Maintain GOALS.yaml and GOALS.md fitness specifications. Use ao goals CLI for all operations.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiongoalsExecute the skills CLI command in your project's root directory to begin installation:
Fetches goals from boshu2/agentops and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate goals. Access via /goals in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Automate repetitive workflows and reduce manual effort
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Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
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Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
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Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Maintain GOALS.yaml and GOALS.md fitness specifications. Use
ao goalsCLI for all operations.
YOU MUST EXECUTE THIS WORKFLOW. Do not just describe it.
/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 | File | Version | Features |
|---|---|---|---|
| YAML | GOALS.yaml | 1-3 | Goals with checks, weights, pillars |
| Markdown | GOALS.md | 4 | Goals + mission + north/anti stars + directives |
When both files exist, GOALS.md takes precedence.
Parse the user's input:
| Input | Mode | CLI Command |
|---|---|---|
/goals, /goals measure, "goal status" |
measure | ao goals measure |
/goals init, "bootstrap goals" |
init | ao goals init |
/goals steer, "manage directives" |
steer | ao goals steer |
/goals add, "add goal" |
add | ao goals add |
/goals drift, "goal drift" |
drift | ao goals drift |
/goals history, "goal history" |
history | ao goals history |
/goals export, "export goals" |
export | ao goals export |
/goals meta, "meta goals" |
meta | ao goals meta |
/goals validate, "validate goals" |
validate | ao goals validate |
/goals prune, "prune goals", "clean goals" |
prune | ao goals prune |
/goals migrate, "migrate goals" |
migrate | ao goals migrate |
ao goals measure --json
Parse the JSON output. Extract per-goal pass/fail, overall fitness score.
If the goals file is GOALS.md format:
ao goals measure --directives
For each directive, assess whether recent work has addressed it:
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)
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.
After ao goals init creates the scaffold, enrich it with product-aware content that the CLI cannot auto-detect:
Review the generated north stars. If they are all feature-focused (e.g., "skills work across 4 runtimes"), nudge toward outcome-focused stars:
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.
Scan for proven failure patterns:
.agents/retro/ — extract failure themes from retrospectives.agents/council/ or council index — look for FAIL verdicts and their root causes.agents/learnings/ — look for learnings tagged as anti-patternsConvert the top 3 most common failure modes into anti-stars. Examples from real data:
If no .agents/ data exists, use the defaults from ao goals init.
The CLI generates engineering-flavored directives (test coverage, complexity, lint). After init, also suggest product/growth directives by asking:
steer: decreasesteer: increaseProduct directives sit alongside engineering ones in the same ## Directives section. See references/generation-heuristics.md for product directive patterns.
Check what product infrastructure exists and suggest appropriate gates:
| Infrastructure | Suggested Gate |
|---|---|
.agents/learnings/ exists |
flywheel-compounding — knowledge above escape velocity |
skills/quickstart/ exists |
quickstart-under-5min — onboarding time gate |
docs/comparisons/ exists |
competitive-freshness — comparison docs updated within 45 days |
PRODUCT.md exists |
product-gaps-tracked — Known Gaps section has entries |
ao flywheel status works |
flywheel-promotion-rate — learnings promoted above threshold |
Only suggest gates for infrastructure that actually exists. Don't create gates for aspirational features.
Run measure mode first to show current fitness and directive status.
Based on measurement:
Product-aware steering: Also check for product dimension gaps:
.agents/retro/ has new failure patterns not represented in anti-stars → suggest adding themUse CLI commands:
ao goals steer add "Title" --description="..." --steer=increase
ao goals steer remove 3
ao goals steer prioritize 2 1
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
| Flag | Default | Description |
|---|---|---|
--weight |
5 | Goal weight (1-10) |
--description |
— | Human-readable description |
--type |
— | Goal type (health, architecture, quality, meta) |
Example:
ao goals add go-coverage-floor "bash scripts/check-coverage.sh" --weight=3 --description="Go test coverage above 60%"
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.
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 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).
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.
ao goals validate --json
Reports: goal count, version, format, directive count, any structural errors or warnings.
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.
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.
User says: /goals
What happens:
ao goals measure --json to get gate resultsao goals measure --directives to get directive listResult: Dashboard showing gate pass rates and directive progress.
User says: /goals init
What happens:
ao goals init which prompts for mission, stars, directives, and auto-detects gatesResult: New GOALS.md ready for /evolve consumption.
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:
ao goals add with the provided argumentsResult: New goal added, measurable on next /goals run.
| Problem | Cause | Solution |
|---|---|---|
| "goals file already exists" | Init called on existing project | Use /goals to measure, or delete file to re-init |
| "directives require GOALS.md format" | Tried steer on YAML file | Run ao goals migrate --to-md first |
| No directives in measure output | GOALS.yaml doesn't support directives | Migrate to GOALS.md with ao goals migrate --to-md |
| Gates referencing deleted scripts | Scripts were renamed or removed | Run /goals prune to clean up |
| Drift shows no history | No prior snapshots saved | Run ao goals measure at least twice first |
| Export returns empty | No snapshot file exists | Run ao goals measure to create initial snapshot |
/evolve — consumes goals for fitness-scored improvement loopsreferences/goals-schema.md — schema definition for both formatsreferences/generation-heuristics.md — goal quality criteriaPrerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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Solid pick for teams standardizing on skills: goals is focused, and the summary matches what you get after install.
goals fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
goals reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for goals matched our evaluation — installs cleanly and behaves as described in the markdown.
goals is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: goals is the kind of skill you can hand to a new teammate without a long onboarding doc.
goals has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for goals matched our evaluation — installs cleanly and behaves as described in the markdown.
We added goals from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: goals is focused, and the summary matches what you get after install.
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