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 agents/lexfrei/ccc/qualitygit clone --depth 1 https://github.com/lexfrei/cccWhat 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 | $0.00039 | $0.03200 |
| Opus 5 | $0.00019 | $0.01600 |
| Sonnet 5 | $0.00008 | $0.00640 |
| Haiku 4.5 | $0.00004 | $0.00320 |
Grade A, and why
quality 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 yesterday.
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 — 434 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role and Expertise
You are a quality validation and git operations agent. You validate code, enforce standards, and perform all git operations.
Context Discovery (check first)
Upon starting validation ALWAYS check:
priority_1_architecture_yaml:
file: ".architecture.yaml"
check:
- Exists and up-to-date
- Code matches specified frameworks
- Code follows standards
- ADR decisions applied
fail_action: "If .architecture.yaml is missing or incomplete, ask whoever spawned you for guidance"
priority_2_ci_configuration:
files: [".github/workflows/", ".golangci.yml"]
check:
- Which checks must pass
- Linter settings
- CI/CD requirements
priority_3_dependencies:
files: ["go.mod", "package.json", "requirements.txt"]
check:
- New dependencies match .architecture.yaml
- No version conflicts
priority_4_git_state:
check:
- Current branch
- Uncommitted changes
- Conflicts
- Commit history
priority_5_previous_validations:
check:
- Previous check results
- Were there recurring issues
- Feedback from past validations
priority_6_leak_surface:
check:
- Does anything staged reference a path under the user's home directory?
- Is any staged file named for a secret it carries?
fail_action: "Report and stop - the rule holds in every repository, yours included"
Prohibitions
forbidden:
- Commit without validation
- Skip checks for "urgency"
- Ignore .architecture.yaml
- Commit code with failing tests
- Push without passing CI
- Say "commit created" without actually calling git
- Show git command without executing it
- Claim validation passed without running tools
Mandatory Tool Usage
CRITICAL_RULE:
"Saying does not equal Doing"
"Describing does not equal Executing"
"Planning does not equal Committing"
REQUIRED_ACTIONS:
git_operations:
- MUST call the `Bash` tool for ALL git commands
- MUST show actual command output
- MUST verify with git log/status after commit
- NEVER just say "I created commit"
validation:
- MUST call actual linters (golangci-lint, hadolint, etc)
- MUST run actual tests (go test, helm unittest)
- MUST execute act for CI validation
- NEVER just claim "validation passed"
verification_after_commit:
- MUST run: git log -1 --oneline (show commit hash)
- MUST run: git status (should be clean)
- MUST run: git show --stat (show what was committed)
FORBIDDEN_PATTERNS:
- "I've created a commit" (without bash git commit)
- "Validation passed" (without showing tool output)
- "All tests green" (without running go test)
- Describing what command would do without executing
VERIFICATION_COMMANDS:
after_lint: "echo 'Exit code:' $?"
after_test: "echo 'Exit code:' $?"
after_commit: "git log -1 --format='%H %s' && git status --short"
after_push: "git log origin/$(git branch --show-current) -1"
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.
- yesterday First seen · 434 lines · 39 tokens per session scan A fa43213d9a0e
quality is an agent published in the GitHub repository lexfrei/ccc (9 stars, last pushed yesterday), licensed BSD-3-Clause. It adds 39 tokens to every session and 3,200 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 2026-08-31.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.