fireworks-skill-memory

name: fireworks-skill-memory description: Persistent cross-session experience memory for Claude Code and Codex skills. TRIGGER when user asks about skill memory, experience distillation, cross-session learning, skill knowledge injection, Claude/Codex memory, session-to-session improvement, or wants to install/configure fireworks-skill-memory.

Persistent experience memory for Claude Code and Codex skills. Shared memory core, runtime-specific adapters, skill-scoped lessons.

What It Does

Every coding-agent session starts from zero. The same mistakes repeat — wrong API parameters, broken sequences, proxy pitfalls — because the runtime has no durable skill memory between sessions.

fireworks-skill-memory solves this by:

Injecting past experience when a skill is invoked
Distilling new lessons into skill-scoped knowledge files
Keeping runtime-specific adapters thin so Claude hooks and Codex explicit flows share one memory core

Installation

Quick Install (Recommended)

In Claude Code, say:

"Help me install fireworks-skill-memory from https://github.com/yizhiyanhua-ai/fireworks-skill-memory"

Or run the one-command installer:

curl -fsSL https://raw.githubusercontent.com/yizhiyanhua-ai/fireworks-skill-memory/main/install.sh | bash

npx skills Install

npx skills add yizhiyanhua-ai/fireworks-skill-memory -g

After installing via npx skills, run the installer to set up hooks:

curl -fsSL https://raw.githubusercontent.com/yizhiyanhua-ai/fireworks-skill-memory/main/install.sh | bash

Codex Setup

Run:

./install-codex.sh

Then use:

python3 cli/skill_memory.py inject --skill <skill-name>
python3 cli/skill_memory.py checkpoint --skill <skill-name> --note "..."
python3 cli/skill_memory.py flush --skill <skill-name> --summary-file ./session-summary.md

How It Works

Claude Code installs 4 hooks that run automatically:

Hook	Trigger	Script	Purpose
`PreToolUse`	Before Skill call	`pre-skill-inject.py`	Inject full KNOWLEDGE.md before skill executes
`PostToolUse`	After Read SKILL.md	`inject-skill-knowledge.py`	Inject top-N entries by relevance + capture error seeds
`PostToolUse`	After any tool call	`error-seed-capture.py`	Capture error signals to session-scoped file
`Stop`	Session end (async)	`update-skills-knowledge.py`	Distill new lessons via Haiku, update KNOWLEDGE.md

Codex uses explicit runtime commands instead:

Command	Purpose
`inject`	Load top-ranked lessons for a skill before a task
`checkpoint`	Save raw notes into the skill directory
`flush`	Distill explicit lesson sections from summary/session inputs into `KNOWLEDGE.md`

Data Flow

Skill invoked → PreToolUse injects experience → Claude executes with context
                                                    ↓
Session ends → Stop hook reads transcript → Haiku distills 1-3 lessons
                                                    ↓
                              KNOWLEDGE.md updated → Ready for next session

Codex task starts → inject loads top lessons → Codex executes with context
                                                ↓
Checkpoint/summary captured → flush distills explicit lessons
                                                ↓
                      KNOWLEDGE.md updated → Ready for next session

Knowledge Storage

<memory-home>/skills/<skill-name>/KNOWLEDGE.md   ← Distilled per-skill experience
<memory-home>/skills/<skill-name>/CHECKPOINTS.md ← Raw runtime notes
<memory-home>/global/KNOWLEDGE.md                ← Global cross-skill principles

Claude legacy runtime also uses:
~/.claude/skills/<skill-name>/KNOWLEDGE.md
~/.claude/skill-usage-stats.json
~/.claude/skill-memory.log

Each entry is tagged with [YYYY-MM] timestamp and [HIT:N] usage counter. Low-frequency, old entries are evicted first.

Configuration (Optional)

All settings are optional, configured via environment variables:

Variable	Default	Description
`SKILLS_KNOWLEDGE_MODEL`	`claude-haiku-4-5`	Default model for the Claude CLI distiller backend
`SKILLS_DISTILLER_BACKEND`	`claude-cli`	Distiller backend selector: `claude-cli`, `openai`, or `null`
`SKILLS_DISTILLER_DEBUG`	unset	Enable backend debug logging to the default distiller log file
`SKILLS_DISTILLER_LOG`	unset	Explicit path for distiller debug logs
`SKILL_MAX`	`100`	Max entries per skill
`GLOBAL_MAX`	`100`	Max global entries
`MIN_TOOL_CALLS`	`5`	Skip sessions with fewer calls (likely summaries)
`SKILLS_INJECT_TOP`	`20`	Max entries injected per active invocation

Requirements

Python 3.9+
Claude Code CLI for the automatic Claude runtime
Claude Haiku access for the default Claude CLI distiller backend
CODEX_HOME for the Codex runtime setup helper
OPENAI_API_KEY / OPENAI_BASE_URL / OPENAI_MODEL when using the OpenAI distiller backend
SKILLS_DISTILLER_DEBUG or SKILLS_DISTILLER_LOG when debugging backend failures

fireworks-skill-memory