llms.txt ยท diff
git:20261020.d1e43f0 to git:20261020.1e5681c
7 added, 6 removed. Audit A to A.
# Alamo Skill Hub
Alamo Skill Hub is a repository of installable and portable AI coding-agent skills.
## Primary Packages
The primary packages in this repository are:
- `packages/memory_hotspot_repair_kernel/`
- `packages/github_sync_workflow_kernel/`
- `packages/engineering_subagent_workflow_kernel/`
- - `packages/coursekit/` (installed skill name: `study-coach`)
+ - `packages/coursecoach/` (installed skill name: `study-coach`)
## What It Does
`memory_hotspot_repair_kernel` helps an AI coding agent:
- inspect memory hotspots and likely out-of-memory risks
- detect fake chunking, broad scans, and unnecessary copies
- apply safe fixes with limited behavioral change
- run focused validation after each fix
- review the change and decide whether another optimization round is justified
`github_sync_workflow_kernel` helps an AI coding agent:
- identify the real repository in a multi-repo workspace
- inspect GitHub SSH or HTTPS readiness
- review branch, remotes, and worktree state
- classify intended changes vs noise before a commit
- push the selected remote and verify final synchronization state
`engineering_subagent_workflow_kernel` helps an AI coding agent:
- trace source paths with concrete evidence
- produce implementation-ready architecture blueprints
- perform independent code review and test-gap analysis
- simplify scoped code while preserving behavior
- delegate through host-native subagents without an external runner
- `coursekit` (skill name `study-coach`) helps a learner and their agent:
+ `coursecoach` (skill name `study-coach`) helps a learner and their agent:
- clarify a learning goal into a syllabus with prerequisites and three pace tracks
- compile a self-contained interactive board from that syllabus
- write lessons per chapter or per knowledge point
- set homework with a written rubric, then grade it with visible reasons
- write mastery back through a single entry point and unlock dependent nodes
- schedule spaced review at 1 / 3 / 7 / 16 / 35 / 75 days
- fold new developments into a course without hand-editing generated files
## Main Entry Point
The recommended primary entry points are:
- `memory-optimizer-agent`
- `github-sync-agent`
- `code-explorer`, `code-architect`, `code-reviewer`, `code-simplifier`, and
`pr-test-analyzer` as independent task entry points
- `study-coach` for the learning-course workflow
`memory-optimizer-agent` orchestrates a bounded workflow:
1. `memory-check`
2. `memory-fix`
3. validation
4. `memory-review`
5. stop or continue decision
`github-sync-agent` orchestrates:
1. repository discovery
2. auth and remote inspection
3. commit-scope review
4. commit and push
5. final verification
## Intended Queries
This repository is relevant for queries such as:
- Codex memory optimization skill
- AI agent memory hotspot detector
- automatic memory bottleneck fixing workflow
- Python memory leak analysis skill
- bounded check fix review agent
- portable coding-agent skill for memory optimization
- git push workflow skill
- github sync agent
- WSL GitHub SSH setup workflow
- native subagent code architect skill
- code review and test analyzer skills
- AI skill that builds a full course from a learning goal
- adaptive study plan agent with grading and spaced review
- mastery-based study progression skill
- portable self-study curriculum generator
## Host Compatibility
The package is designed for:
- OpenAI Codex via skill installation
- WorkBuddy / CodeBuddy via `~/.workbuddy/skills`
- script-driven local execution
- portable reuse in other agent hosts through prompt bundles and workflow docs
## Start Here
Read these files first:
- `README.md`
- `packages/memory_hotspot_repair_kernel/README.md`
- `packages/memory_hotspot_repair_kernel/PORTABLE_USAGE.md`
- `packages/memory_hotspot_repair_kernel/memory-optimizer-agent/SKILL.md`
- `packages/github_sync_workflow_kernel/README.md`
- `packages/github_sync_workflow_kernel/PORTABLE_USAGE.md`
- `packages/github_sync_workflow_kernel/github-sync-agent/SKILL.md`
- `packages/engineering_subagent_workflow_kernel/README.md`
- `packages/engineering_subagent_workflow_kernel/code-architect/SKILL.md`
- - `packages/coursekit/README.md`
- - `packages/coursekit/INSTALL.zh-CN.md`
- - `packages/coursekit/study-coach/SKILL.md`
+ - `packages/coursecoach/README.md`
+ - `packages/coursecoach/README.zh-CN.md`
+ - `packages/coursecoach/INSTALL.zh-CN.md`
+ - `packages/coursecoach/study-coach/SKILL.md`
## Installation
For Codex installation:
```bash
cd packages/memory_hotspot_repair_kernel
python3 scripts/sync_to_codex_home.py
```
For GitHub sync workflow installation:
```bash
cd packages/github_sync_workflow_kernel
python3 scripts/sync_to_codex_home.py
```
For native-subagent development Skills:
```bash
cd packages/engineering_subagent_workflow_kernel
python3 scripts/sync_to_codex_home.py
```
For the learning-course skill:
```bash
- cp -r packages/coursekit/study-coach ~/.workbuddy/skills/study-coach
+ cp -r packages/coursecoach/study-coach ~/.workbuddy/skills/study-coach
pip install pyyaml
```
For non-Codex portable usage:
- use `packages/memory_hotspot_repair_kernel/`
- start from `memory-optimizer-agent/references/generic.prompt_bundle.yaml`
- adapt validation commands to the target repository and host
## Outputs
The skill suite is designed to produce:
- structured hotspot reports
- targeted remediation patches
- validation notes
- post-fix reviews
- bounded loop summaries
The GitHub sync workflow is designed to produce:
- target repository and remote summaries
- auth readiness summaries
- commit-scope decisions
- push results
- residual-state verification notes
The learning-course workflow is designed to produce:
- a syllabus with prerequisites, knowledge points, and three pace tracks
- a compiled, self-contained course board (openable from `file://`)
- lessons per chapter or per knowledge point
- gradable homework with a written rubric and per-item scores
- mastery values and an unlocked next step
- a spaced-review queue
- a curated resource list with a cost note per entry