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/smart-ai-memory/attune-ai/code-qualitynpx skills add Smart-AI-Memory/attune-ai --skill code-qualitygit clone --depth 1 https://github.com/Smart-AI-Memory/attune-aiWhat 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 | $0.00036 | $0.00610 |
| Opus 5 | $0.00018 | $0.00305 |
| Sonnet 5 | $0.00007 | $0.00122 |
| Haiku 4.5 | $0.00004 | $0.00061 |
Grade A, and why
code-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 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Quality
IMPORTANT: Start your response with a context preamble.
Call help_lookup(topic="code-quality", mode="preamble") and
display the returned preamble text as a blockquote. Then
tell the user they can say "tell me more" for a step-by-step
guide, or answer the scoping questions below to proceed.
If the MCP call fails, fall back to:
Code Quality — Reviews your code for style issues, likely bugs, and structural problems in one pass.
Scoping
Before running, ask:
- Scope: "Which files or directory should I review?"
- Depth: "Quick scan, thorough, or deep review?"
- Quick: code_review only
- Thorough: code_review + bug_predict combined
- Deep: deep_review (security + quality + test gaps)
Execution
Quick scan:
code_review(path="<user-specified path>")
Thorough analysis:
code_review(path="<user-specified path>")
bug_predict(path="<user-specified path>")
Merge and deduplicate results from both tools.
Deep review (multi-pass: security, quality, test gaps):
deep_review(path="<user-specified path>")
Output Format
Prefer the rich panel. If the tool response includes panel_html,
pass it to mcp__visualize__show_widget — the universal report panel
(title, score, findings/category sections; from
attune.workflows.report_panel). It shows an explicit "did not
complete" state on failure, never a false "clean". Fall back to the
markdown below when the widget surface is unavailable.
## Code Quality Report
**Health:** X/100 | **Files:** Y | **Issues:** Z
### Issues by Category
| Category | Count | Severity |
|----------|-------|----------|
| Style | X | Low |
| Correctness | Y | High |
| Security | Z | Critical |
| Predicted Bugs | W | Medium |
### Details
| File | Line | Issue | Source |
|------|------|-------|--------|
### Predicted Bug Risks
| File | Pattern | Confidence |
|------|---------|------------|
Help
After presenting results, call:
help_lookup(topic="code-quality", mode="workflow_help")
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 · 100 lines · 36 tokens per session scan A 1a37ab6872e8
code-quality is a skill published in the GitHub repository Smart-AI-Memory/attune-ai (10 stars, last pushed 3d ago), licensed Apache-2.0. It adds 36 tokens to every session and 610 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.
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