by KimGLee
Governance standard and reference toolset for LLM-maintained knowledge corpora
# Add to your Claude Code skills
git clone https://github.com/KimGLee/CambiumLast scanned: 8/20/2026
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"issues": [],
"status": "PASSED",
"scannedAt": "2026-08-20T04:35:28.794Z",
"npmAuditRan": true,
"pipAuditRan": true,
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}Cambium is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by KimGLee. Governance standard and reference toolset for LLM-maintained knowledge corpora. It has 342 GitHub stars.
Yes. Cambium passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/KimGLee/Cambium" and add it to your Claude Code skills directory (see the Installation section above).
Cambium is primarily written in Python. It is open-source under KimGLee on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh Cambium against similar tools.
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English | 简体中文
Cambium is a governance standard and reference toolset for knowledge repositories maintained with LLM agents.
It helps an operator answer five practical questions:
Cambium is not a knowledge base, a RAG engine, an agent scheduler, or a default domain policy. It governs work; it does not supply the corpus or decide its meaning.
effective governance
= Cambium kernel
+ exactly one selected profile
+ adopter-owned runtime state
The diagram shows how these layers connect to runtime routes, deterministic tools, and agent execution contexts.

| Layer | What it owns |
|---|---|
kernel/ |
Cross-domain governance semantics, invariants, state meanings, and extension points |
Card/ |
Curated, non-authoritative flight checklists for an already selected task route or phase |
Read Set/ |
Machine-resolvable declarations of what canonical material an already selected route or phase must load |
| Selected profile | One repository's scope, language, architecture, sources, priorities, roles, scans, and allowed extensions |
.cambium/ |
The adopter's current governance identity, task state, Queue, plans, deltas, receipts, and recovery evidence |
Tools/ |
Stable public commands and Area/Domain implementations for deterministic checks, controlled writes, schemas, and generated projections |
The kernel is normative. A profile can fill or tighten an extension point, but cannot disable a kernel rule. Tools execute declared rules; they do not make the final semantic judgment.
Cards are short, curated checklists, not routes or a second copy of the standard. Read Sets own the static loading boundary. When a Card is insufficient or disputed, its read-back hook resolves through the paired Read Set to the canonical owner.
This repository is intentionally uninstantiated. It contains one candidate Profile template and non-authoritative examples, but selects no adopter profile and creates no fabricated task state.
Cambium currently provides:
The generated MCP surface exposes both leaf calls and the bounded Runner. The Runner is not a scheduler or governance engine: it derives one identity-bound next action from current runtime state, invokes only registered capabilities, reads the result back, and stops at every semantic boundary. Each underlying Tool still decides whether its operation is valid and whether its evidence counts. For every active typed path, the transport retains the admitted file or parent-directory descriptor through subprocess consumption; an unsupported platform fails server initialization instead of claiming this assurance.
Cambium does not currently bundle:
These boundaries are intentional. A host may add capabilities, but it must not claim evidence for a capability it cannot prove. See ROADMAP.md for the delivery order.
Long-running work uses three state objects with different owners:
| State object | What it answers |
|---|---|
| Coverage Ledger | Which knowledge objects exist, what disposition they have, and which batch currently owns unfinished work? |
| Required Queue | Which batches exist, what are their manifests and dependencies, and what lifecycle state is each batch in? |
| Progress Ledger | What is the task contract, whole-task state, checkpoint, Standards identity, and accepted Queue fingerprint? |
They must agree, but they are not interchangeable task lists.
The adopter-owned namespace contains six lifecycle classes:
.cambium/
├── <canonical current state>
├── <bound operational inputs>
├── <evidence and history>
├── <recovery state>
├── <transient workspace>
└── <derived projections>
Do not edit canonical state by hand. Use the owning writer so revisions, hashes, receipts, and recovery evidence move together. Tools/execution/task_runtime/runtime_paths.py is the single machine owner of the current physical path spellings and object classifications; this README does not maintain a second directory contract.
Adoption creates and approves one profile for one repository. Copying a template or example does not select it.
Run the authoring workflow from a Cambium source checkout after the Agent-driven Host preparation. With terminal access and installation authorization, the Agent prepares and verifies the required toolchain; users do not choose dependency versions or fill in local paths. The user supplies and confirms repository decisions, without manually copying template files or writing TOML.
python3 Tools/scaffold_profile.py . --profile-id my-profile
python3 Tools/scaffold_profile.py . --profile-id my-profile --apply
The first command is a dry run. The second creates profiles/my-profile/profile.toml with the confirmed identity and empty slots, copies only the declared supporting files, and refuses to overwrite an existing candidate. It makes no policy choice and performs no adoption.
The assisting agent uses profiles/interview.yaml to discuss the repository's needs and Tools/profile_candidate.py to read, preview, edit, and render the candidate. User answers live once in profile.toml; independently referenced policy bodies retain their own owner. profiles/README.md describes the exact workflow and snapshot preconditions.
The Kernel owns slot meaning and legal values through K00/19 and domain-owned contracts. Tools own TOML encoding—including the root version, slots packaging, and draft-validation entry point—plus file layout, evaluation, and presentation. Existing domain YAML contracts remain sole owners where other consumers need them; their CUE projections are generated and checked, not parallel handwritten rules.
python3 Tools/profile_onboarding_status.py . --profile-id my-profile --json
python3 Tools/check_profile.py profiles/my-profile
Unanswered draft fields remain unanswered: omission is not agreement to disable an option or inherit a default. Existing legal defaults still apply where the completed contract permits them, but do not prove user confirmation. Mechanical validity, user confirmation, and adoption are separate; a rendered view or successful check never selects the Profile.
Prepare a plan from Tools/schemas/profile_adoption_plan.template.yaml, then dry-run and apply it:
python3 Tools/apply_profile_adoption.py . --plan <plan>.yaml \
--upstream-root <local-cambium-repository> --upstream-ref <git-ref>
python3 Tools/apply_profile_adoption.py . --plan <plan>.yaml \
--upstream-root <local-cambium-repository> --upstream-ref <git-ref> --apply
The transaction resolves the upstream ref to its full Git commit SHA and records that SHA as the sole Standards identity in upstream_revision_id. It binds the selected Profile and resulting adopter-owned contracts/evidence, and restores the previous control plane if any step fails. It never restamps or rewrites the adopter's upstream Card bytes. Adoption remains an explicit CLI maintenance operation: its external upstream repository i