hierarchical-agent-memory

Scoped CLAUDE.md memory system (HAM) that cuts context-token spend with directory-level context files, a decisions/patterns memory layer, and a savings dashboard. USE WHEN a multi-directory project keeps re-reading the same files and you want scoped agent memory.

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Repository: Sheshiyer/skill-clusters
Letzte Quellaktivität: 5. Juni 2026 um 17:21
Erkannte Sprache von SKILL.md: Englisch
Sterne: 0
Forks: 1

Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.

Ein direkter Befehl überspringt den Prüf-Prompt. Prüfen Sie die Quelle, bevor Sie ihn ausführen.

npx skills add https://github.com/Sheshiyer/skill-clusters --skill hierarchical-agent-memory

Der Befehl bleibt in einer Zeile. Scrollen Sie horizontal, um ihn vor dem Kopieren vollständig zu prüfen.

Sie bevorzugen eine lokale Kopie? Laden Sie die Dateien herunter, die SkillsMP derzeit vorliegen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

SKILL.md

Quellanweisungen · Schreibgeschützte Vorschau

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arcplume

Arcplume runs Grok through the Grok Build CLI's own OAuth-authenticated session (grok login) for image generation, with strict preflight validation, secret-safe handling, and headless CLI-driven execution -- no separate XAI_API_KEY billing. Video falls back to the billed xAI API. USE WHEN a user wants to generate an image via a locally logged-in Grok Build CLI session, e.g. 'generate an image with grok', 'use grok build', or 'use my logged-in grok session'.

2026-07-07

selemene-core

Shared reference for the Selemene cluster: the two report surfaces (deterministic Rust reports vs. narrative witness-pipeline readings), the @selemene/bridge CLI contract, the output manifest format, and non-prescriptive witnessing tone. USE WHEN deciding which Selemene surface to invoke or when routing between birth/compatibility/transit reports and solo/dyadic readings.

2026-07-07

selemene-orchestrator

Route Selemene Engine tasks to the right surface: deterministic reports (birth/compatibility/transit) via selemene-core and the @selemene/bridge CLI, or narrative witness readings via selemene-report. USE WHEN the user wants anything under the Selemene/Noesis umbrella but has not named the exact surface.

2026-07-07

Alle aus diesem Repository ansehen

.memory/

project/
├── CLAUDE.md              # Root context (~200 tokens)
├── .memory/
│   ├── decisions.md       # Architecture Decision Records
│   ├── patterns.md        # Reusable patterns
│   ├── inbox.md           # Inferred items awaiting confirmation
│   └── audit-log.md       # Audit history
└── src/
    ├── api/CLAUDE.md      # Scoped context for api/
    ├── components/CLAUDE.md
    └── lib/CLAUDE.md

## Context Routing

→ api: src/api/CLAUDE.md
→ components: src/components/CLAUDE.md
→ lib: src/lib/CLAUDE.md

Trigger	What it does
`go ham`	Set up HAM — auto-detect platform, generate CLAUDE.md files
`ham savings`	Show token and cost savings report
`ham dashboard`	Launch the interactive web dashboard
`ham audit`	Health check on memory files
`ham insights`	Generate actionable insights from session data
`ham route`	Add/update Context Routing section in root CLAUDE.md
`ham carbon`	Show energy and carbon efficiency data

User: go ham

Agent: HAM setup complete. Created 8 files.
  - CLAUDE.md (root)
  - .memory/decisions.md
  - .memory/patterns.md
  - .memory/inbox.md
  - src/api/CLAUDE.md
  - src/components/CLAUDE.md
  - src/lib/CLAUDE.md
  - src/utils/CLAUDE.md

Baseline captured in .memory/baseline.json
Run "HAM savings" to see your token and cost savings.

User: ham savings

Agent:
  Before HAM: ~7,500 tokens/prompt
  After HAM:    ~450 tokens/prompt
  Savings:    7,050 tokens (94%)

  Monthly projection (1,500 prompts):
    Sonnet: ~$31.73 saved
    Opus:   ~$158.63 saved

name	hierarchical-agent-memory
description	Scoped CLAUDE.md memory system (HAM) that cuts context-token spend with directory-level context files, a decisions/patterns memory layer, and a savings dashboard. USE WHEN a multi-directory project keeps re-reading the same files and you want scoped agent memory.
cluster	ai-agents-meta
version	1.0.0
origin	antigravity-awesome-skills (MIT)
risk	safe
source	https://github.com/kromahlusenii-ops/ham
date_added	2026-02-27

name	hierarchical-agent-memory
description	Scoped CLAUDE.md memory system (HAM) that cuts context-token spend with directory-level context files, a decisions/patterns memory layer, and a savings dashboard. USE WHEN a multi-directory project keeps re-reading the same files and you want scoped agent memory.
cluster	ai-agents-meta
version	1.0.0
origin	antigravity-awesome-skills (MIT)
risk	safe
source	https://github.com/kromahlusenii-ops/ham
date_added	2026-02-27

hierarchical-agent-memory

Installationsoptionen

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