AX Audit

Feature-level reviewer for apps where an agent acts for the user. One question: does it earn trust, and where does it break?

• IS: rules-based audit of agentic surfaces (chat, tool execution, config, dashboards) across architecture (rules-arch/) and trust (rules-ax/), ending in a ship-readiness verdict plus an AX Relationship Summary.
• IS NOT: traditional frontend UX (use ui-design Audit mode); developer-facing API, CLI, or type ergonomics (use dx-audit); agent instruction files (use agents-md); what the product should do before it exists (use product-design).

No agentic features in scope? Stop. AX rules against forms and lists are noise.

Contents

• Audit workflow
• Two rule layers
• Tiers and verdict
• AX Relationship Summary
• Reference files
• Gotchas
• Audit self-check
• Related skills

Audit workflow

AX Audit progress:
- [ ] Step 1: Scope, via the diff against the PR base merge-base (PR mode) or explicit path (full sweep)
- [ ] Step 2: Detect agentic features per references/feature-playbooks.md
- [ ] Step 3: Run each detected feature's playbook in order, plus the diff-wide checks (PR mode only)
- [ ] Step 4: For each check, load the rule file and follow its detection recipe
- [ ] Step 5: Tier each finding per references/ship-readiness.md (rule override table wins)
- [ ] Step 6: Render verdict + findings + AX Relationship Summary per references/output-format.md
- [ ] Step 7: Run the audit self-check and report its evidence counts

PR-mode scope is the diff plus the tool definitions and orchestrator it touches. Findings in untouched files belong in a full sweep, not this verdict. Playbook annotations are a scan copy; the rule file is authoritative. parity-orphan-ui-action runs on every PR-mode audit and never in a full sweep, where there is no diff for it to read.

Rule greps name the most common identifiers, not every framework's spelling. When a grep misses in code that plainly does the thing (a gate, a stream, a tool result), check references/framework-signals.md for the stack's name for it before recording unknown.

Two rule layers

Layer	Folder	Rules	Load when a playbook names
1: Architecture	rules-arch/	12	rules-arch/<category>-<slug>.md
2: Experience	rules-ax/	15	rules-ax/<category>-<slug>.md

Categories: arch = parity, granularity, context, comm; ax = trust, control, context, comm. Shared prefixes are different rules: rules-arch/comm-no-approval-gate.md (no gate on the execution path) is not rules-ax/control-no-approval-gate.md (gate exists, stakes are wrong).

Run Layer 1 comm/parity and Layer 2 control/trust first. They hold the blockers. Category map: rules-arch/_sections.md, rules-ax/_sections.md.

Priority	Layer	Category	Prefix	Rules
1	arch	Communication	comm-	3
2	arch	Parity	parity-	4
3	ax	Control	control-	4
4	ax	Trust	trust-	4
5	arch	Context	context-	3
6	ax	Communication	comm-	4
7	ax	Context	context-	3
8	arch	Granularity	granularity-	2

Tiers and verdict

Three tiers. Full trigger lists and the generic surface bump live in references/ship-readiness.md.

Precedence: the rule's own surface-override table > the generic bump > defaultTier. Apply at most one adjustment.

Verdict: ✅ READY (0 blockers, ≤3 sprint) · ⚠️ READY WITH FOLLOW-UP (0 blockers, ≥4 sprint) · ❌ NOT READY (≥1 blocker) · 🚫 INCOMPLETE (self-check failed).

Blockers outrank an incomplete audit. With ≥1 release-blocker and a failed self-check, report ❌ NOT READY and note the self-check failure beneath it: the blockers are established findings and stay actionable, while 🚫 reads as "nothing was learned" and sends the reader away. Reserve 🚫 for an audit with no blockers whose coverage you cannot vouch for.

AX Relationship Summary

Render after findings when any agentic feature was detected. Findings serve engineers; this serves designers and PMs. Four fields: evolution stage (behavior, not a label), trust signal (high/moderate/low plus one-line reason), key gap (one actionable sentence), trust question (one question only research can answer).

Reference files

File	Read when
references/feature-playbooks.md	Steps 2-3: detection heuristics, per-feature ordered checks, diff-wide checks
references/framework-signals.md	Step 4, when the code uses AI SDK, MCP, the Claude Agent SDK, or AG-UI: where the gate, the stream, the completion signal, and the structured result live in each, with the spec defaults the rules lean on
references/ship-readiness.md	Step 5: tier triggers, precedence, verdict logic
references/output-format.md	Step 6: findings JSON schema, summary schema, terminal rendering
references/agent-native-principles.md	A Layer 1 finding needs grounding the rule file does not carry
references/ax-evolution-curve.md	Writing the AX Relationship Summary: stage, action depth, costume vs intelligence
references/invisible-interface.md	Grounding for structured tool output, approval payload, access scope, unprompted action; also the arguments that stay in keyGap
references/evaluation-scenarios.md	When changing this skill. Never loads during a user audit
rules-arch/_sections.md	Layer 1 categories, default tiers, co-firing pairs
rules-ax/_sections.md	Layer 2 categories, default tiers, co-firing pairs

Gotchas

• Scope before rules. Running all 27 rules repo-wide on a 3-file PR buries a new release-blocker under pre-existing backlog noise; the verdict stops meaning "can this PR merge."
• The rule's override table is authoritative. comm-no-intent-handshake defaults to fix-this-sprint but its table says release-blocker on tool execution. Stacking the generic "+1 tier on tool execution" bump on an explicit override double-upgrades backlog findings into blockers.
• A stop button not wired to AbortController.abort() is a false affordance. control-no-escape-hatch still fails: verify the abort() call, not the button label, or the audit passes a UI that lies to users.
• A client stop() that only closes the stream leaves the executor running. useChat().stop() aborts the fetch. Unless the route passes req.signal into streamText({ abortSignal }) and tool execute reads it, the server finishes every remaining tool call after the user pressed Stop. Trace the signal to the loop, not to the button.
• Tool annotations are hints, not stakes. MCP tells clients to treat annotations from untrusted servers as untrusted; a gate that auto-approves on a third-party server's readOnlyHint: true has handed the gate to that server. comm-no-approval-gate fails it. The spec defaults (destructiveHint: true, readOnlyHint: false) are the fail-closed baseline.
• A framework approval flag is the gate's input, not the gate. AI SDK toolApproval: "user-approval" emits a tool-approval-request part and waits. A UI that never renders state === "approval-requested", or answers it with addToolApprovalResponse({ approved: true }) on arrival, has a gate in the type system and none for the user. Check the renderer and the response call, not the option.
• Absence checks need a recorded file list. "Find components lacking X" greps return nothing both when everything passes and when nothing was scanned. List candidate files first (rg -l <feature-pattern>), check each for the counter-pattern, and cite the file list as evidence.
• detection: observational rules cannot fail on grep evidence alone. granularity-static-api-mapping, trust-no-uncertainty-markers, control-over-conversational, and comm-no-generative-momentum need interaction-flow judgment; on static evidence alone, return unknown with a reason, not fail.
• Gates fail in three separate places. Absent from the path (comm-no-approval-gate), present but mismatched to the stakes (control-no-approval-gate), or correct and unreadable (control-thin-approval-payload). Report the first that holds and fix in that order.
• Interactive gates do not cover unattended runs. Cron, webhook, and queue entry points reach the same executor with nobody to prompt. comm-unrequested-action-no-consent audits that path; evidence names the entry point, not the executor.
• ax-audit-ignore:<slug> comments count as suppressed, not pass. Report the count in the verdict block; a suppression with no reason is itself a warn.
• Don't inflate tiers. comm-no-generative-momentum and granularity-static-api-mapping default to backlog. One finding promoted to release-blocker flips the whole PR to ❌ NOT READY, so promoting cosmetic ones trains the team to ignore the verdict entirely.
• Don't duplicate ui-design Audit mode findings. "Missing loading state" and "form clears on error" are its territory; duplicating them trains engineers to dismiss the whole AX report.
• A Personally Intelligent agent that only ever suggests has plateaued. Memory stage is not trust. Name the highest action rung in evolutionStage.behavior or the summary flatters a polite chatbot.

Audit self-check

Flag the audit INCOMPLETE if any of these hold, and include the counts as evidence (planned vs. run rules per playbook, unknown rate, suppressed count):

• Fewer rules ran than the playbooks planned
• More than 30% of rules returned unknown. Count only unknown here, never out-of-scope: a rule whose layer is absent from the scope you were given was answered correctly, and a narrow diff is the scope Step 1 asks for. Marking a correctly scoped audit INCOMPLETE buries its real blockers under a verdict that reads as "we learned nothing".
• Any fail/warn finding lacks file:line evidence or a fix snippet
• Every finding landed in the same tier (suspect blanket assignment)
• AX Relationship Summary is missing despite detected agentic features

Related skills

• ui-design Audit mode: traditional frontend UX around agentic surfaces; run both on agentic feature PRs
• dx-audit: same files, different reader. This skill asks whether an agent can operate and recover; dx-audit asks whether a human adopting the API, CLI, or types finds it ergonomic
• product-design: what the agentic feature should do, before this audit
• agents-md: CLAUDE.md / AGENTS.md instruction files

Maintenance only: evals/evals.json contains regression scenarios for changes to this skill; it does not load during a user task.