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Ax Audit

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mblode
ax-audit

Audits agentic products for tool parity, authority, approval payloads, recovery, and trust using 27 rules and a ship verdict. Use when asked for an "AX audit", to review an agent approval flow, or whether an agent can operate the product. For human-facing API ergonomics use dx-audit; for ordinary UI use ui-design.

Overview

Publishermblode
Repositoryagent-skills
Skill nameax-audit
Stars
118
Forks
11
Bundled files
40
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 40 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mblode on GitHub. Read the source before you install it.

Installation

Install the Ax Audit AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mblode/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/skills/ax-audit .claude/skills/ax-audit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ax Audit in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ax Audit on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ax Audit is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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); public site or docs agent scores (use agent-ready); 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

text
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

LayerFolderRulesLoad when a playbook names
1: Architecturerules-arch/12rules-arch/<category>-<slug>.md
2: Experiencerules-ax/15rules-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.

PriorityLayerCategoryPrefixRules
1archCommunicationcomm-3
2archParityparity-4
3axControlcontrol-4
4axTrusttrust-4
5archContextcontext-3
6axCommunicationcomm-4
7axContextcontext-3
8archGranularitygranularity-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

FileRead when
references/feature-playbooks.mdSteps 2-3: detection heuristics, per-feature ordered checks, diff-wide checks
references/framework-signals.mdStep 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.mdStep 5: tier triggers, precedence, verdict logic
references/output-format.mdStep 6: findings JSON schema, summary schema, terminal rendering
references/agent-native-principles.mdA Layer 1 finding needs grounding the rule file does not carry
references/ax-evolution-curve.mdWriting the AX Relationship Summary: stage, action depth, costume vs intelligence
references/invisible-interface.mdGrounding for structured tool output, approval payload, access scope, unprompted action; also the arguments that stay in keyGap
references/evaluation-scenarios.mdWhen changing this skill. Never loads during a user audit
rules-arch/_sections.mdLayer 1 categories, default tiers, co-firing pairs
rules-ax/_sections.mdLayer 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
  • agent-ready: whether public docs and HTTP APIs are discoverable to coding agents; this skill audits in-product agent UX
  • 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.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ax Audit AI skill do?

Audits agentic products for tool parity, authority, approval payloads, recovery, and trust using 27 rules and a ship verdict. Use when asked for an "AX audit", to review an agent approval flow, or whether an agent can operate the product. For human-facing API ergonomics use dx-audit; for ordinary UI use ui-design.

Why use Ax Audit on TypingMind?

Because you install it once and use it with any model. Ax Audit is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ax Audit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mblode/agent-skills/tree/main/skills/ax-audit. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ax Audit?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ax Audit?

As many as you like. As long as a model supports skills, you can use Ax Audit with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ax Audit AI skill free?

Yes. It is published on GitHub by mblode under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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