Aep Calibrate

Calibrate

Human alignment checkpoint. Agents build to spec, but specs are lossy compressions of human intent. This skill pauses execution, lets the human inspect what was built, and captures what "right" actually means in a format agents can consume.

Where this fits:

/aep-reflect (identified alignment gap)
  → /aep-calibrate           (Phase 1: generate dimension-specific brief)
  → human explores       (method varies by type — external tools, conversation, code review)
  → /aep-calibrate capture   (Phase 2: capture decisions into artifact)
  → /aep-dispatch            (stories dispatched with calibration context)

Session: Main, interactive with user Input: Calibration type + product definition from product/index.yaml (split mode) or product-context.yaml (v1 mode) + operational state from product-context.yaml Output: Calibration artifact (standalone or inline) + updated calibration.history

Type Detection

Check how the skill was invoked to determine the calibration dimension:

Path A — Explicit: User says /aep-calibrate visual-design or /aep-calibrate api-surface. Type is given directly.

Path B — Routed from /aep-reflect: Reflection classified an observation as a calibration need with a specific dimension. The dimension and observation text are passed as context.

Path C — Ambient: User says /aep-calibrate with no type. Determine the type:

1. Check calibration.plan in product-context.yaml (operational file, both modes) — which dimension is next for the current layer?
2. Check stories with calibration_type set in the current .5 layer.
3. If neither applies, ask the user: "What feels off? (visual design / UX flow / API surface / data model / scope direction / copy tone / performance quality)"

Postcondition: one of the 7 dimensions is selected.

File Resolution

ls product/index.yaml 2>/dev/null && echo "SPLIT MODE" || echo "V1 MODE"
cat product-context.yaml

Mode semantics are canonical in references/file-resolution.md. Read the product definition (quality_dimensions, layers, activities, constraints, success_criteria, failure_model) from product/index.yaml in split mode or product-context.yaml in v1 mode; read operational state (calibration.plan, calibration.history, stories, architecture) always from product-context.yaml. Which file each type writes to is in references/calibration-types.md (Write Targets).

Mode Detection

After type is determined, check for existing calibration:

• Establishment mode: no prior entry in calibration.history for this dimension → full brief, create artifact from scratch.
• Extension mode: prior entry exists → delta brief covering only NEW patterns/decisions not in the existing calibration.

Calibration Types

Every dimension is either heavy or light (the split is canonical in /aep-map references/alignment-layers.md) — this drives the Phase 1 hand-off:

• Heavy: external exploration with tools outside the agent workflow, a standalone calibration/<type>.yaml artifact, and (usually) .5 alignment-layer stories. Phase 1 stops and hands off.
• Light: conversational Q&A that updates the product context in place. Phase 1 flows straight into Phase 2.

Per-dimension brief templates, exploration methods, scan targets, and write targets are in references/calibration-types.md — load it when picking a dimension or scanning current state. For ux-flow / visual-design, running /aep-design-lens first seeds the brief with a theory-grounded, severity-scored health-check (evidence) that calibrate turns into the human's decision.

Phase 1: Generate Brief

Step 1: Read Product Context

cat product-context.yaml

Extract:

• opportunity.bet + product.problem → product identity
• product.persona.description + product.persona.jtbd → target user
• opportunity.why_now → urgency/positioning
• stories where layer matches the active layer → scope of what was built or will be built
• product.constraints.required_stack + preferred_stack → technical constraints
• calibration.history → prior calibration decisions for this dimension (extension mode)

Step 2: Scan Current State

Inspect the current implementation against the scan targets for this type (table in references/calibration-types.md → Scan Targets) — e.g. globals.css/components//routes/ for visual-design, architecture.interfaces and handler files for api-surface.

Step 3: Generate Brief

Use the type-specific template from references/briefs/<type>.md.

• Establishment mode: generate the full brief template with all sections.
• Extension mode: read the existing calibration artifact or product-context sections, then generate a focused brief covering only what's NEW in the current layer: "Here's your current calibrated system. These new [pages/endpoints/entities/etc.] need decisions not yet covered: [list]."

Write the brief to docs/calibration-brief.md and print the full content to the terminal.

Postcondition: docs/calibration-brief.md exists and its content was printed.

Step 4: Hand Off

Heavy calibrations (visual-design, ux-flow, copy-tone): print exploration instructions and stop — the human explores externally, out of the agent's hands.

Calibration brief written to: docs/calibration-brief.md

Next steps (you do these):

  1. [Type-specific exploration instructions]
  2. Explore variations, then pick a direction.
  3. Save reference files to docs/design-references/ (if applicable)
  4. When ready, come back and run:
     /aep-calibrate capture

For visual-design, point the human to references/vibe-design-tools.md for tool guidance.

Light calibrations (api-surface, data-model, scope-direction, performance-quality): present the brief and proceed directly to Phase 2 — the brief frames the conversation, no external exploration needed.

Phase 2: Capture Decisions (/aep-calibrate capture)

Step 1: Interactive Q&A

Ask the structured questions from references/capture/<type>.md, one at a time. (Heavy examples: chosen direction, palette, journey decisions, voice. Light examples: naming decisions, entity/field names, scope-gap assessment, latency thresholds.)

Postcondition: every question in references/capture/<type>.md is answered.

Step 2: Produce Artifact

Heavy calibrations:

• Establishment mode: create calibration/<type>.yaml from scratch using the schema at references/schemas/<type>-schema.yaml, filling all sections from the Q&A answers.
• Extension mode: read the existing calibration/<type>.yaml, add entries for newly covered patterns, and update calibrated_at / calibrated_from_layer — extend existing values, do not replace them.

For visual-design specifically, also update globals.css with the captured palette: convert values to oklch and write them as CSS custom properties under :root and .dark. Establishment replaces the full palette; extension adds only new custom properties.

Light calibrations: update the relevant section(s) in the file resolved for this type (see references/calibration-types.md → Write Targets) — architecture.interfaces, architecture.domain_model, product.goals/mvp_boundary/layers, or product.success_criteria/failure_model.

Postcondition: the chosen decision is recorded in existing schema fields — for heavy, calibration/<type>.yaml exists with the chosen direction in direction.name/direction.description and calibrated_at set; for light, the target section reflects the decisions.

Step 3: Update Calibration History

Append one entry to calibration.history and one to changelog in product-context.yaml, per the product-context schema:

• calibration.history entry — dimension, calibrated_at, calibrated_from_layer, mode (establishment|extension), artifact_path (null for light calibrations), sections_updated, summary.
• changelog entry — date, type: calibration, author: human, summary, sections_changed.

Step 4: Commit

Validate YAML before committing (see references/yaml-guardrails.md for common fixes):

npx js-yaml product-context.yaml > /dev/null && echo "YAML OK"

Fix any error before committing. Then commit and push to $BASE (resolve $BASE per /aep-git-ref "Resolving $BASE"):

git pull --ff-only origin "$BASE"
git add calibration/ product-context.yaml product/
git commit -m "feat: calibrate <dimension> — <brief summary>"
git push origin "$BASE"

Postcondition: npx js-yaml printed YAML OK and git push exited 0.