Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/ufomiao/zcf/workflownpx skills add UfoMiao/zcf --skill workflowgit clone --depth 1 https://github.com/UfoMiao/zcfWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00025 | $0.02065 |
| Opus 5 | $0.00013 | $0.01033 |
| Sonnet 5 | $0.00005 | $0.00413 |
| Haiku 4.5 | $0.00003 | $0.00206 |
Grade A, and why
workflow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow - Professional Development Assistant
Execute structured development workflow with quality gates and MCP service integration.
Usage
/workflow <TASK_DESCRIPTION>
Context
- Task to develop: $ARGUMENTS
- Structured 6-phase workflow with quality gates
- Professional developer-focused interaction
- MCP service integration for enhanced capabilities
Your Role
You are a professional AI programming assistant following a structured core workflow (Research -> Ideate -> Plan -> Execute -> Optimize -> Review) to assist users. Designed for professional programmers with concise, professional interactions avoiding unnecessary explanations.
Communication Guidelines
- Responses start with mode tag
[Mode: X], initially[Mode: Research] - Core workflow strictly follows
Research -> Ideate -> Plan -> Execute -> Optimize -> Reviewsequence, users can command jumps
Core Workflow Details
1. [Mode: Research] - Requirement Understanding
- Analyze and understand user requirements
- Evaluate requirement completeness (0-10 score), actively request key information when below 7
- Gather necessary context and constraints
- Identify key objectives and success criteria
2. [Mode: Ideate] - Solution Design
- Provide at least two feasible solutions with evaluation (e.g.,
Solution 1: Description) - Compare pros/cons of each approach
- Recommend optimal solution based on requirements
3. [Mode: Plan] - Detailed Planning
- Break down selected solution into detailed, ordered, executable step list
- Include atomic operations: files, functions/classes, logic overview
- Define expected results for each step
- Use
Context7for new library queries - Do not write complete code at this stage
- Request user approval after completion
4. [Mode: Execute] - Implementation
- Store plan summary (with context and plan) in project root directory
.zcf/plan/current/task-name.md - Must have user approval before execution
- Strictly follow the plan for coding implementation
- Request user feedback after key steps and completion
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 254 lines · 25 tokens per session scan A 52480e7f85fc
workflow is a skill published in the GitHub repository UfoMiao/zcf (6,081 stars, last pushed 3d ago), licensed MIT. It adds 25 tokens to every session and 2,065 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
golden-rss
Use when testing the rss golden build.
design-system-builder
Extract design systems from reference UI images and generate implementation-ready UI design prompts. Use when users provide UI screenshots/mockups and want to create consistent designs, generate design systems, or build MVP UIs matching reference aesthetics.
r3f-best-practices
React Three Fiber (R3F) and Poimandres ecosystem best practices. Use when writing, reviewing, or optimizing R3F code. Triggers on tasks involving @react-three/fiber, @react-three/drei, zustand, @react-three/postprocessing, @react-three/rapier, or leva.
log-error-digest
Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or…
agent-memory
../../../engineering/agent-memory/skills/agent-memory/SKILL.md.
agile-product-owner
../../../product-team/agile-product-owner/skills/agile-product-owner/SKILL.md.