Semantic layer for AI work · Apache-2.0 open source

Your team's playbook,
as a file the agent
actually executes

Prompts are read. Playbooks are executed. ContextJemo turns the way your team actually works into declarative files — AET tactics and kernel MD — that agents run, humans review, and git tracks. Cheap models become enough, because the structure carries the intelligence.

#CTX-001 One paper, one demo — turn a playbook into a working demo, instantly.
tactics/saas-pricing-monitor.aet.yaml
# A real tactic — steps are prompts, not code
schema_version: "0.2"
aet:
  id: saas-pricing-monitor
  version: 0.1.0
  steps:
    - id: s2
      name: 对比历史快照,检测定价结构变化
      instruction: >
        读取最新两个快照文件,逐一 diff…
      agent_requirements: [data-processing, analysis]
      depends_on: [s1]
      checkpoint:
        success_criteria: >
          diff 报告生成;changed_vendors 为空时标记"无变化"
AET · Agent Execute Tactics #AET-2.2
01 · The semantic layer

Three properties that make
playbooks into assets

01 / DEPOSITED

Semantic deposits

A tactic is a file, not a chat log. It lands in git, diffs like code, rolls back like code. A teammate can read what your agent was told to do — and why — without asking you.

#CHARTER-03.7
02 / REPLICABLE

Semantics replicate

One tactic, many agents. The same declarative file drives different models and different platforms. When you improve the playbook, every consumer inherits the fix — the improvement is not re-explained.

#BRIEF-1.3
03 / AI-IZED

The layer becomes AI

The semantic layer is not static documentation. Agents read it, execute against it, and write back to it: update_kernel evolves the kernel; cross-model verification gates the result. The layer improves because it is used, not because someone maintains a wiki.

#SPEC-1.0
declarative git-diffable verifiable self-evolving model-agnostic
02 · The files

Two artifacts.
Both plain text.

Everything in ContextJemo is a prompt — at three levels of structure. The kernel holds what must never change. The AET tactic holds what to do. The prompt template holds the smallest reusable unit.

Kernel · MD

Values & red lines

≤ 90 lines, hard budget. Axioms, self-cognition, bottom lines. A validator rejects it if it overruns — attention is a scarce resource, and restraint is a capability.

#CHARTER-03.3
AET · YAML

Steps & checkpoints

1–20 steps. Each step is a natural-language instruction with a machine-checkable success criterion. You declare what "done" means; the runtime decides how to get there.

#SPEC-2.1
kernel.md — five sections, ≤90 lines
### 四、红线规则(Bottom Line)

| 红线 | 触发动作 |
|------|---------|
| R1:无来源结论 | 结论不写入报告,改为「待核」标注 |
| R2:营销内容当事实 | 降级为「参考」,注明来源性质 |
| R3:超出知识截止日期 | 标注「数据可能过时」 |
| R4:单一来源支撑关键结论 | 强制要求第二来源印证 |
| R5:预算超支(>80%)| 停止深度检索
Real kernel — researcher-kernel.md #KERNEL-R1..R5
03 · The position

Black box makes you believe it.
Declarative makes you see it.

Mainstream agent orchestration is a black box: you hand over a task, and how it scheduled, how many tokens it burned, what each step produced — none of it is visible. ContextJemo takes the opposite road.

DimensionBlack-box agent orchestrationContextJemo declarative
Scheduling logicHidden in the engine, invisibleAET YAML, in plain sight — you define who and in what order
Each step's outputInvisibleVisible and costed, per step
Where experience accumulatesScattered across chat logsIn git — diffable, shareable, compounding
ControlHanded to the engineKept by you — edit the YAML, you edit the behaviour
IterationWaiting on a vendor releaseYours — change one line, run once, see the effect
When it breaksYou don't know which step diedMachine-judged checkpoints point straight at it
#VALUE-02 Predictability is the precondition for an asset to be worth anything.
04 · The lifecycle

Say → make → try → use → grow

One Paper: a playbook's full life, from a sentence of intent to an asset that compounds. The demo is not a throwaway — it is the fuel the asset is refined with.

01

Say

Describe the outcome in one sentence. No interrogation, no three-question intake.

02

Make

The co-creation brain drafts the tactic immediately. Open questions are marked inline, not asked back.

03

Try

Rehearsal with visible outputs and visible cost. Missing inputs are labelled honestly, never invented.

04

Use

The tactic lands in the library as YAML — versioned, shareable, runnable by any agent.

05

Grow

Run data and human confirmations feed back. The asset sharpens with every confirmed run.

#CHARTER-04 Confirmation is the asset: what, on what evidence, what was decided, what happened, who signed.
05 · Open source

Files first.
Platform second.

The repository is Apache-2.0. The formats are documented. AET spec v1.0 is frozen — and the triggers for independently open-sourcing it are written down, not aspirational.

#SCOPE-OPEN This repository is prototype-grade. A working prototype is not traction.
quick start
# Node ≥ 22
git clone https://github.com/xingkongxia1988/contextjemo
cd contextjemo && pnpm install

# conversational mode — just say what you want
npm run chat

# › /run   → s1 ✓ 13.5s   s2 ✓ 7.5s
# › /save  → ✓ saved ./tactics/your-tactic.aet.yaml
No API key required to try #README-QS
Start here

Bring one real workflow.
We'll show you its ledger.

No slides, no discovery workshop. Bring a task your team already does by hand — we'll turn it into a tactic and show you what it costs, step by step.