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TriCore

TriCore Architecture - A deterministic (Code-First) three-layer memory and cognitive framework designed for low-resource servers/Agents. It includes the unde...

MIT-0 · Free to use, modify, and redistribute. No attribution required.
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Purpose & Capability
The package implements a code-first memory manager (tools/memctl.py), cognitive-skill templates, and an installer — all consistent with a 'TriCore' memory/cognition framework. Requiring Python, adding memctl, and providing planning/React/self-evolution templates is proportional to the described purpose. However, the installer also injects system policy rules and overrides OpenClaw's compaction prompt (system-wide configuration), which is a stronger footprint than many memory helper skills would need.
Instruction Scope
SKILL.md and the included files explicitly instruct agents to forbid arbitrary file creation, route all persistence through memctl.py, run memctl.py lint for any automation, and use memory_search for retrieval. Those instructions align with the skill's goal (centralize memory), but they place strong constraints on normal agent behavior and tell the agent to read/migrate any existing MEMORY.md (migrate_legacy). The instructions do not request unexplained credentials or network exfiltration.
Install Mechanism
There is no remote download of code; install.sh copies files from the package into the workspace and runs local Python scripts. No external URLs, shorteners, or remote archives are fetched. That lowers supply-chain risk compared to fetching remote binaries. The script does call 'openclaw config set' (a system CLI) which is expected to configure OpenClaw but will fail if OpenClaw isn't present.
Credentials
The skill does not request environment variables, tokens, or credentials. It does, however, recommend (but not require) optional components like an 'agent-browser' and expects the agent to have exec/write/edit permissions to perform self-evolution — this is documented and consistent with the skill's self-modifying/evolution objectives.
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Persistence & Privilege
The installer injects a TriCore block into POLICY.md and overrides OpenClaw's pre-compaction memory flush prompt (openclaw config set). Those are persistent, system-wide changes that affect global behavior and other skills. The skill also provides a self-evolution template that uses default_api:edit/write (ability to modify code). While these are coherent with a 'memory OS' designer's goals, they grant broad, persistent influence over the runtime and tooling and could lock or interfere with other workflows.
What to consider before installing
This package is internally consistent: it implements a local memory engine (tools/memctl.py), templates for planning/ReAct/self-evolution, and an installer that enforces use of the engine by modifying POLICY.md and OpenClaw config. Before installing, consider: 1) Back up POLICY.md and MEMORY.md (install will move/rename a large MEMORY.md). 2) Review tools/memctl.py and install.sh yourself (they are local and do not fetch remote code). 3) Be aware install.sh will call 'openclaw config set' to override compaction behavior and inject a Linter policy — this is intrusive and affects other skills; test installation in an isolated workspace or sandbox first. 4) The self-evolution skill uses edit/write permissions (it can modify code); only enable it if you trust the skill and are prepared to review/monitor automated code changes. 5) If you are unsure, run the installer manually in a throwaway environment, inspect the created files in memory/ and policy changes, and verify you can revert them with uninstall.sh.

Like a lobster shell, security has layers — review code before you run it.

Current versionv1.0.1
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License

MIT-0
Free to use, modify, and redistribute. No attribution required.

SKILL.md

🤖 Agent Usage Guide (Read First)

If you are the current AI Agent and have just been asked to load, use, or analyze this skill:

  1. This is your fundamental operating system law. Your memory and state have been completely constrained under the TriCore architecture. You are STRICTLY FORBIDDEN from arbitrarily creating independent text files like task_plan.md or findings.md in the root directory!
  2. Your memory write operations must and can only be proxied by the command-line python3 tools/memctl.py (capture/work_upsert/kb_append). When reading history, you MUST use the native semantic retrieval tool memory_search to fetch fragments.
  3. Please use this manual as your base operating instructions. If instructed to configure Cron or write system automation scripts, you must call memctl.py lint to test the scheme's legality after writing the commands.

TriCore Architecture

The underlying infrastructure of "storage and computation decoupling" built for true autonomous Agents.

Traditional Agent skills often carry their own "memory baggage" (such as generating task_plan.md, reflection.md, or scattered learning notes in the project root), leading to context silos and storage chaos.

TriCore abandons the paradigm of arbitrarily reading and writing text based on LLMs, and instead adopts a Code-First deterministic state machine:

  1. Unified Engine: All memory additions, deletions, modifications, and queries must be routed through tools/memctl.py.
  2. Three-Layer Storage:
    • Brief (Layer 1): MEMORY.md (System-level micro-profile, storing only pointers and laws)
    • Living (Layer 2): memory/state/WORKING.md (Currently running task streams/lifecycle tracking)
    • Stable/Volatile (Layer 3): memory/kb/*.md (Accumulated knowledge base) & memory/daily/*.md (Temporary logs)
  3. Retrieval First: It is forbidden to directly pour huge files using the read tool; you must use semantic retrieval memory_search to fetch code snippets, greatly saving Tokens and protecting low-resource environments.
  4. Hard Constraints (Linting): Features a native memctl.py lint mechanism; any Cron or Skill changes that break the architecture will be intercepted and reported as errors by the Linter.
  5. System Compatibility (Compaction Hook): Automatically overrides OpenClaw's underlying pre-compaction memory flush prompt during installation, preventing HTTP 429 request burst death loops caused by unauthorized file writing attempts during Token compaction.

📦 Architectural Components

This skill package contains complete system components:

  1. tools/memctl.py: The core engine, containing subcommands like ensure, capture, work_upsert, kb_append, lint.
  2. install.sh: One-click installation script that automatically initializes directories and injects TriCore compliance policies into POLICY.md.
  3. cognitive-skills/: Three core cognitive skills refactored based on TriCore (as templates for your Agent to load):
    • planning-with-files.md: A PEP planning system that discards detached task lists.
    • react-agent.md: A ReAct loop based on persisting mental states to WORKING.md.
    • self-evolution.md: An evolution system that completely detaches memory management and focuses on "Code-level CI/CD".

🧩 Core Dependencies & Runtime Requirements

As an underlying cognitive foundation, TriCore itself and its embedded three major cognitive skills have the following dependencies on the host environment:

1. Hard Dependencies

  • OpenClaw (v2026+): Must support native memory_search and memory_get tools (this is the retrieval basis for completely deprecating reading large files).
  • Python 3.6+: Python 3 must be installed in the host environment (used to execute the tools/memctl.py state engine).
  • System Tools: bash, sed, grep (used for regular expression parsing by the Linter and Hooks).

2. Cognitive Skill Soft Dependencies

If you enable cognitive-skills/self-evolution.md (Self Code Evolution Skill), your Agent must have tentacles to explore outward, otherwise, it can only undergo "hallucinated self-evolution" in an internal infinite loop.

  • 🌟 agent-browser (Highly Recommended):
    • Function: Enables the Agent to truly read GitHub source code, official API documentation, and the latest papers.
    • Installation: You need to separately install OpenClaw's agent-browser skill, which provides WYSIWYG crawling and clicking capabilities based on a headless browser.
  • Search Tools (web_search / web_fetch):
    • Function: Acts as a lightweight fallback for the browser, used to quickly extract Markdown snippets from public web pages.
  • Runtime Modification Permissions (default_api:exec & default_api:write):
    • Function: The essence of the evolution skill is "modifying code"; if your Agent is running in a ReadOnly sandbox, evolution cannot occur.

🚀 Installation & Initialization (The 3-Step Setup)

In any completely new OpenClaw environment, executing the following command will deploy the TriCore architecture:

# Grant installation script permissions and execute
bash ./install.sh

install.sh executes in the following order:

Step 1: Core Engine Deployment

  1. Creates standard directories like memory/state/, memory/kb/, memory/daily/.
  2. Deploys the tools/memctl.py engine to the current environment.

Step 2: Force Legacy MEMORY Migration (Agent Action Required)

In a low-resource architecture, a massive MEMORY.md full of conversation history and diaries is extremely fatal. The script will automatically detect the current MEMORY.md:

  • If found to be too bloated (> 1500 bytes), it will be renamed and moved to memory/archive/legacy-MEMORY-<date>.md.
  • Then, a compliant minimalist MEMORY.md template will be rebuilt in the root directory.
  • Agent Note: At this time, you need to actively use read to read the legacy backup file, and call memctl.py to redistribute this legacy (facts into kb/facts, rules into kb/playbooks, logs into daily); it is STRICTLY FORBIDDEN to paste long texts intact back into the new MEMORY.md!

Step 3: System Global Linter Blockade Deployment

The script will inject a [CRITICAL: TriCore Compliance] top-priority defense line into the system's POLICY.md. Thereafter, all planning for disk-writing, state updating, and automated tasks executed by the Agent must all pass the memctl.py lint regex check, otherwise, they will be rejected in red text in the terminal.


📚 Core Command Cheat Sheet

In the Agent tool flow or internal sub-scripts, please strictly use the following API to access states:

1. Record temporary logs / session ledger (Volatile)

python3 tools/memctl.py capture "Tested API connectivity, successful."

2. Create / Update task tracking (Living State)

python3 tools/memctl.py work_upsert --task_id "T-API-01" --title "Fix API" --goal "Connect interface" --done_when "Returns 200"

3. Accumulate knowledge & experience (Stable KB)

python3 tools/memctl.py kb_append facts "This API only accepts JSON format."
python3 tools/memctl.py kb_append playbooks "When encountering an error in this module, check if Redis is started first."

4. Check script / Cron command compliance (Linter)

python3 tools/memctl.py lint "Command to execute or .md file path to check"
# Pass normally: Exit Code 0 (LINT PASS)
# Illegal write: Exit Code 1 (LINT ERROR)

Built with ❤️ for OpenClaw / Berton Han

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