/goals — Fitness Goal Maintenance

Maintain GOALS.yaml and GOALS.md fitness specifications. Use ao goals CLI for all operations.

YOU MUST EXECUTE THIS WORKFLOW. Do not just describe it.

Quick Start

/goals                    # Measure fitness (default)
/goals init               # Bootstrap GOALS.md interactively
/goals steer              # Manage directives
/goals add                # Add a new goal
/goals drift              # Compare snapshots for regressions
/goals history            # Show measurement history
/goals export             # Export snapshot as JSON for CI
/goals meta               # Run meta-goals only
/goals validate           # Validate structure
/goals prune              # Remove stale gates
/goals migrate            # Migrate YAML to Markdown

Format Support

When both files exist, GOALS.md takes precedence.

Mode Selection

Parse the user's input:

Measure Mode (default) — Observe

Step 1: Run Measurement

ao goals measure --json

Parse the JSON output. Extract per-goal pass/fail, overall fitness score.

Step 2: Directive Gap Assessment (GOALS.md only)

If the goals file is GOALS.md format:

ao goals measure --directives

For each directive, assess whether recent work has addressed it:

• Check git log for commits mentioning the directive title
• Check beads/issues related to the directive topic
• Rate each directive: addressed / partially-addressed / gap

Step 3: Report

Present fitness dashboard:

Fitness: 5/7 passing (71%)

Gates:
  [PASS] build-passing (weight 8)
  [FAIL] test-passing (weight 7)
    └─ 3 test failures in pool_test.go

Directives:
  1. Expand Test Coverage — gap (no recent test additions)
  2. Reduce Complexity — partially-addressed (2 refactors this week)

Init Mode

ao goals init

Or with defaults:

ao goals init --non-interactive

Creates a new GOALS.md with mission, north/anti stars, first directive, and auto-detected gates. Error if file already exists.

Post-Init Enrichment

After ao goals init creates the scaffold, enrich it with product-aware content that the CLI cannot auto-detect:

Enrich North Stars with Outcomes

Review the generated north stars. If they are all feature-focused (e.g., "skills work across 4 runtimes"), nudge toward outcome-focused stars:

• Feature-focused (weaker): "Skills work across 4 runtimes"
• Outcome-focused (stronger): "A new user goes from install to first validated workflow in under 5 minutes"

Ask the user: "Your north stars describe features. What user outcome would tell you the product is actually working?" Add at least one outcome-focused star.

Enrich Anti-Stars from Failure Modes

Scan for proven failure patterns:

1. Check .agents/retro/ — extract failure themes from retrospectives
2. Check .agents/council/ or council index — look for FAIL verdicts and their root causes
3. Check .agents/learnings/ — look for learnings tagged as anti-patterns

Convert the top 3 most common failure modes into anti-stars. Examples from real data:

• "Product promises with no automated verification" (from council FAILs where claims had no gates)
• "Goals that measure code metrics instead of user outcomes" (from retros where passing gates didn't improve product)
• "Capture without compounding" (from flywheel analysis where knowledge was stored but never retrieved)

If no .agents/ data exists, use the defaults from ao goals init.

Add Product Directives

The CLI generates engineering-flavored directives (test coverage, complexity, lint). After init, also suggest product/growth directives by asking:

1. "What's your biggest product gap right now?" → directive with steer: decrease
2. "What user behavior do you want to increase?" → directive with steer: increase
3. "What metric would tell you the product is working?" → directive with measurable target

Product directives sit alongside engineering ones in the same ## Directives section. See references/generation-heuristics.md for product directive patterns.

Add Product Gates

Check what product infrastructure exists and suggest appropriate gates:

Only suggest gates for infrastructure that actually exists. Don't create gates for aspirational features.

Steer Mode — Orient/Decide

Step 1: Show Current State

Run measure mode first to show current fitness and directive status.

Step 2: Propose Adjustments

Based on measurement:

• If a directive is fully addressed → suggest removing or replacing
• If fitness is declining → suggest new gates
• If idle rate is high → suggest new directives

Product-aware steering: Also check for product dimension gaps:

• If all directives are engineering-flavored (test, lint, build, refactor) → suggest at least one product/growth directive
• If no directive cites a specific metric → flag: "Vague directives are a smell. Can any of these reference a specific number?"
• If .agents/retro/ has new failure patterns not represented in anti-stars → suggest adding them
• If PRODUCT.md has Known Gaps not covered by any directive → suggest a directive to close the gap

Step 3: Execute Changes

Use CLI commands:

ao goals steer add "Title" --description="..." --steer=increase
ao goals steer remove 3
ao goals steer prioritize 2 1

Add Mode

Add a single goal to the goals file. Format-aware — writes to GOALS.yaml or GOALS.md depending on which format is detected.

ao goals add <id> <check-command> --weight=5 --description="..." --type=health

Example:

ao goals add go-coverage-floor "bash scripts/check-coverage.sh" --weight=3 --description="Go test coverage above 60%"

Drift Mode

Compare the latest measurement snapshot against a previous one to detect regressions.

ao goals drift                    # Compare latest vs previous snapshot

Reports which goals improved, regressed, or stayed unchanged.

History Mode

Show measurement history over time for all goals or a specific goal.

ao goals history                        # All goals, all time
ao goals history --goal go-coverage     # Single goal
ao goals history --since 2026-02-01     # Since a specific date
ao goals history --goal go-coverage --since 2026-02-01  # Combined

Useful for spotting trends and identifying oscillating goals.

Export Mode

Export the latest fitness snapshot as JSON for CI consumption or external tooling.

ao goals export

Outputs the snapshot to stdout in the fitness snapshot schema (see references/goals-schema.md).

Meta Mode

Run only meta-goals (goals that validate the validation system itself). Useful for checking allowlist hygiene, skip-list freshness, and other self-referential checks.

ao goals meta --json

See references/goals-schema.md for the meta-goal pattern.

Validate Mode

ao goals validate --json

Reports: goal count, version, format, directive count, any structural errors or warnings.

Prune Mode

ao goals prune --dry-run    # List stale gates
ao goals prune              # Remove stale gates

Identifies gates whose check commands reference nonexistent paths. Removes them and re-renders the file.

Migrate Mode

Convert between goal file formats.

ao goals migrate --to-md      # Convert GOALS.yaml → GOALS.md
ao goals migrate               # Migrate GOALS.yaml to latest YAML version

The --to-md flag creates a GOALS.md with mission, north/anti stars sections, and converts existing goals into the Gates table format. The original YAML file is backed up.

Examples

Checking fitness and directive gaps

User says: /goals

What happens:

1. Runs ao goals measure --json to get gate results
2. If GOALS.md format, runs ao goals measure --directives to get directive list
3. Assesses each directive against recent work
4. Reports combined fitness + directive gap dashboard

Result: Dashboard showing gate pass rates and directive progress.

Bootstrapping goals for a new project

User says: /goals init

What happens:

1. Runs ao goals init which prompts for mission, stars, directives, and auto-detects gates
2. Creates GOALS.md in the project root

Result: New GOALS.md ready for /evolve consumption.

Adding a new goal after a post-mortem

User says: /goals add go-parser-fuzz "cd cli && go test -fuzz=. ./internal/goals/ -fuzztime=10s" --weight=3 --description="Markdown parser survives fuzz testing"

What happens:

1. Runs ao goals add with the provided arguments
2. Writes the new goal in the correct format (YAML or Markdown)

Result: New goal added, measurable on next /goals run.

Troubleshooting

See Also

• /evolve — consumes goals for fitness-scored improvement loops
• references/goals-schema.md — schema definition for both formats
• references/generation-heuristics.md — goal quality criteria

Reference Documents

• references/generation-heuristics.md
• references/goals-schema.md