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Agent skill

Hierarchical Agent Memory

by sickn33 in sickn33/agentic-awesome-skills

Scoped CLAUDE.md memory system that reduces context token spend.

MITAuto-check passedAgent Workflows

Install Hierarchical Agent Memory

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill hierarchical-agent-memory -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills hierarchical-agent-memory --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/hierarchical-agent-memory .claude/skills/hierarchical-agent-memory && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
hierarchical-agent-memory
GitHub stars
47k
Used in
2 other repos
Token cost
~1.1k tokens
SKILL.md length
428 words
Files
1
Skills in repo
1,493
Repo updated
First seen
Licence
MIT

At a glance

Scoped CLAUDE.md memory system that reduces context token spend.

  • Works in 3 steps: Setup ("go ham") → Context Routing → Dashboard ("ham dashboard")
  • Tasks that involve Agent memory
  • SKILL.md covers When to Use This Skill, How It Works, Commands and Examples, plus 3 more sections
  • Calls go

What it does

Hierarchical Agent Memory is an agent skill from sickn33/agentic-awesome-skills. Scoped CLAUDE.md memory system that reduces context token spend. Creates directory-level context files, tracks savings via dashboard, and routes agents to the right sub-context.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Agent memory and Agent instruction files. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

  • Tasks that involve Agent memory
  • Tasks that involve Agent instruction files

Example prompts

  • “/hierarchical-agent-memory”

Requirements

  • Node.js

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Setup ("go ham")
  2. Context Routing
  3. Dashboard ("ham dashboard")

What it can do on your machine

Read from SKILL.md and the folder at commit 680176d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • go

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Hierarchical Agent Memory loads about 1.1k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 428 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~51
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit 680176d, republished under its MIT licence (© sickn33). 428 words, ~1,144 tokens.

Download SKILL.mdSave it as .claude/skills/hierarchical-agent-memory/SKILL.md (or your agent's skills folder).
name
hierarchical-agent-memory
description
Scoped CLAUDE.md memory system that reduces context token spend. Creates directory-level context files, tracks savings via dashboard, and routes agents to the right sub-context.
risk
safe
source
https://github.com/kromahlusenii-ops/ham
date_added
2026-02-27

Hierarchical Agent Memory (HAM)

Scoped memory system that gives AI coding agents a cheat sheet for each directory instead of re-reading your entire project every prompt. Root CLAUDE.md holds global context (~200 tokens), subdirectory CLAUDE.md files hold scoped context (~250 tokens each), and a .memory/ layer stores decisions, patterns, and an inbox for unconfirmed inferences.

When to Use This Skill

  • Use when you want to reduce input token costs across Claude Code sessions
  • Use when your project has 3+ directories and the agent keeps re-reading the same files
  • Use when you want directory-scoped context instead of one monolithic CLAUDE.md
  • Use when you want a dashboard to visualize token savings, session history, and context health
  • Use when setting up a new project and want structured agent memory from day one

How It Works

Step 1: Setup ("go ham")

Auto-detects your project platform and maturity, then generates the memory structure:

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
Step 2: Context Routing

The root CLAUDE.md includes a routing section that tells the agent exactly which sub-context to load:

markdown
## Context Routing

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

The agent reads root, then immediately loads the relevant subdirectory context — no guessing.

Step 3: Dashboard ("ham dashboard")

Launches a web dashboard at localhost:7777 that visualizes:

  • Token savings (HAM-on vs HAM-off sessions)
  • Daily token and cost trends
  • Per-directory session breakdown
  • Context file health (missing/stale/inherited CLAUDE.md coverage)
  • Routing compliance (how often the agent follows the routing map)
  • Carbon/energy estimates
Show full SKILL.md (202 more words)Show less

Commands

TriggerWhat it does
go hamSet up HAM — auto-detect platform, generate CLAUDE.md files
ham savingsShow token and cost savings report
ham dashboardLaunch the interactive web dashboard
ham auditHealth check on memory files
ham insightsGenerate actionable insights from session data
ham routeAdd/update Context Routing section in root CLAUDE.md
ham carbonShow energy and carbon efficiency data

Examples

Example 1: First-time setup
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.
Example 2: Checking 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

Best Practices

  • Keep root CLAUDE.md under 60 lines / 250 tokens
  • Keep subdirectory CLAUDE.md files under 75 lines each
  • Run ham audit every 2 weeks to catch stale or missing context files
  • Use ham route after adding new directories to keep routing current
  • Review .memory/inbox.md periodically — confirm or reject inferred items

Limitations

  • Token estimates use ~4 chars = 1 token approximation, not a real tokenizer
  • Baseline savings comparisons are estimates based on typical agent behavior
  • Dashboard requires Node.js 18+ and reads session data from ~/.claude/projects/
  • Context routing detection relies on CLAUDE.md read order in session JSONL files
  • Does not auto-update subdirectory CLAUDE.md content — you maintain those manually or via ham audit
  • Carbon estimates use regional grid averages, not real-time energy data
  • agent-memory-systems — general agent memory architecture patterns
  • agent-memory-mcp — MCP-based memory integration

© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/hierarchical-agent-memory of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit 680176d

Used in 2 other repositories

We found 7 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 9, 2026.

Compare with similar skills

Hierarchical Agent Memory next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Hierarchical Agent Memory compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Hierarchical Agent Memory this skillsickn33/agentic-awesome-skills47k2 repos~1.1kAutomated safety check: PassMIT
Neat-Freak Knowledge CloseoutKKKKhazix/khazix-skills21k—~1.9kAutomated safety check: PassMIT
SkillOpt Sleep Cyclemicrosoft/SkillOpt18k—~2.3kAutomated safety check: PassMIT
CLAUDE.md Improveranthropics/claude-plugins-official38k5 repos~1.5kAutomated safety check: PassApache-2.0
Harness Engineering10xChengTu/harness-engineering1021 repos~1kAutomated safety check: PassNone
Codebase Analyzerseverity1/claude-code-auto-memory159—~1.5kAutomated safety check: PassMIT

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Categories

Questions about Hierarchical Agent Memory

What does Hierarchical Agent Memory do?

Scoped CLAUDE.md memory system that reduces context token spend. Hierarchical Agent Memory is an agent skill from sickn33/agentic-awesome-skills.md memory system that reduces context token spend.

When should I use Hierarchical Agent Memory?

Hierarchical Agent Memory fits situations like: tasks that involve Agent memory; tasks that involve Agent instruction files.

How do I install Hierarchical Agent Memory in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill hierarchical-agent-memory -a claude-code`. Or copy the skill folder (skills/hierarchical-agent-memory in sickn33/agentic-awesome-skills) into .claude/skills/hierarchical-agent-memory in your project. Claude Code loads it when a task matches its description.

How do I install Hierarchical Agent Memory in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill hierarchical-agent-memory -a codex`. Or copy the skill folder (skills/hierarchical-agent-memory in sickn33/agentic-awesome-skills) into .agents/skills/hierarchical-agent-memory in your project. Codex loads it when a task matches its description.

Can I use Hierarchical Agent Memory in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill hierarchical-agent-memory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hierarchical-agent-memory, .gemini/skills/hierarchical-agent-memory, .github/skills/hierarchical-agent-memory and .opencode/skills/hierarchical-agent-memory in your project.

What does Hierarchical Agent Memory need to run?

Going by SKILL.md and its folder, Hierarchical Agent Memory needs the command-line tools its instructions call (go). Our summary lists: Node.js.

Does Hierarchical Agent Memory access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Hierarchical Agent Memory safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Hierarchical Agent Memory use?

Hierarchical Agent Memory is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hierarchical Agent Memory use?

About 1.1k tokens (SKILL.md is roughly 4.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Hierarchical Agent Memory?

Skills that share tags, products or a category with Hierarchical Agent Memory: Neat-Freak Knowledge Closeout (KKKKhazix/khazix-skills, 21k stars), SkillOpt Sleep Cycle (microsoft/SkillOpt, 18k stars), CLAUDE.md Improver (anthropics/claude-plugins-official, 38k stars) and Harness Engineering (10xChengTu/harness-engineering, 102 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hierarchical Agent Memory?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,379 GitHub stars. The repository holds 1,493 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.