow run test-coverage --path ./src --target 80

# CI/CD friendly output
attune workflow run security-audit --path ./src --json > results.json

# Cheap-mode: route inherit-default subagents to Haiku
attune workflow run bug-predict --cheap

Cost knobs

--cheap is a single-flag shortcut for ATTUNE_AGENT_MODEL_DEFAULT=haiku. For finer-grained control, set per-keyword env vars listed in PROJECT_OVERVIEW.md → Per-Agent Model Override. Subagent names are matched against keywords (first match wins): security/vuln/architect → opus; quality/plan/research → sonnet; complexity/lint/coverage/dep/scanner/finder/detector → haiku; reviewer → inherit (override hook).

Spend gate

The first billable attune workflow run of a session surfaces an estimate and asks for an explicit go before any paid call. Once you confirm, a session spend window (~5h, aligned to Anthropic's rolling usage window) is established and later runs proceed silently until the window expires or a run would exceed it. A --no-llm run never reaches the gate.

The framing matches your billing meter: API users see a dollar band (≈ up to $X), subscription users see usage-headroom framing (no dollar figure).

Env var Effect
ATTUNE_SPEND_GATE=off Disable the gate entirely (always proceed).
ATTUNE_MAX_BUDGET_USD=0 Also disables the gate (the existing cap-disable; 0 = no cap).
ATTUNE_MAX_BUDGET_USD=<n> Sets the per-run estimate band / cap (positive float).
ATTUNE_SPEND_GATE_AUTHORIZED=1 Pre-authorize a non-interactive run (CI, the ops daemon) — required because a context that can't prompt blocks by default rather than spending silently.

In a non-interactive run (no TTY) with no pre-authorization, the gate blocks rather than spend silently, and prints the ATTUNE_SPEND_GATE_AUTHORIZED=1 hint. The ops dashboard and the security-scan CI workflow set this opt-in automatically.


Telemetry Commands

attune telemetry show

Display usage summary including API calls, tokens, and costs.

attune telemetry show
attune telemetry show --days 7

Options:

Option Short Default Description
--days -d 30 Number of days to summarize

Output:

📊 Telemetry Summary

------------------------------------------------------------
  Period:         Last 30 days
  Workflow runs:  45
  Total tokens:   1,234,567
  Total cost:     $12.34
------------------------------------------------------------


attune telemetry savings

Show cost savings from intelligent tier routing.

attune telemetry savings
attune telemetry savings --days 90

Options:

Option Short Default Description
--days -d 30 Number of days to analyze

Output:

💰 Cost Savings Report

------------------------------------------------------------
  Period:              Last 30 days
  Actual cost:         $12.34
  Premium-only cost:   $45.00 (estimated)
  Savings:             $32.66
  Savings percentage:  72.6%

  * Premium baseline assumes Claude Opus pricing (~$45/1M tokens)
------------------------------------------------------------


attune telemetry export

Export telemetry data to a file.

attune telemetry export -o telemetry.json
attune telemetry export -o telemetry.csv --format csv

Options:

Option Short Required Default Description
--output -o Yes - Output file path
--format -f No json Output format (json/csv)
--days -d No 30 Number of days

attune telemetry routing-stats

Show adaptive routing statistics — how the tier router chose between cheap, capable, and premium models across your workflows.

attune telemetry routing-stats
attune telemetry routing-stats --workflow security-audit
attune telemetry routing-stats --workflow code-review --stage scan --days 14

Options:

Option Short Default Description
--workflow -w all Filter by workflow name
--stage -s all Filter by stage name within a workflow
--days -d 7 Number of days to include

Output (per workflow):

📊 Adaptive Routing Statistics

  Workflow:      security-audit
  Period:        Last 7 days
  Total calls:   28
  Avg cost:      $0.0034
  Success rate:  96.4%

  Models used:   claude-haiku-4-5, claude-sonnet-4-5

  Per-Model Performance:
    claude-sonnet-4-5:
      Calls:         20   Success rate: 100.0%
      Avg cost:      $0.0045  Avg latency: 1420ms
    claude-haiku-4-5:
      Calls:         8    Success rate: 87.5%
      Avg cost:      $0.0008  Avg latency: 680ms


attune telemetry routing-check

Get tier upgrade recommendations based on recent routing performance. Tells you if a stage is consistently failing at a lower tier and should be promoted.

attune telemetry routing-check
attune telemetry routing-check --workflow code-review --days 30

Options:

Option Short Default Description
--workflow -w all Limit analysis to one workflow
--days -d 7 Number of days to analyze

attune telemetry models

Show model performance broken down by provider.

attune telemetry models
attune telemetry models --days 14

Options:

Option Short Default Description
--days -d 7 Number of days
--min-calls - 5 Minimum call count to include in report

attune telemetry agents

Show active agents and their current coordination status.

attune telemetry agents

Displays agent IDs, session type, access tier, capabilities, and last heartbeat time for all agents currently registered in the coordination layer.


attune telemetry signals

Show coordination signals for a specific agent — messages sent and received across the multi-agent coordination bus.

attune telemetry signals --agent <agent-id>

Options:

Option Short Required Description
--agent -a Yes Agent ID to inspect

Costs Commands

Track API spend and savings from intelligent tier routing.

attune costs

Show a cost report for the recent period.

attune costs
attune costs --days 30
attune costs --workflow security-audit
attune costs --json

Options:

Option Short Default Description
--days -d 7 Number of days
--workflow -w all Filter by workflow name
--json - false Output raw JSON

Output:

Cost Report — Last 7 days
--------------------------------------------------
  Requests:        142
  Actual cost:     $0.4821
  Baseline (Opus): $6.3900
  Saved:           $5.9079  (92.5%)


attune costs today

Show costs incurred today only.

attune costs today

attune costs export

Export cost data to a file.

attune costs export -o costs.json
attune costs export -o costs.csv --format csv --days 30

Options:

Option Short Required Default Description
--output -o Yes - Output file path
--format -f No json Output format (json or csv)
--days -d No 30 Days of history to include

attune costs reset

Clear all stored cost data. Requires explicit confirmation.

attune costs reset --confirm

Options:

Option Required Description
--confirm Yes Safety flag — must be passed to proceed

Provider Commands

attune provider show

Display current LLM provider configuration.

attune provider show

Output:

🔧 Provider Configuration

------------------------------------------------------------
  Mode:            SINGLE
  Primary provider: anthropic
  Cost optimization: ✅ Enabled

  Available providers:
    [✓] anthropic
------------------------------------------------------------


attune provider set <name>

Set the active LLM provider.

attune provider set anthropic

Arguments:

Argument Required Choices Description
name Yes anthropic Provider to use

Note: As of v5.0.0, Attune AI is Anthropic-only. Multi-provider support may return in future versions.


Memory Commands

attune remember <text>

Save a lesson learned for future workflow prompts.

# Save a project-local lesson
attune remember "Always run ruff before committing"

# Save a global lesson (applies to all projects)
attune remember --global "Prefer heapq.nlargest over sorted()[:N]"

Arguments:

Argument Required Description
text Yes Lesson text to save

Options:

Option Description
--global Save to global lessons (~/.attune/lessons.md)

Lessons are stored as markdown in .attune/lessons.md (project) or ~/.attune/lessons.md (global) and automatically injected into all workflow prompts. Token budget: 3,000 tokens max (oldest lessons dropped first when over budget).


attune forget <identifier>

Remove a lesson by line number or keyword.

# Remove by line number (from `attune lessons` output)
attune forget 3

# Remove by keyword match (first match removed)
attune forget "heapq"

Arguments:

Argument Required Description
identifier Yes Line number or keyword

attune lessons

List all current lessons with line numbers.

# Show all lessons (project + global)
attune lessons

# Show only global lessons
attune lessons --global

Options:

Option Description
--global Show only global lessons

Output:

Attune Lessons
==================================================
    1. [2026-02-23] Always run ruff before committing [project]
    2. [2026-02-20] Use _validate_file_path for writes [global]

2 lesson(s) total.
Remove with: attune forget <number> or attune forget <keyword>

attune memory capture <topic> <content>

Save a topic to personal cross-session memory. The content is polished by Claude before saving so it's clear and retrievable in future sessions.

attune memory capture "auth-pattern" "Always use _validate_file_path before writes"
attune memory capture "deploy-note" "Blue/green deploy requires 10-min warm-up" --project

Arguments:

Argument Required Description
topic Yes Slug identifier — letters, digits, hyphens, max 50 chars
content Yes Raw content to capture and polish

Options:

Option Short Description
--project - Save to .attune/memory/ (project-local) instead of global
--no-polish - Skip LLM polish step; save content verbatim

attune memory recall <topic>

Retrieve a saved memory topic.

attune memory recall auth-pattern
attune memory recall deploy-note --deep

Arguments:

Argument Required Description
topic Yes Topic slug to retrieve

Options:

Option Description
--deep Show full detail including related topics

attune memory topics

List all saved personal memory topics.

attune memory topics

attune memory forget-topic <topic>

Delete a saved memory topic.

attune memory forget-topic old-pattern

Utility Commands

attune doctor

Run a comprehensive environment health check — verifies Python version, API key, Redis connectivity, installed extras, and MCP server reachability.

attune doctor

Output:

🩺 Attune AI Environment Check

  ✅ Python 3.11.5 (≥ 3.10 required)
  ✅ ANTHROPIC_API_KEY set
  ✅ attune-ai 6.3.0 installed
  ✅ Redis reachable (localhost:6379)
  ⚠️  attune-rag not installed (pip install attune-ai)
  ✅ MCP server importable

2 warnings. Run `attune features` to see optional extras.


attune features

Show which optional feature groups are installed and which are available to install, with the pip command for each.

attune features

Output:

📦 Attune AI Features

  ✅ core          Always available
  ✅ redis         Core — redis + agent-memory-client ship with attune-ai
  ✅ rag           Core — attune-rag ships with attune-ai
  ✅ developer     attune-ai[developer] — Development tools
  ❌ author        attune-ai[author] — Template authoring (attune-author)

Install missing extras: pip install 'attune-ai[<name>]'


attune setup

Install the Attune slash commands to ~/.claude/commands/ so they are available in every Claude Code session without a project-level plugin.

attune setup

Copies all commands from the installed attune-ai package into ~/.claude/commands/. Safe to re-run — existing commands are overwritten with the latest version.


attune validate

Validate your configuration and environment.

attune validate

Checks:

  • Configuration file (attune.config.json/yml)
  • API keys (ANTHROPIC_API_KEY)
  • Workflow registration

Output:

🔍 Validating configuration...

  ✅ Config file: attune.config.yml
  ✅ Anthropic (Claude) API key set
  ✅ 12 workflows registered

------------------------------------------------------------

✅ Configuration is valid


attune version

Show version information.

attune version
attune version --verbose

Options:

Option Short Description
--verbose -v Show Python version and platform

Global Options

These options work with any command:

Option Short Description
--verbose -v Enable debug logging
--help -h Show help for command

Verification Configuration

Workflows support optional post-execution verification that runs real tools (pytest, ruff, mypy, etc.) to verify output. Configure via the verification: section in your workflow config.

Example Configuration

# In your workflow config (e.g. empathy.config.yml)
verification:
  enabled: true
  strategy: auto          # auto, run-tests, lint-check,
                          # type-check, build, custom-command,
                          # or none
  max_retries: 2          # Retry failed verification (default: 2)
  timeout_seconds: 300    # Per-attempt timeout (default: 300)
  fail_open: false        # If true, failed verification does
                          # not fail the workflow

  # Per-workflow overrides
  workflows:
    code-review:
      strategy: lint-check
    test-gen:
      strategy: run-tests
      max_retries: 3
    release-prep:
      strategy: build
      fail_open: true
    security-audit:
      strategy: custom-command
      command: "bandit -r src/ --severity-level medium"

Built-in Strategies

Strategy Command Default for
run-tests pytest tests/ -x --tb=short -q test-gen, refactor-plan
lint-check ruff check src/ --no-fix code-review, bug-predict, perf-audit, security-audit
type-check mypy src/ --ignore-missing-imports (manual)
build python -m build --no-isolation release-prep, secure-release
custom-command (user-provided) (manual)
none (skipped) doc-gen, research-synthesis

Auto Strategy

When strategy: auto is set (the default), the verification module looks up the workflow name in the defaults table above. If no default is mapped, verification is skipped.

Verification Result

After verification runs, results are attached to workflow_result.metadata["verification"]:

{
  "passed": true,
  "strategy": "run-tests",
  "command": "pytest tests/ -x --tb=short -q",
  "attempts": 1,
  "duration_ms": 4230,
  "exit_code": 0
}

If verification fails and fail_open is false (the default), the workflow is marked as failed with error_type: "verification".


Environment Variables

Variable Description
ANTHROPIC_API_KEY Anthropic API key (required)
ATTUNE_CONFIG Custom config file path
ATTUNE_LOG_LEVEL Logging level (DEBUG, INFO, WARNING)

Exit Codes

attune workflow run follows a four-code contract:

Code Meaning
0 Workflow ran and succeeded (also: interactive spend prompt declined)
1 Workflow ran and reported failure (WorkflowResult.success false)
2 Workflow raised an uncaught exception (traceback on stderr)
3 CLI-level stop — workflow not found, bad input JSON, bad path, no auth, or spend-gate block (the workflow never executed)

Other subcommands use 0 for success and 1 for error.


The framework includes additional CLI tools:

See All CLI Entry Points below for the full list of available CLIs.


Claude Code Integration

For interactive features, use Claude Code slash commands instead of CLI:

Command Purpose
/dev Developer tools (debug, commit, PR)
/testing Run tests, coverage, benchmarks
/docs Documentation generation
/release Release preparation
/help Navigation hub overview

These provide guided, conversational experiences built on top of the same framework.


All CLI Entry Points

Primary (Canonical)

Command Module Description
attune <command> attune.cli_minimal Automation-focused CLI (workflows, telemetry, provider, validate)
python -m attune.cli attune.cli Full-featured modular CLI (30+ commands)

Specialty CLIs

Invoked via python -m <module>:

Command Description
python -m attune.models Model registry, auth setup, cost estimation
python -m attune.test_generator AI-powered test generation and risk analysis
python -m attune.socratic Socratic question-driven workflow selection
python -m attune.telemetry Detailed telemetry and cost analysis
python -m attune.project_index Project indexing and code scanning

Deprecated

Entry Point Replacement Removal Target
attune.cli_unified attune (cli_minimal) v5.0.0