deepagent-toolchain-plan

DeepAgent-style tool discovery for VCO: propose a minimal skill/tool chain (with verification points) and reduce confirm_required friction.

Best use case

deepagent-toolchain-plan is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

DeepAgent-style tool discovery for VCO: propose a minimal skill/tool chain (with verification points) and reduce confirm_required friction.

Teams using deepagent-toolchain-plan should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/deepagent-toolchain-plan/SKILL.md --create-dirs "https://raw.githubusercontent.com/foryourhealth111-pixel/Vibe-Skills/main/bundled/skills/deepagent-toolchain-plan/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/deepagent-toolchain-plan/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How deepagent-toolchain-plan Compares

Feature / Agentdeepagent-toolchain-planStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

DeepAgent-style tool discovery for VCO: propose a minimal skill/tool chain (with verification points) and reduce confirm_required friction.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# DeepAgent Toolchain Plan (VCO)

## When to use

Use this skill when:

- VCO router returns `route_mode=confirm_required` and you want a **better, evidence-backed choice**
- The task spans multiple domains/tools and you need a **skill chain**, not a single skill
- The user asks “用什么工具/技能最好?” / “怎么编排这套技能?”
- The conversation is long or messy and you need to **re-anchor** on goal → toolchain → verification

## Non-goals (avoid redundancy)

- This is **not** a replacement for VCO routing. It is an *augmentation* that proposes a chain.
- This is **not** GitNexus. For code dependency/impact, use GitNexus overlays.
- This does **not** introduce long-term episodic memory (VCO governance disables it).

## Runtime (Upstream vendoring)

DeepAgent upstream is vendored for reference / optional advanced runs:

- `C:\Users\羽裳\.codex\_external\ruc-nlpir\DeepAgent\`

VCO-managed runtime config and self-check scripts (no secrets stored/printed):

- `C:\Users\羽裳\.codex\skills\vibe\config\ruc-nlpir-runtime.json`
- `pwsh C:\Users\羽裳\.codex\skills\vibe\scripts\ruc-nlpir\preflight.ps1`

## Core output (must)

Return a toolchain with:

1. **Goal + deliverable** (1–2 lines)
2. **Chain steps** (3–8 steps, each: skill/tool + why + expected artifact)
3. **Verification points** (at least 1 falsifiable check)
4. **Fallbacks** (what to do if a tool is unavailable)

## Workflow

### Step 1: Capture the task in a contract

- Goal (one sentence)
- Deliverable (code / plan / report / dataset / etc.)
- Constraints (time, no heavy deps, offline-only, etc.)

### Step 2: Ask VCO router for a white-box view (recommended)

Run the router script in probe mode to get candidates + overlays in a machine-readable form:

- `pwsh C:\Users\羽裳\.codex\skills\vibe\scripts\router\resolve-pack-route.ps1 -Prompt "<PROMPT>" -Grade L -TaskType planning -Probe -ProbeLabel "toolchain" -ProbeOutputDir outputs/runtime/router-probes`

Then use the emitted `confirm_ui` + overlay advice to decide the chain.

### Step 3: Build a minimal chain (DeepAgent principle)

Prefer a chain that:

- Starts with **evidence acquisition** (local docs / web / code graph)
- Then **planning**
- Then **execution**
- Ends with **verification + review**

### Step 4: Guardrails

- If the chain requires web browsing, explicitly choose between:
  - `web.run` (fast structured browse)
  - `playwright` / `turix-cua` (dynamic/interactive)
- If the chain requires heavy model hosting (vLLM), provide a Lite alternative.

## Suggested chains (templates)

### A) “Research → report”

1. `webthinker-deep-research` (Lite) → `outputs/webthinker/.../report.md`
2. `flashrag-evidence` (local protocol checks) → citeable snippets
3. `code-reviewer` (if code changes) or `verification-quality-assurance` (if routing changes)

### B) “VCO enhancement work (config/skills)”

1. `flashrag-evidence` (locate existing policy/overlays)  
2. `writing-plans` (implementation plan with file paths + verify steps)
3. `verification-before-completion` (run check + router probe)

Related Skills

writing-plans

1174
from foryourhealth111-pixel/Vibe-Skills

Use when you have a spec or requirements for a multi-step task, before touching code

treatment-plans

1174
from foryourhealth111-pixel/Vibe-Skills

Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.

speckit-plan

1174
from foryourhealth111-pixel/Vibe-Skills

Generate technical implementation plans from feature specifications. Use after creating a spec to define architecture, tech stack, and implementation phases. Creates plan.md with detailed technical design.

planning-with-files

1174
from foryourhealth111-pixel/Vibe-Skills

Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.

deepagent-memory-fold

1174
from foryourhealth111-pixel/Vibe-Skills

DeepAgent-style memory folding for VCO sessions: compress long context into structured working/tool memory without using episodic-memory.

create-plan

1174
from foryourhealth111-pixel/Vibe-Skills

Create a concise plan. Use when a user explicitly asks for a plan related to a coding task.

zinc-database

1174
from foryourhealth111-pixel/Vibe-Skills

Access ZINC (230M+ purchasable compounds). Search by ZINC ID/SMILES, similarity searches, 3D-ready structures for docking, analog discovery, for virtual screening and drug discovery.

zarr-python

1174
from foryourhealth111-pixel/Vibe-Skills

Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.

yeet

1174
from foryourhealth111-pixel/Vibe-Skills

Use only when the user explicitly asks to stage, commit, push, and open a GitHub pull request in one flow using the GitHub CLI (`gh`).

xlsx

1174
from foryourhealth111-pixel/Vibe-Skills

Spreadsheet toolkit (.xlsx/.csv). Create/edit with formulas/formatting, analyze data, visualization, recalculate formulas, for spreadsheet processing and analysis.

xan

1174
from foryourhealth111-pixel/Vibe-Skills

High-performance CSV processing with xan CLI for large tabular datasets, streaming transformations, and low-memory pipelines.

writing-docs

1174
from foryourhealth111-pixel/Vibe-Skills

Guides for writing and editing Remotion documentation. Use when adding docs pages, editing MDX files in packages/docs, or writing documentation content.