# Audit Rubric

> Scoring rubric for evaluating production-AI deployment readiness. The marquee `production-audit` skill uses this rubric to compute the 0-100 score. Auto-loaded so scoring is consistent across sessions and so the user can self-score independently. Use this rubric whenever auditing, reviewing, or quantifying a deployment's production-readiness.

- **Type:** Skill
- **Install:** `agentstack add skill-temurkhan13-aufgaard-audit-rubric`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [temurkhan13](https://agentstack.voostack.com/s/temurkhan13)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [temurkhan13](https://github.com/temurkhan13)
- **Source:** https://github.com/temurkhan13/aufgaard/tree/main/skills/audit-rubric

## Install

```sh
agentstack add skill-temurkhan13-aufgaard-audit-rubric
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Audit Rubric (35-pattern scoring)

The Aufgaard audit produces a 0-100 score. This rubric is the canonical scoring framework — same logic across sessions, same logic the bundle's Field Reference PDF documents.

## Scoring formula

Start at **100**. Subtract:

- **−15 per CRITICAL finding** — confirmed, actively-firing, in-production-path
- **−5 per HIGH finding** — confirmed pattern hit but in a less-critical path, OR a critical pattern with mitigating controls
- **−2 per MEDIUM finding** — pattern matches loosely, or short-window observation
- **0 for partial-coverage gaps** — honest disclosure that we couldn't measure

Floor at **0**. Cap at **100**. Round to integer.

## Severity assignment per pattern

For each of the 35 patterns, the audit assigns a severity based on:

1. **Whether the pattern is firing** (any rule hit in the underlying MCP scan)
2. **Where it's firing** (production code path vs dev / test / scratch)
3. **How recent** (last 7 days = elevated; older = baseline)
4. **Mitigation present** (e.g. bash-vet hook IS active = mitigated even if rule fires; without hook = critical)

### Default severity ladder

| Pattern category | Default if firing in production path |
|---|---|
| P5.y bash destructive (active BLOCK match) | CRITICAL if no hook; HIGH with hook |
| P5.z agent-config attack (active BLOCK match) | CRITICAL — always |
| P3.4 HERMES.md / 429-imminent $50/mo waste) | MEDIUM |
| P7.2 no per-agent cost attribution | MEDIUM |
| P2.x OOM / CPU spike (active) | HIGH |
| P3.1-P3.3 connection / networking (active) | HIGH (MEDIUM if intermittent) |
| Partial coverage (e.g. ~ tier in catalogue) | DON'T penalize — this is honest disclosure |
| Uncovered (❌ tier in catalogue) | DON'T penalize — flagged as gap |

## Score interpretation

| Range | Color | Verdict |
|---|---|---|
| 90-100 | 🟢 | Excellent — production-ready; maintenance mode |
| 75-89 | 🟢 | Good — minor polish; nothing blocking deploy |
| 60-74 | 🟡 | Watch — at least 1 high finding; address this week |
| 40-59 | 🟡 | Attention needed — multiple high findings; address before next major change |
| 20-39 | 🔴 | At-risk — critical findings present; halt expansions, fix critical |
| 0-19 | 🔴 | Production-AI emergency — multiple critical findings; serious review needed |

## Coverage modifier

The aggregate audit score is the BASE. We also report a **coverage modifier** for honesty:

```
Effective score:  · Coverage: /35 patterns measurable from your data (%)
```

If only 23 of 35 patterns are measurable from the user's data (e.g. they don't have a JSONL log for cost-tracker yet), the score is computed from those 23 patterns only — and we say so. We don't pretend a partial scan is a full audit.

Example:
> Score: 78/100 (across 23 measurable patterns) · 12 patterns uncovered or unmeasurable from current data — see Coverage breakdown for the gap list.

## Recommendation templates

For each finding, the audit suggests a remediation. Templates:

### CRITICAL — Halt
```
> 🔴 P-id:  — CRITICAL
> Halt expansion of [feature]; remediate immediately.
> Specific action: [grounded in the data — e.g. "rewrite cron-summarizer at  to add explicit heartbeat + non-zero exit on no-data scenario"]
```

### HIGH — Address this week
```
> 🟡 P-id:  — HIGH
> Address within 7 days.
> Specific action: [grounded in the data]
```

### MEDIUM — Schedule
```
> 🟢 P-id:  — MEDIUM
> Schedule for next maintenance window.
> Specific action: [grounded in the data]
```

## Anti-patterns in scoring

These would invalidate an audit:

- ❌ **Speculation** — "this might be P5.y" without an actual rule hit. Don't penalize for "could happen"; penalize for "is happening."
- ❌ **Padding** — listing 7 medium findings when 2 of them are the same root cause. Group into one.
- ❌ **Generic recommendations** — "improve error handling" is not a recommendation; "rewrite line 17 of api.py to remove `except: pass`" is.
- ❌ **Hidden assumptions** — if the data is incomplete, say so. Don't compute a 95/100 from a 5/35-pattern partial scan and pretend it's comprehensive.

## Re-audit cadence

The audit is point-in-time. Re-run via `/aufgaard:production-audit`:

- **After any major code change** that touches LLM-call sites or agent config
- **After any package upgrade** of a dependency in the catalogue
- **Weekly** as a routine pulse-check
- **After incident response** to verify the fix didn't introduce new patterns
- **Before any expansion** (new agent, new domain, new integration)

The audit report should always include a "Next audit recommended in [N] days" footer based on the score band — higher scores get longer cadences.

## Score-trend tracking (future)

Scoring history is currently per-session. Future v1.x could persist scores to a local file for trend tracking ("score went 78 → 84 over 30 days; you fixed P6.2 in `agents/billing.py`"). Not yet built; flagged as enhancement.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [temurkhan13](https://github.com/temurkhan13)
- **Source:** [temurkhan13/aufgaard](https://github.com/temurkhan13/aufgaard)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-temurkhan13-aufgaard-audit-rubric
- Seller: https://agentstack.voostack.com/s/temurkhan13
- Browse the marketplace: https://agentstack.voostack.com/browse

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