reflect

Reflect on the conversation and update the brain. Use when wrapping up, after mistakes or corrections, or when significant codebase knowledge was gained. Triggers: "reflect", "remember this".

170 stars

Best use case

reflect is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Reflect on the conversation and update the brain. Use when wrapping up, after mistakes or corrections, or when significant codebase knowledge was gained. Triggers: "reflect", "remember this".

Teams using reflect should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/reflect/SKILL.md --create-dirs "https://raw.githubusercontent.com/poteto/brainmaxxing/main/.agents/skills/reflect/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/reflect/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How reflect Compares

Feature / AgentreflectStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Reflect on the conversation and update the brain. Use when wrapping up, after mistakes or corrections, or when significant codebase knowledge was gained. Triggers: "reflect", "remember this".

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Reflect

Review the conversation and persist learnings — to `brain/`, to skill files, or as structural enforcement.

## Process

1. **Read `brain/index.md`** to understand what notes already exist
2. **Scan the conversation** for:
   - Mistakes made and corrections received
   - User preferences and workflow patterns
   - Codebase knowledge gained (architecture, gotchas, patterns)
   - Tool/library quirks discovered
   - Decisions made and their rationale
   - Friction in skill execution, orchestration, or delegation
   - Repeated manual steps that could be automated or encoded
3. **Skip** anything trivial or already captured in existing brain files
4. **Route each learning** to the right destination (see Routing below)
5. **Update `brain/index.md`** if any brain files were added or removed

## Routing

Not everything belongs in the brain. Route each learning to where it will have the most impact.

### Structural enforcement check

Before routing a learning to `brain/`, ask: can this be a lint rule, script, metadata flag, or runtime check? If yes, encode it structurally and skip the brain note. See `brain/principles/encode-lessons-in-structure.md`.

### Brain files (`brain/`)

Codebase knowledge, principles, gotchas — anything that informs future sessions. This is the default destination. Use the `brain` skill for writing conventions.

- One topic per file. File name = topic slug.
- Group in directories with index files using `[[wikilinks]]`.
- No inlined content in index files.

### Skill improvements (`.agents/skills/<skill>/`)

If a learning is about how a specific skill works — its process, prompts, or edge cases — update the skill directly.

### Backlog items

Follow-up work that can't be done during reflection — bugs, non-trivial rewrites, tooling gaps. File as a todo or backlog item.

## Summary

```
## Reflect Summary
- Brain: [files created/updated, one-line each]
- Skills: [skill files modified, one-line each]
- Structural: [rules/scripts/checks added]
- Todos: [follow-up items filed]
```

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