Audit logo

Audit

Organization
ww-w-ai
audit

View audit logs, decision traces, and session history for AI transparency. ACTION_TYPES (19 entries) include PDCA events (phase_transition, gate_passed/failed, agent_spawned/completed/failed, rollback_executed, destructive_blocked) and Sprint events (sprint_paused, sprint_resumed, master_plan_created — v2.1.13). Triggers: audit, log, decision trace, history

Overview

Publisherww-w-ai
Repositorybkit-claude-code
Skill nameaudit
Stars
601
Forks
154
Bundled files
Instructions only
LicenseApache-2.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by ww-w-ai on GitHub. Read the source before you install it.

Installation

Install the 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/ww-w-ai/bkit-claude-code.git /tmp/bkit-claude-code
mkdir -p .claude/skills
cp -r /tmp/bkit-claude-code/skills/audit .claude/skills/audit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 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 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 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.

Audit Skill

User-invocable skill for viewing audit logs, decision traces, and session history.

Arguments

ArgumentDescriptionExample
(none)Show recent audit log entries (same as log)/audit
logShow recent audit log entries (last 20)/audit log
trace <feature>Show decision traces for a feature/audit trace user-auth
summaryShow daily/weekly audit summary/audit summary
search <query>Search audit logs by action type, feature, or date/audit search "phase_transition"

Action Details

log (Default)

Display recent audit log entries.

  1. Read today's audit log from .bkit/audit/YYYY-MM-DD.jsonl
  2. If today's log is empty or has fewer than 20 entries, also read yesterday's log
  3. Parse JSONL entries (one JSON object per line)
  4. Display the last 20 entries in reverse chronological order
  5. Format each entry with timestamp, action, feature, and details

JSONL Entry Schema:

json
{
  "timestamp": "2026-03-19T10:30:00.000Z",
  "action": "phase_transition",
  "feature": "user-auth",
  "from": "plan",
  "to": "design",
  "automationLevel": "semi-auto",
  "triggeredBy": "user",
  "details": "Plan approved, transitioning to Design"
}

Output Format:

--- Audit Log (Last 20 Entries) -------------------
[2026-03-19 10:30] phase_transition | user-auth
  plan -> design (Semi-Auto, user-triggered)

[2026-03-19 10:25] checkpoint_created | user-auth
  Checkpoint cp-1710842700000 before Design phase

[2026-03-19 10:20] automation_level_changed | -
  L1 -> L2 (trust score: 72)
...
---------------------------------------------------
Total entries today: 45

trace

Show decision traces for a specific feature.

  1. Read decision trace files from .bkit/decisions/YYYY-MM-DD.jsonl
  2. Filter entries matching the specified feature
  3. Display chronological decision chain with rationale

Decision Trace Entry Schema:

json
{
  "timestamp": "2026-03-19T10:30:00.000Z",
  "feature": "user-auth",
  "decision": "advance_to_design",
  "rationale": "Plan document complete, matchRate N/A at this phase",
  "alternatives": ["request_plan_revision", "skip_to_do"],
  "chosenBecause": "Plan deliverable exists and passes validation",
  "automationLevel": "semi-auto",
  "confidence": 0.92
}

Output Format:

--- Decision Trace: user-auth ---------------------
[10:15] START -> pm
  Decision: Begin PDCA cycle
  Rationale: New feature request detected

[10:20] pm -> plan
  Decision: advance_to_plan
  Rationale: PRD document generated successfully
  Alternatives: [reject_prd, revise_scope]
  Confidence: 0.88

[10:30] plan -> design
  Decision: advance_to_design
  Rationale: Plan document complete, passes validation
  Alternatives: [request_plan_revision, skip_to_do]
  Confidence: 0.92
---------------------------------------------------
Total decisions: 3

summary

Show daily or weekly audit summary.

  1. Read audit logs for the current day (and optionally past 7 days)
  2. Aggregate by action type and count occurrences
  3. Calculate key metrics:
    • Total actions recorded
    • Phase transitions count
    • Automation vs manual ratio
    • Error/recovery events
    • Average trust score change
  4. Display formatted summary

Output Format:

--- Audit Summary (2026-03-19) --------------------
Total Actions       : 45
Phase Transitions   : 12
Checkpoints Created : 4
Errors Recorded     : 1
Recoveries          : 1

Action Breakdown:
  phase_transition       : 12 (27%)
  checkpoint_created     :  4 (9%)
  match_rate_recorded    :  8 (18%)
  automation_level_change:  2 (4%)
  iteration_completed    :  6 (13%)
  other                  : 13 (29%)

Automation Ratio: 67% auto / 33% manual
Trust Score Change: +3 (69 -> 72)
---------------------------------------------------
Weekly Trend (last 7 days):
  Mon: 32 actions | Tue: 45 actions | Wed: 28 actions
  ...

search

Search audit logs by action type, feature name, or date range.

  1. Parse the search query to determine filter type:
    • If query matches an action type (e.g., phase_transition), filter by action
    • If query matches a feature name, filter by feature
    • If query matches a date (YYYY-MM-DD), filter by date
    • Otherwise, perform full-text search across all fields
  2. Read relevant JSONL files from .bkit/audit/
  3. Apply filters and return matching entries (max 50 results)
  4. Display results in chronological order

Search Examples:

bash
# Search by action type
/audit search "phase_transition"

# Search by feature name
/audit search "user-auth"

# Search by date
/audit search "2026-03-18"

# Full-text search
/audit search "error"

File Locations

PathFormatPurpose
.bkit/audit/YYYY-MM-DD.jsonlJSONLDaily audit log entries
.bkit/audit/summary/JSONPre-computed daily/weekly summaries
.bkit/decisions/YYYY-MM-DD.jsonlJSONLDecision trace entries

Module Dependencies

ModuleFunctionUsage
lib/audit/audit-logger.jsreadAuditLog()Read audit entries
lib/audit/audit-logger.jssearchAuditLog()Search/filter entries
lib/audit/decision-tracer.jsgetDecisionTrace()Read decision traces

Retention Policy

  • Audit logs: 30-day retention, auto-cleanup via daily hook
  • Decision traces: 30-day retention, linked to audit logs
  • Total storage budget: 100MB (auto-prune oldest when exceeded)

Usage Examples

bash
# View recent log entries
/audit

# View decision trace for a feature
/audit trace user-auth

# View daily summary
/audit summary

# Search for phase transitions
/audit search "phase_transition"

# Search by feature
/audit search "user-auth"

Frequently asked questions

What does the Audit AI skill do?

View audit logs, decision traces, and session history for AI transparency. ACTION_TYPES (19 entries) include PDCA events (phase_transition, gate_passed/failed, agent_spawned/completed/failed, rollback_executed, destructive_blocked) and Sprint events (sprint_paused, sprint_resumed, master_plan_created — v2.1.13). Triggers: audit, log, decision trace, history

Why use Audit on TypingMind?

Because you install it once and use it with any model. 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 Audit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ww-w-ai/bkit-claude-code/tree/main/skills/audit. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use 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 Audit?

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

Is the Audit AI skill free?

Yes. It is published on GitHub by ww-w-ai under the Apache-2.0 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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