ritual-meta-human-in-loop

Human-in-Loop — Mid-Session Elicitation (v2)

Purpose

Define when and how to pull the user for a decision during an active build/debug session. The constraint: only interrupt when the decision would fork the trajectory into branches that are expensive to switch between, and only when the answer isn't discoverable by the agent itself.

The Fork Test (Revised)

Before asking the user anything mid-session:

1. Is there a fork? Does the next step have 2+ valid approaches?
2. Was this resolved by initial elicitation? Check whether any elicitation answer already determines this fork. If yes, use that answer — don't re-ask.
3. Is it a correctness fork or a preference fork?
   • Correctness: One branch is technically impossible or will fail. Always pull — regardless of budget.
   • Preference: Both branches work, the user just might prefer one. Respect the pull budget.
4. Can I resolve it myself? Search skills, check chain state, review existing code. If the answer is findable, find it.
5. Is the switch cost high? Would choosing wrong require rewriting >1 file or redeploying?

Pull the user if: (1) AND NOT (2) AND (preference AND budget remaining, OR correctness) AND NOT (4) AND (5).

Canonical Fork Points

Static forks known to Ritual dApp development:

Fork	Type	Branch A	Branch B	Switch Cost
Short-running vs long-running	Correctness	Inline receipt result	Callback to contract	Contract redesign
Direct call vs consumer contract	Preference	EOA → precompile	Contract wraps precompile	Architecture change
Owner secrets vs delegated	Preference	User encrypts per-request	ACL-based delegation	Encryption flow rewrite
Persistent memory vs one-shot agent	Correctness	Sovereign Agent (0x080C) or LLM-only (no 0x0820)	Persistent Agent (0x0820)	Completely different ABI
SSE streaming vs receipt polling	Preference	Real-time tokens via fetch()+SSE with auth headers	Poll spcCalls after settlement	Frontend architecture
Passkey vs wallet auth	Preference	TxPasskey (0x77), P-256	MetaMask, secp256k1	Tx type, address derivation

General fork detection heuristic for novel forks: "Am I about to write code that hard-codes assumption X, where the user might reasonably want Y, and switching X→Y after deployment requires more than local edits?" If yes, it's a fork.

How to Pull

Format

Present 2-3 options (never more) with a recommendation:

I've reached a design decision:

[One-sentence description of what forks]

A: [First option — one sentence, plain language]
B: [Second option — one sentence, plain language]

I'd go with [A/B] because [one concrete reason].

Should I proceed with that, or do you prefer the other?

Correctness Forks

For correctness forks, frame it as a constraint, not a choice:

Your design needs [X], but [constraint Y] prevents it.

Two ways to handle this:
A: [Workaround one]
B: [Workaround two — fundamentally different]

I'd recommend A because [reason]. Should I go with that?

Timeout

If the user doesn't respond within 2 turns, proceed with the recommendation. Note: "Went with [option] — let me know if you'd like to change direction."

Pull Budget

The budget is derived from the build plan, not a constant:

1. After elicitation, count the number of unresolved forks in the build plan.
2. Set the pull budget = number of unresolved forks.
3. Correctness forks don't count against the budget — they always fire.

After exhausting the budget, default to recommendations silently for preference forks. Log the decision for traceability.

Within-Session Learning

Track the user's decision pattern:

• If the user picked the simpler option 2+ times → bias future recommendations toward simplicity.
• If the user overrode the recommendation 2+ times → increase pull frequency (the agent's model is miscalibrated).
• If the user said "you decide" 2+ times → reduce pull frequency (the user is delegating).

This learning resets at session boundaries — don't carry preferences across sessions unless the user explicitly says to.

Relationship to Other Omega Skills

Skill	Relationship
skills/ritual-meta-elicitation/SKILL.md	Handles session-start. Human-in-loop handles mid-session. Check elicitation answers before pulling.
skills/ritual-meta-non-interactive-bias/SKILL.md	Says "search before asking." Human-in-loop is the exception for preference-based forks that search can't resolve.
skills/ritual-meta-circuit-breaker/SKILL.md	Fires when trajectory diverges. Human-in-loop prevents divergence by catching forks before they become problems.
skills/ritual-meta-orchestrator/SKILL.md	Defines the α/β interleave. Human-in-loop triggers during α when a fork is detected.