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 skills/poteto/brainmaxxing/reflectnpx skills add poteto/brainmaxxing --skill reflectgit clone --depth 1 https://github.com/poteto/brainmaxxingWhat 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 | $0.00040 | $0.00514 |
| Opus 5 | $0.00020 | $0.00257 |
| Sonnet 5 | $0.00008 | $0.00103 |
| Haiku 4.5 | $0.00004 | $0.00051 |
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 2d 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reflect
Review the conversation and persist learnings — to brain/, to skill files, or as structural enforcement.
Process
- Read
brain/index.mdto understand what notes already exist - 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
- Skip anything trivial or already captured in existing brain files
- Route each learning to the right destination (see Routing below)
- Update
brain/index.mdif 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]
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.
- 2d ago First seen · 61 lines · 40 tokens per session scan A 9489b1126ea8
reflect is a skill published in the GitHub repository poteto/brainmaxxing (273 stars, last pushed 6mo ago), licensed MIT. It adds 40 tokens to every session and 514 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
article-writing
Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.
a-evolve
Apply A-Evolve's agentic evolution methodology to improve AI agent performance across runs. Use when the user wants to diagnose agent failures, generate targeted skills from error patterns, evolve system prompts, or accumulate episodic knowledge. Works standalone or inside AutoResearchClaw pipelines. Triggers on…
hive.chart-creation-foundations
Required reading whenever any chart tool is available. Teaches the one-tool embedding contract (call chartrender → live chart appears in chat AND a downloadable PNG lands in the queen session dir), the ECharts (data viz) vs Mermaid (structural diagrams) decision, the BI/financial-grade aesthetic baseline (no…
📝 任务完成后归档
重要提醒: 每次完成复杂调试或开发任务后，主动执行此流程！ 将学到的经验归档为 skill，供以后参考。不要等用户提醒。.
deck-course-module
暖纸背景 + Playfair, 左侧学习目标常驻, 含 MCQ 自测页.
code-documenter
Use when adding docstrings, creating API documentation, or building documentation sites. Invoke for OpenAPI/Swagger specs, JSDoc, doc portals, tutorials, user guides.