audit

A workflow for checking how completely a software feature has been implemented against its requirements.

In plain words
What is it for?
Use it to audit one feature or an entire project, assign implementation-completeness levels, summarize critical gaps, and create follow-up tasks.
Why use it?
It reveals missing or partial work by scanning the codebase for evidence such as routes, database models, services, components, and navigation.

Command

Part of the pokayokay plugin — 17 skills, 23 commands, 14 agents, 4 hooks, 1 MCP server shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/srstomp/pokayokay/audit
Clone the repo
git clone --depth 1 https://github.com/srstomp/pokayokay

Or install pokayokay, the plugin that ships this one along with the rest of its 17 skills, 23 commands, 14 agents, 4 hooks, 1 MCP server.

Per session 6 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,536 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00006 $0.01536
Opus 5 $0.00003 $0.00768
Sonnet 5 $0.00001 $0.00307
Haiku 4.5 $0.00001 $0.00154

Measured 3d ago against content hash 35e532e3357e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

audit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/pokayokay/commands/audit.md · 208 lines

How it starts

The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Feature Audit Workflow

Audit implementation completeness against requirements.

Feature: $ARGUMENTS (optional - audits all if not specified)

Agent Delegation

Delegate the codebase scanning to the yokay-auditor agent for isolated execution. This keeps verbose scan output separate from the main conversation.

Use the yokay-auditor agent to scan the codebase for feature implementation evidence.
Return only the summary table and critical gaps to this conversation.

The agent will:

  1. Detect project framework
  2. Scan for backend/frontend/route/navigation evidence
  3. Assign L0-L5 completeness levels
  4. Return a structured summary

After receiving the agent's summary, continue with remediation task creation below.

Steps

1. Get Task List

npx @stevestomp/ohno-cli tasks

Or use ohno MCP get_tasks.

2. Read Project Context

Read .claude/PROJECT.md for:

  • Expected features
  • Success criteria
  • Tech stack (to know where to look)

3. Scan Codebase

For each feature/task, search for implementation evidence:

Backend indicators:

  • API routes/endpoints
  • Database models/migrations
  • Service/controller files

Frontend indicators:

  • Components/pages
  • Route definitions
  • Navigation links

4. Assign Completeness Levels

Dimension 1: User Accessibility (L0-L5) - Default

Level Name Criteria
L0 Not Started No implementation found
L1 Backend Only API exists, no frontend
L2 Frontend Exists Component exists, not routable
L3 Routable Has route, not in navigation
L4 Accessible In navigation, missing polish
L5 Complete Fully implemented and accessible

Dimension 2: Testing Coverage (T0-T4)

Level Name Criteria
T0 No Tests No test files exist
T1 Unit Only Unit tests present, no integration
T2 Integration Unit + integration tests
T3 E2E E2E tests for critical paths
T4 Full Coverage >80% coverage, all test types

Read the full file on GitHub · 208 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 208 lines · 6 tokens per session scan A 35e532e3357e

Subscribe to this mod's changes

audit is a command published in the GitHub repository srstomp/pokayokay (9 stars, last pushed 1mo ago), licensed MIT. It adds 6 tokens to every session and 1,536 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.