Outcome Setup
SkillDatabases & dataSet up or repair one outcome-loop folder for improving a real-world outcome. Use when the user wants to define goal.md, run.md, analytics/instrumentation, levers, target repos/accounts, or the folder contract for an outcome loop.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Outcome Setup skill
What this skill tells your AI
The instructions your AI receives, as published by nimrobo/superdense in skills/outcome-setup/SKILL.md and read by ahel’s review.
Set up one outcome folder as the control plane for improving a real-world outcome. Superdense remains the durable store for sessions, artifacts, externalization targets, and reward snapshots.
Read references/outcome-loop.md before writing or repairing files.
Outcome Packs
If the user asks to set up an outcome pack, resolve the pack before scaffolding files:
- Use
superdense outcome-pack get <exact-name>when the user provides an exact pack name such asx-reach. - Use
superdense outcome-pack search <keyword>when the user provides a descriptive name or fuzzy intent such as "X reach" or "landing page". - Use
superdense outcome-pack listwhen the available pack names are unknown. - Treat
listandsearchresponses as JSON. Use the returnednamefield as the exact name forget. - Treat
getas the source markdown for the pack's startinggoal.md,run.md, andgate.mdshape. - Adapt the fetched pack to the user's actual folder, target surfaces, analytics, guardrails, and constraints. Do not copy it blindly when local context contradicts it.
Workflow
- Locate or choose the outcome folder. One folder manages one outcome. It may sit above target repos/accounts.
- Inspect existing files and target surfaces before asking questions. Discover target repo conventions, analytics libraries, env patterns, and existing events from files and docs where possible.
- Ask the human only for non-discoverable intent or external access:
- north-star outcome and audience,
- guardrails and constraints,
- target surfaces such as repos, accounts, pages, campaigns, or dashboards,
- acceptable analytics access and any required human setup.
- Create or repair only the small fixed core:
goal.mdrun.mdgate.mdruns/
- Put the scaffold under git. If the outcome folder is already inside a parent git work tree, commit the new files there. Otherwise run
git initin the outcome folder. Then stage and commit the scaffold, for examplegit add goal.md run.md gate.md runs/ && git commit -m "outcome: scaffold <outcome-name>". - Do not create
metrics.md,hypotheses.md, orexperiments.md. Durable measurement results belong in Superdense reward snapshots; structured hypotheses and experiment verdicts belong in Superdense throughsuperdense hypothesis ...andsuperdense experiment .... - In
run.md, scaffold the lever portfolio fields fromreferences/outcome-loop.md: lever status, pull count, latest reward summary, uncertainty, last pulled, and Pareto-best dimension or guardrail. Also scaffold the Selection Policy with target explore ratio, explore triggers, exploit triggers, tie-break, and keep rule. - Put measurement definitions, diagnostics, event names, source systems, and instrumentation checklist in
run.md. - Define
gate.mdas reusable completion policy, not a per-run checklist. Include the standard sections fromreferences/outcome-loop.md:# Gate,## Completion Rules,## Required Checks,## Warning Checks, optional## Gate Phases,## Deterministic Checks, and## Failure Policy. It may be operationally empty when no checks are known yet; mark lists asnone configuredinstead of inventing fake checks. - Add local deterministic check scripts only when this outcome needs them. Keep them inside the outcome folder, reference them from
gate.md, and do not add bundled or generic script templates. - If analytics/instrumentation is missing and the target repo is available, implement the smallest viable instrumentation in that target repo after inspecting local conventions. Never commit private credentials. Treat public client tokens according to target repo conventions.
- If external account setup is required, pause with a concrete checklist for the human. Continue once the human provides access or confirms setup.
File Responsibilities
goal.mdis protected. It defines the outcome boundary, audience, north-star metric, guardrails, target surfaces, and human-owned constraints.run.mdis mutable. It defines the current lever portfolio, actions, diagnostic measurements, analytics/instrumentation checklist, Superdense reward preflight, Selection Policy, action selection rules, and run template.gate.mdis reusable completion policy. It defines required checks, warning checks, optional pre/post phases, deterministic checks when needed, and the failure policy for every run.runs/starts empty unless the user is repairing an existing loop.
Version Control
Initialize git only when the outcome folder is not already inside a git work tree. If a parent repo tracks the folder, avoid nesting a repository and commit goal.md, run.md, gate.md, and runs/ in the parent repo instead. Never commit private credentials; use .gitignore for local secrets, drafts, exports, or account-specific files that should stay untracked.
Dry Run
If the user asks for a dry run, show the proposed goal.md, run.md, and gate.md contents plus the git commands that would run, without writing files, running git, or changing target repos.
Signals
- GitHub stars
- 92
- Forks
- 12
- Last commit
- Jul 2026
Advanced
- Item type
- skill
- Key
outcome-setup- Source
- github.com/nimrobo/superdense