review

review is a command for coding agents from srstomp/pokayokay. It costs 6 tokens per session (773 once invoked), scanned A, original, MIT.

A command for reviewing finished coding sessions to find successes, problems, and recurring patterns. It examines task history and recent Git commits.

In plain words
What is it for?
Use it to review completed work, assess code changes and tests, and document improvements for future sessions.
Why use it?
It helps reveal delays, blockers, rework, missing requirements, and lost context that may otherwise repeat.

Command

Part of the pokayokay plugin — 24 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/review
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 24 skills, 23 commands, 14 agents, 4 hooks, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for review

README.md
[![agentmods](https://agentmods.dev/badge/commands/srstomp/pokayokay/review.svg)](https://agentmods.dev/commands/srstomp/pokayokay/review)
Your own site
<a href="https://agentmods.dev/commands/srstomp/pokayokay/review"><img src="https://agentmods.dev/badge/commands/srstomp/pokayokay/review.svg" alt="Measured on agentmods" height="20"></a>
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 773 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 $0.00773
Opus 5 $0.00003 $0.00387
Sonnet 5 $0.00001 $0.00155
Haiku 4.5 $0.00001 $0.00077

Measured 5d ago against content hash e52327dcc319, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

review 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 5d 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/review.md · 131 lines

How it starts

The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Session Review Workflow

Analyze recent work sessions to identify what went well, what went wrong, and patterns to improve.

Steps

1. Get Session History

Use ohno MCP get_session_context or:

npx @stevestomp/ohno-cli context

2. Review Completed Tasks

npx @stevestomp/ohno-cli tasks

Check for patterns:

  • Tasks that took longer than expected
  • Tasks that were blocked
  • Tasks completed quickly

3. Check Git History

git log --oneline -20

Look for:

  • Commit frequency and quality
  • Reverts or fixes
  • Patterns in commit messages

4. Identify What Went Well

  • Features completed successfully
  • Clean implementations
  • Good test coverage
  • Smooth handoffs

5. Identify What Went Wrong

  • Blockers encountered
  • Tasks that needed rework
  • Missing requirements discovered late
  • Context loss between sessions

6. Extract Patterns

Document recurring issues:

  • Common blockers
  • Frequent mistake types
  • Areas needing more upfront planning

6.1 Skill Effectiveness Analysis

Skills Used This Session

Review which skills were invoked and their outcomes:

| Skill | Times Used | Success Rate | Avg Duration |
|-------|------------|--------------|--------------|
| api-design | 3 | 100% | 45 min |
| testing-strategy | 2 | 50% | 60 min |
| spike | 1 | GO decision | 2.5 hours |
Spike Outcomes

Track spike decisions and follow-through:

Spike Decision Follow-up Created Implemented
D1 Multi-tenant GO 3 tasks 1 of 3
Redis Caching NO-GO 0 tasks N/A
Skill Gaps Identified

Note when work would have benefited from a skill:

  • Database migration manually done - would benefit from database-design
  • CI pipeline created without ci-cd - missing caching optimization
  • No security review on auth changes - should use security-audit

6.2 Session Quality Metrics

Metric This Session Trend
Tasks completed 5 +2 vs avg
Tasks blocked 1 Same
Bugs discovered 2 +1 vs avg
Spikes completed 1 New
Skills invoked 3 +1 vs avg
Commits per task 1.2 Same

Read the full file on GitHub · 131 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. 5d ago First seen · 131 lines · 6 tokens per session scan A e52327dcc319

Subscribe to this mod's changes

review is a command published in the GitHub repository srstomp/pokayokay (9 stars, last pushed 2mo ago), licensed MIT. It adds 6 tokens to every session and 773 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.