stress-regulation

name	stress-regulation
description	Produce a bounded StressProposal for today by consuming the runtime-computed `classified_state` + `policy_result` and applying judgment-only steps — action matrix, rationale prose, vendor cross-check. The runtime already did every band, every score, and every R-rule; this skill does not re-derive them.
allowed-tools	Read, Bash(hai state snapshot *), Bash(hai state read *), Bash(hai propose *), Bash(hai intent list *), Bash(hai target list *)
disable-model-invocation	false

Stress Regulation

All arithmetic happens in code. Your job is: read the bundle, honour the policy result, pick an action, write the rationale, persist.

Load the bundle

hai state snapshot --as-of <today> --user-id <u> --evidence-json <hai clean output>

Under snapshot.stress you receive these blocks:

• today — today's accepted_stress_state_daily row (garmin_all_day_stress, manual_stress_score, body_battery_end_of_day, stress_event_count, stress_tags_json), or null.
• history — recent days of stress rows for context.
• signals — the runtime-derived dict the classifier consumed: garmin_all_day_stress, manual_stress_score, body_battery_end_of_day, body_battery_prev_day, stress_history_garmin_last_7. Context only; never re-derive.
• classified_state — garmin_stress_band, manual_stress_band, body_battery_trend_band, coverage_band, stress_state, stress_score, body_battery_delta, uncertainty. Source of truth.
• policy_result — policy_decisions[], forced_action, forced_action_detail, capped_confidence, and (v0.2.0 W-PROV-2) optional evidence_locators[]. The runtime always emits a row-level locator citing today's accepted_stress_state_daily; an R-sustained-very-high-stress firing additionally cites garmin_all_day_stress per consecutive day in the trailing run. Source of truth.
• missingness — per state_model_v1.md §5.

Protocol

1. If the policy forced an action, use it

If policy_result.forced_action is set, action is that value and action_detail is policy_result.forced_action_detail. Confidence: low for defer_decision_insufficient_signal, else moderate. Skip the action matrix; jump to rationale.

Note: when R-sustained-very-high-stress fires, it forces escalate_for_user_review and the corresponding policy_decisions[] entry carries an escalate tier. Copy the decision verbatim — severity is already recorded there.

2. Otherwise, pick from the action matrix

Keyed on classified_state.stress_state:

state	action + action_detail
calm	maintain_routine
manageable	maintain_routine with {"caveat": "minor_variation"} when any band is not favourable
elevated	add_low_intensity_recovery with {"reason_token": "<primary_driver_band>"} — choose the band doing the most work (garmin_stress_band=high → garmin_stress_band; manual_stress_band=high → manual_stress_band; body_battery_trend_band=declining → body_battery_trend_band)
overloaded	schedule_decompression_time with {"reason_token": "<primary_driver_band>"} — same driver-band selection

3. Confidence

Default from classified_state.coverage_band: full → high, partial → moderate, sparse → moderate, insufficient → low. If policy_result.capped_confidence is set, it lowers the default but never raises it. The vendor cross-check below may lower further.

4. Vendor cross-check

The snapshot carries Garmin's own stress signals under stress.today:

• garmin_all_day_stress vs classified_state.garmin_stress_band — informational; the classifier already turned the score into a band. If the user's manual_stress_score band lands in a meaningfully different band than Garmin (e.g. manual very_high but Garmin moderate), cap confidence at moderate and add agent_vendor_stress_disagreement to uncertainty.
• body_battery_delta — informational in rationale; never action-bearing on its own.

5. Rationale (5–8 lines)

One line per band that informed the decision. Name the band; do not re-derive it.

Examples: garmin_stress=<band>, manual_stress=<band>, body_battery_trend=<band>, stress_state=<state>, sustained_very_high_stress (if R-sustained fired), agent_vendor_stress_disagreement (if applicable).

6. Uncertainty

Start with classified_state.uncertainty (already sorted + deduped). Append any tokens you added (e.g. *_unavailable_at_source derived from the snapshot's missingness token, vendor-disagreement tokens). Re-sort alphabetically; deduplicate.

7. Follow-up

Stress emits a StressProposal, not a recommendation, so it has no follow_up field. Synthesis assigns review semantics per finalised plan. Skip this step.

On defer_decision_insufficient_signal, synthesis uses the stress-domain template "How were your stress levels yesterday?" (owned by core.narration.templates.DEFER_REVIEW_QUESTION_TEMPLATES).

Output

Emit a StressProposal JSON and call hai propose --domain stress --proposal-json <path>. The propose tool validates the shape and appends to proposal_log; it is your determinism check.

proposal_id = prop_<for_date>_<user_id>_stress_01 (idempotent on (for_date, user_id, domain); re-running on the same day does not produce a new row).

Copy policy_result.policy_decisions into the output's policy_decisions verbatim — the runtime decided them; you do not re-edit or add new ones. v0.2.0 W-PROV-2: if policy_result.evidence_locators is present, copy that list verbatim into the proposal's evidence_locators field — do NOT derive locators yourself; the runtime computed them. If the field is absent, omit evidence_locators from the proposal.

Invariants

• You never compute a band, a score, or a ratio. classified_state is the source of truth.
• You never evaluate an R-rule (require_min_coverage, no_high_confidence_on_sparse_signal, sustained_very_high_stress_escalation). policy_result is the source of truth; you honour forced_action and capped_confidence.
• You never apply X-rule mutations. Synthesis owns all cross-domain reasoning; this skill emits one domain's bounded proposal.
• You never emit an action outside the v1 enum (maintain_routine, add_low_intensity_recovery, schedule_decompression_time, escalate_for_user_review, defer_decision_insufficient_signal). hai propose enforces this.
• You never fabricate values for missing evidence; missing stays missing.
• If a decision isn't reasoned in rationale[] or policy_decisions[], it didn't happen.