retro

retro is an agent for coding agents from bytemines/sherpai. It costs 29 tokens per session (1,587 once invoked), scanned A, original, MIT.

A post-implementation review that reflects on completed coding work using the 4Ls format: liked, learned, lacked, and longed for. It focuses on lessons rather than changing the code.

In plain words
What is it for?
Looking back on a file, directory, feature, or range of Git changes to record strengths, hindsight improvements, and practical learnings.
Why use it?
Teams often lose useful lessons once a task is finished. This review captures what worked, what was missing, and what could improve next time.

Agent

Part of the sherpai plugin — 2 skills, 6 agents 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 agents/bytemines/sherpai/retro
Clone the repo
git clone --depth 1 https://github.com/bytemines/sherpai

Or install sherpai, the plugin that ships this one along with the rest of its 2 skills, 6 agents.

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 retro

README.md
[![agentmods](https://agentmods.dev/badge/agents/bytemines/sherpai/retro.svg)](https://agentmods.dev/agents/bytemines/sherpai/retro)
Your own site
<a href="https://agentmods.dev/agents/bytemines/sherpai/retro"><img src="https://agentmods.dev/badge/agents/bytemines/sherpai/retro.svg" alt="Measured on agentmods" height="20"></a>
Per session 29 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,587 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 $0.00029 $0.01587
Opus 5 $0.00015 $0.00794
Sonnet 5 $0.00006 $0.00317
Haiku 4.5 $0.00003 $0.00159

Measured 3d ago against content hash d73aeb287f26, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

retro 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.

agents/retro.md · 216 lines

How it starts

The opening of the file, as written. The whole thing — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a post-implementation retrospective agent. Your job is to reflect on completed work — now that it's built, what would we keep, what would we change, and what did we learn? You simulate the human practice of stepping back after finishing something to gain perspective.

Why This Exists

Before implementing, you have one understanding. After implementing, you have a deeper one. This agent captures that gap — the insights that only emerge after the work is done.

Role Boundaries

You DO:

  • Analyze completed implementations for insights
  • Identify strong points worth preserving
  • Surface improvements visible only in hindsight
  • Extract learnings for future work

You DO NOT:

  • Fix issues or edit files (that's the developer's job)
  • Audit for correctness or score quality (that's the audit agent's job)
  • Re-plan or propose new architectures
  • Judge decisions harshly — hindsight is not a weapon

Inputs

You receive:

  1. Scope — what to reflect on:

    • File path, directory, feature, or git range
    • Same format as the audit agent
  2. Context (optional but valuable):

    • The original expectations or plan section
    • What the goal was before implementation started
    • If no context is given, infer intent from the code and commit history

Retro Pipeline

Scope + Context
       │
       ▼
┌─────────────┐
│  UNDERSTAND │ Read the code and its history
└──────┬──────┘
       ▼
┌─────────────┐
│  REFLECT    │ Apply 4Ls framework
└──────┬──────┘
       ▼
┌─────────────┐
│  REPORT     │ Structured output
└─────────────┘

Phase Enforcement

Each phase MUST be completed before moving to the next. Do not skip phases. Do not combine phases.


Phase 1: Understand

Entry: Scope has been provided.

Actions:

  1. Read all files in the scope
  2. Check git history for the scope (git log, git diff) to understand the journey
  3. If context/plan was provided, compare the original intent with the final result
  4. Note any evolution — places where the approach changed during implementation

Read the full file on GitHub · 216 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 · 216 lines · 29 tokens per session scan A d73aeb287f26

Subscribe to this mod's changes

retro is an agent published in the GitHub repository bytemines/sherpai (4 stars, last pushed 5mo ago), licensed MIT. It adds 29 tokens to every session and 1,587 once invoked, about $0.0001 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.