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.
npx agentmods add commands/joelyyoung/retrolens/reflectgit clone --depth 1 https://github.com/JoelYYoung/retrolensWrote 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.
[](https://agentmods.dev/commands/joelyyoung/retrolens/reflect)<a href="https://agentmods.dev/commands/joelyyoung/retrolens/reflect"><img src="https://agentmods.dev/badge/commands/joelyyoung/retrolens/reflect.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00538 |
| Opus 5 | $0.00000 | $0.00269 |
| Sonnet 5 | $0.00000 | $0.00108 |
| Haiku 4.5 | $0.00000 | $0.00054 |
Grade A, and why
reflect 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.
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
retrolens:reflect Command
Extract reusable human lessons and agent directives from a session analysis.
Full skill reference: Read
./SKILL.md→ Workflow D for lesson formats and writing standards.
Prerequisites
Run /retrolens:analyze first to produce a session analysis.
Usage
/retrolens:reflect [<session-id>] [--out <file>] [--format <md|json>]
Arguments
<session-id>- Session ID/prefix,latest, or omit to use the most recently analyzed session
Options
--out <file>- Write output to a file (default:notes/session-<ID>-lessons.md)--format <md|json>- Output format (default:md)
What This Command Does
Step 1: Read the session through learning lenses
For each turn, identify:
| Signal | What to look for |
|---|---|
| 🔴 Errors & Fixes | Tool failures, repeated retries, user corrections |
| 🟡 Inefficiency | Unnecessary exploration, redundant reads, off-target tool calls |
| 🟢 Effective practices | Right tool first try, clean drill-down, good commit points |
| ⚠️ Environment traps | API limits, version issues, proxy failures |
Step 2: Produce two output sections
Human lessons — how to interact with agents better:
- Which prompts worked first try vs. caused confusion?
- What upfront context would have saved turns?
- Which tasks were too large and should be split?
Agent directives — reusable rules for future sessions:
- Project conventions (naming, file structure, import order)
- Environment gotchas (proxy, API keys, version constraints)
- Sequencing rules ("always run tests after editing")
- Known pitfalls discovered in this session
Step 3: Write the artifact
Ask the user where to save:
Where should I write the lessons?
notes/session-<ID>-lessons.md— standalone file- Append to
AGENTS.md— VS Code Copilot instructions- Append to
CLAUDE.md— Claude Code instructions- Append to
.github/copilot-instructions.md— Copilot global- Custom path
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.
- 5d ago First seen · 68 lines · 0 tokens per session scan A 9ab9ca4efe60
reflect is a command published in the GitHub repository JoelYYoung/retrolens (2 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 538 tokens. 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.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
session-end
I'll summarize this coding session and update the memory system with our accomplishments.
memory-store
Store an insight, decision, or pattern to memory.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.