# RIA-TV++ Methodology Pipeline: A 7-Stage Agent Workflow Explained

> Discover the 7-stage RIA-TV++ methodology pipeline for transforming text into actionable skill artifacts. Understand its end-to-end workflow for extraction, verification, structuring, and testing.

- Repository: [kangarooking/cangjie-skill](https://github.com/kangarooking/cangjie-skill)
- Tags: deep-dive
- Published: 2026-07-22

---

**The RIA-TV++ pipeline is a seven-stage agent-oriented workflow that transforms raw textual sources into actionable skill artefacts through progressive extraction, verification, structuring, and testing.**

The RIA-TV++ methodology, implemented in the `kangarooking/cangjie-skill` repository, provides a systematic approach to converting unstructured text—such as books, transcripts, and podcasts—into machine-readable **skill** files. This end-to-end pipeline enforces six strict invariants to ensure that the resulting artefacts are both agent-ready and human-usable.

## Stage 0: Structural Analysis (整书理解 – Adler)

The workflow begins with **Stage 0**, which applies Adler’s four-step reading methodology to produce a structural, interpretive, and critical analysis of the entire source work. This phase generates a high-level overview that guides subsequent extraction.

According to [`methodology/01-stage0-adler.md`](https://github.com/kangarooking/cangjie-skill/blob/main/methodology/01-stage0-adler.md), this stage outputs `books/<slug>/BOOK_OVERVIEW.md`, establishing the conceptual foundation before any chunking occurs.

## Stage 1: Parallel Extraction (并行提取)

**Stage 1** deploys five sub-agents running in parallel to segment the source into candidate units. Each unit is extracted with a minimal set of mandatory fields and stored as raw candidates.

As documented in [`methodology/02-stage1-parallel-extract.md`](https://github.com/kangarooking/cangjie-skill/blob/main/methodology/02-stage1-parallel-extract.md), these extracts populate the `candidates/` folder, serving as the initial pool of raw material for the pipeline.

## Stage 1.5: Triple Verification

Between extraction and structuring lies **Stage 1.5**, a rigorous quality gate implementing three independent verification checks:

- **V1 (Cross-domain check)**: Validates applicability across different contexts
- **V2 (Predictive power)**: Assesses the unit’s ability to forecast outcomes  
- **V3 (Exclusivity)**: Ensures the unit is distinct and non-redundant

Only candidates passing all three checks proceed, with verification records saved as [`verified.md`](https://github.com/kangarooking/cangjie-skill/blob/main/verified.md) per unit (see [`methodology/03-stage1.5-triple-verify.md`](https://github.com/kangarooking/cangjie-skill/blob/main/methodology/03-stage1.5-triple-verify.md)).

## Stage 2: RIA++ Construction (RIA++ 构造)

**Stage 2** transforms verified units into the six-dimensional **RIA++** schema. Each dimension serves a specific purpose in making knowledge actionable:

| Dimension | Field | Purpose |
|-----------|-------|---------|
| **R** | Reading | Original quote or excerpt |
| **I** | Interpretation | Re-interpretation in accessible terms |
| **A1** | Past Application | Historical case or example |
| **A2** | Future Trigger | Activation condition for the skill |
| **E** | Execution | Concrete, actionable steps |
| **B** | Boundary | Limitations and scope constraints |

This stage produces individual [`SKILL.md`](https://github.com/kangarooking/cangjie-skill/blob/main/SKILL.md) files as defined in [`methodology/04-stage2-ria-plus.md`](https://github.com/kangarooking/cangjie-skill/blob/main/methodology/04-stage2-ria-plus.md).

```markdown

# Skill: 《xxx》中的时间管理框架

## R — Reading (原文)

> “时间管理的核心在于把大块任务拆解为可执行的微步骤……”

## I — Interpretation (自述)

将作者关于“把大块任务拆解为微步骤”的论述，重新表述为：先拆分任务，再分配时间块。

## A1 — Past Application (书中案例)

作者在第 3 章举例说明如何在项目启动阶段使用此框架来制定里程碑。

## A2 — Future Trigger ★

当用户在日历中看到“未完成的任务”时，触发该技能，提示立即拆分为子任务。

## E — Execution (可执行步骤)

1. 在待办列表中新建任务。  
2. 将任务拆分为不超过 30 分钟的子任务。  
3. 为每个子任务分配具体时间块。

## B — Boundary (边界)

不适用于需要持续关注的大型宏观目标，例如“提升个人品牌”。此类目标应交由更高层的规划技能处理。

```

## Stage 3: Zettelkasten Linking (链接 – Zettelkasten)

**Stage 3** atomizes the skills and establishes bidirectional links between related units, creating a navigable knowledge graph. This process generates an [`INDEX.md`](https://github.com/kangarooking/cangjie-skill/blob/main/INDEX.md) file that serves as the entry point for the skill set.

The atomization and linking rules are specified in [`methodology/05-stage3-zettelkasten.md`](https://github.com/kangarooking/cangjie-skill/blob/main/methodology/05-stage3-zettelkasten.md), enabling non-linear exploration of the extracted knowledge.

## Stage 4: Pressure Testing (压力测试)

**Stage 4** subjects the skills to automated validation. The system generates [`test-prompts.json`](https://github.com/kangarooking/cangjie-skill/blob/main/test-prompts.json) containing blind test scenarios, executes them against the skills, and marks pass/fail results.

If a skill fails testing, it returns to previous stages for revision. The testing protocol and prompt format are detailed in [`methodology/06-stage4-pressure-test.md`](https://github.com/kangarooking/cangjie-skill/blob/main/methodology/06-stage4-pressure-test.md).

```json
{
  "skill_id": "time-management-framework",
  "prompt": "User wants to schedule a new project. How should they apply the skill?",
  "expected_output": [
    "Create a task entry",
    "Break it into ≤30‑minute subtasks",
    "Assign each subtask to a specific time block"
  ]
}

```

## Stage 5: Delivery (交付)

The final **Stage 5** packages the validated skills into a reader-friendly [`DIGEST.md`](https://github.com/kangarooking/cangjie-skill/blob/main/DIGEST.md) and installs the artefacts into the host `skills/` directory. This makes the knowledge immediately available for consumption by downstream agents such as `darwin-skill`.

The delivery specifications reside in [`methodology/07-stage5-deliver.md`](https://github.com/kangarooking/cangjie-skill/blob/main/methodology/07-stage5-deliver.md).

## Pipeline Invariants

The RIA-TV++ methodology enforces **six invariants** (documented in [`methodology/00-overview.md`](https://github.com/kangarooking/cangjie-skill/blob/main/methodology/00-overview.md)) that govern every stage:

- **Atomicity**: Each skill represents a single, indivisible unit of knowledge
- **Traceability**: Every artefact links back to its source material
- **Verifiability**: All units must pass objective quality checks
- **Evolvability**: Skills can be updated as source material or requirements change
- **User Participation**: Human oversight remains integral to the process
- **Deliverability**: Final outputs must be immediately usable by target agents

## Summary

- The RIA-TV++ pipeline consists of **seven sequential stages** (0 through 5, including 1.5) that progressively refine raw text into structured skills.
- **Stage 0** creates structural overviews using Adler’s methodology, while **Stage 1** extracts parallel candidates and **Stage 1.5** applies triple verification.
- **Stage 2** structures verified content into the six-field RIA++ schema (R, I, A1, A2, E, B) producing [`SKILL.md`](https://github.com/kangarooking/cangjie-skill/blob/main/SKILL.md) files.
- **Stage 3** builds Zettelkasten-style knowledge graphs with [`INDEX.md`](https://github.com/kangarooking/cangjie-skill/blob/main/INDEX.md), and **Stage 4** validates through automated [`test-prompts.json`](https://github.com/kangarooking/cangjie-skill/blob/main/test-prompts.json) scenarios.
- **Six invariants** (atomicity, traceability, verifiability, evolvability, user participation, deliverability) ensure the output is both agent-ready and human-usable according to the `kangarooking/cangjie-skill` implementation.

## Frequently Asked Questions

### What is the RIA++ six-field schema used in Stage 2?

The RIA++ schema is a structured format that transforms raw excerpts into actionable skills. It comprises six dimensions: **R** (Reading) for the original quote, **I** (Interpretation) for rephrasing, **A1** (Past Application) for historical examples, **A2** (Future Trigger) for activation conditions, **E** (Execution) for concrete steps, and **B** (Boundary) for scope limitations. This structure ensures each skill is immediately applicable and contextually bounded.

### How does the triple verification in Stage 1.5 ensure quality?

Stage 1.5 implements three independent checks defined in [`methodology/03-stage1.5-triple-verify.md`](https://github.com/kangarooking/cangjie-skill/blob/main/methodology/03-stage1.5-triple-verify.md): V1 validates cross-domain applicability, V2 assesses predictive power, and V3 confirms exclusivity against existing units. A candidate must pass all three verifications to proceed to Stage 2, effectively filtering out redundant or weakly supported content before resource-intensive structuring occurs.

### What files are generated by the end of the RIA-TV++ pipeline?

The pipeline produces several concrete artefacts: [`BOOK_OVERVIEW.md`](https://github.com/kangarooking/cangjie-skill/blob/main/BOOK_OVERVIEW.md) from Stage 0, `candidates/` directories from Stage 1, [`verified.md`](https://github.com/kangarooking/cangjie-skill/blob/main/verified.md) files from Stage 1.5, individual [`SKILL.md`](https://github.com/kangarooking/cangjie-skill/blob/main/SKILL.md) files from Stage 2, an [`INDEX.md`](https://github.com/kangarooking/cangjie-skill/blob/main/INDEX.md) knowledge graph from Stage 3, [`test-prompts.json`](https://github.com/kangarooking/cangjie-skill/blob/main/test-prompts.json) from Stage 4, and finally [`DIGEST.md`](https://github.com/kangarooking/cangjie-skill/blob/main/DIGEST.md) with installed skills in Stage 5.

### How does Stage 4 pressure testing work?

Stage 4 generates automated test prompts stored in [`test-prompts.json`](https://github.com/kangarooking/cangjie-skill/blob/main/test-prompts.json) that simulate real-world usage scenarios. Each skill undergoes blind testing against these prompts, with results marked pass or fail. Failed skills return to earlier stages for revision, creating a feedback loop that ensures only validated, robust skills reach final delivery.