J-Space Cognition Suite SV1

Simplified Chinese

J-Space is an inference-time workspace and control suite for complex reasoning, repository engineering, coordinated agents, and authorized security analysis. You install one skill, load relevant modules, and keep long-task decisions connected to durable evidence.

Its thirteen modules share one premise and one routing entry. Standard-library Python scripts persist state, reread actual source text, detect stale maps and evidence, and return blocking results when a required condition is missing. The host supplies tools and agents.

Quick start

You need a host that can load a local SKILL.md and retrieve its supporting files. Python 3.10+ is needed for executable controllers and validation; low/medium can use the documented prose fallback. No pip dependencies or background service are required.

1. Copy the complete j-space/ directory into your host's Skills directory. Obtain that directory from the host's own configuration; no universal location or invocation syntax applies to every host. Keep SKILL.md, modules/, references/, and scripts/ together; avoid an extra nested j-space/j-space/ directory. Copy LICENSE and THIRD_PARTY_NOTICES.md alongside the installed SKILL.md when distributing the standalone skill. Use an empty destination to avoid mixing installs.

2. Use Python 3.10 or later to verify the installed directory:

    <skill-root>/scripts/verify_suite.py
   

3. Reload the host if it discovers skills only at startup. Select j-space through its skill UI. Use $j-space or /j-space only if that host documents the syntax; otherwise ask it to read the installed SKILL.md explicitly. Confirm it can retrieve one routed module and execute the installed controller's --help if you need strict gates.

4. Give it the task and its acceptance conditions:

   Use j-space to modify this repository. Inspect the existing contracts, maintain a
   source-backed map, delegate independent work where useful, and verify the final behavior.
   

Replace `` with your available python, python3, or py -3 command. Resolve <skill-root> to the installed directory. Keep the task directory as the working directory, or pass --root TASK_DIRECTORY before a controller subcommand.

For a path with spaces in Bash:

python3 "/path with spaces/j-space/scripts/control.py" --root "/task directory" status

For a quoted interpreter path in PowerShell:

& "C:\Python313\python.exe" "C:\Skills\j-space\scripts\control.py" --root "D:\Task Directory" status

Run status after initializing the task. UTF-8 input supports English and Chinese task content; use the language requested by the user for deliverables. Run controllers in the target project's task directory, not the installed skill directory. Installing the files does not automatically register hooks, launch agents, or grant tool access.

Intended use. This suite is designed for real engineering and production-oriented projects with contracts, dependencies, verification, and recovery needs. It is not aimed at toy demonstrations such as “a pelican riding a bicycle.” Its suitability for serious work is a design focus, not a guarantee that any untested deployment is production-ready.

Operating levels

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