CCG is a command-line workflow engine that coordinates Claude, Codex, Gemini, and other models as specialized collaborators on coding tasks. It is used to analyze requests, choose a strategy, delegate work to model-specific roles, and combine their results. The catalogue entries provide the skills, commands, agents, and plugin that implement this workflow.
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 skills add fengshao1227/ccg-workflow --skill teach-impeccablegit clone --depth 1 https://github.com/fengshao1227/ccg-workflowWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/fengshao1227/ccg-workflow/teach-impeccable)<a href="https://agentmods.dev/skills/fengshao1227/ccg-workflow/teach-impeccable"><img src="https://agentmods.dev/badge/skills/fengshao1227/ccg-workflow/teach-impeccable/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/fengshao1227/ccg-workflow/teach-impeccable"><img src="https://agentmods.dev/badge/skills/fengshao1227/ccg-workflow/teach-impeccable.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What 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 5.1 | $0.00033 | $0.00597 |
| Opus 5 | $0.00016 | $0.00298 |
| Sonnet 5 | $0.00007 | $0.00119 |
| Haiku 4.5 | $0.00003 | $0.00060 |
Grade A, and why
teach-impeccable 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 6d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- teach-impeccable — 100% identical, 2 lines differ
- teach-impeccable — 100% identical, 2 lines differ
- teach-impeccable — 91% identical, 9 lines differ
- design-brief — 91% identical, 15 lines differ
- teach-impeccable — 91% identical, 9 lines differ
- teach-impeccable — 91% identical, 9 lines differ
- teach-impeccable — 91% identical, 9 lines differ
- teach-impeccable — 91% identical, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gather design context for this project, then persist it for all future sessions.
Step 1: Explore the Codebase
Before asking questions, thoroughly scan the project to discover what you can:
- README and docs: Project purpose, target audience, any stated goals
- Package.json / config files: Tech stack, dependencies, existing design libraries
- Existing components: Current design patterns, spacing, typography in use
- Brand assets: Logos, favicons, color values already defined
- Design tokens / CSS variables: Existing color palettes, font stacks, spacing scales
- Any style guides or brand documentation
Note what you've learned and what remains unclear.
Step 2: Ask UX-Focused Questions
Ask the user using AskUserQuestion. Focus only on what you couldn't infer from the codebase:
Users & Purpose
- Who uses this? What's their context when using it?
- What job are they trying to get done?
- What emotions should the interface evoke? (confidence, delight, calm, urgency, etc.)
Brand & Personality
- How would you describe the brand personality in 3 words?
- Any reference sites or apps that capture the right feel? What specifically about them?
- What should this explicitly NOT look like? Any anti-references?
Aesthetic Preferences
- Any strong preferences for visual direction? (minimal, bold, elegant, playful, technical, organic, etc.)
- Light mode, dark mode, or both?
- Any colors that must be used or avoided?
Accessibility & Inclusion
- Specific accessibility requirements? (WCAG level, known user needs)
- Considerations for reduced motion, color blindness, or other accommodations?
Skip questions where the answer is already clear from the codebase exploration.
Step 3: Write Design Context
Synthesize your findings and the user's answers into a ## Design Context section:
## Design Context
### Users
[Who they are, their context, the job to be done]
### Brand Personality
[Voice, tone, 3-word personality, emotional goals]
### Aesthetic Direction
[Visual tone, references, anti-references, theme]
### Design Principles
[3-5 principles derived from the conversation that should guide all design decisions]
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.
- 6d ago First seen · 72 lines · 33 tokens per session scan A 72e2bf689e5e
teach-impeccable is a skill published in the GitHub repository fengshao1227/ccg-workflow (5,881 stars, last pushed 7d ago), licensed MIT. It adds 33 tokens to every session and 597 once invoked, about $0.0002 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 2026-09-03.
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