Borrowing it
Nothing to install: this file belongs to Smart-AI-Memory/attune-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Smart-AI-Memory/attune-ai/main/.agents/skills/workflows/SKILL.mdgit clone --depth 1 https://github.com/Smart-AI-Memory/attune-aiWrote 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/smart-ai-memory/attune-ai/workflows)<a href="https://agentmods.dev/skills/smart-ai-memory/attune-ai/workflows"><img src="https://agentmods.dev/badge/skills/smart-ai-memory/attune-ai/workflows/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/smart-ai-memory/attune-ai/workflows"><img src="https://agentmods.dev/badge/skills/smart-ai-memory/attune-ai/workflows.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00007 | $0.00519 |
| Opus 5.5 | $0.00003 | $0.00208 |
| Sonnet 5.5 | $0.00001 | $0.00104 |
| Haiku 4.5 | $0.00001 | $0.00052 |
Grade A, and why
workflows 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 1mo 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
workflows
AI-powered analysis workflows for security, bugs, and performance.
Routes
| Subcommand | Action |
|---|---|
run security-audit |
Security vulnerability scan |
run bug-predict |
Bug prediction analysis |
run perf-audit |
Performance audit |
run code-review |
Code review workflow |
| list | List available workflows |
Usage
/workflows # Ask which workflow
/workflows run security-audit # Security audit
/workflows run bug-predict # Bug prediction
/workflows run perf-audit # Performance audit
/workflows list # List all workflows
Fast-Path Detection
When the user provides a workflow name AND a path,
skip AskUserQuestion and execute directly:
/workflows run security-audit ./src→ execute/workflows run bug-predict src/auth→ execute/workflows run security-audit→ ask for path/workflows→ ask which workflow
Rule: If both workflow and target are provided,
proceed to execution. If either is missing, use
AskUserQuestion.
Behavior
run security-audit
If a path argument was provided (e.g.,
/workflows run security-audit ./src), skip
AskUserQuestion and execute immediately.
Otherwise, use AskUserQuestion to scope:
- Which path?
src/, specific module, or full project?
Then run:
uv run attune workflow run security-audit --path <target>
run bug-predict
Use AskUserQuestion to scope:
- Which path to scan?
Then run:
uv run attune workflow run bug-predict --path <target>
run perf-audit
Use AskUserQuestion to scope:
- Which path to audit?
Then run:
uv run attune workflow run perf-audit --path <target>
run code-review
Use AskUserQuestion to scope:
- Which path or files to review?
- Focus area: quality, security, performance, or all?
Then run:
uv run attune workflow run code-review --path <target>
list
Run:
uv run attune workflow list
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.
- 1mo ago First seen · 110 lines · 7 tokens per session scan A b650f319b6aa
workflows is a skill published in the GitHub repository Smart-AI-Memory/attune-ai (10 stars, last pushed today), licensed Apache-2.0. It adds 7 tokens to every session and 519 once invoked, about $0.0000 per session on Opus 5.5. 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 skills, from other repositories
ripple
Analyzing pre-change impact across vertical (dependency chains, files) and horizontal (pattern consistency, naming) dimensions. Use to estimate blast radius before a refactor. No code.
sweep
Detecting unnecessary files, unused code, and orphaned files, and proposing safe deletion. Not for removal execution (Builder), repo structure (Grove), or scope cutting (Void).
bolt
Optimizing frontend (re-render, memoization, lazy loading) and backend (N+1, indexing, caching, async) performance, plus continuous auto-tuning loops for GC/threadpool/cache/worker settings.
lens
Comprehending and investigating codebases: structure mapping, feature discovery, data flow tracing for 'does X exist?' or 'how does Y work?'. Includes a conversational ask mode. Does not write code.
scout
Investigating bugs via root cause analysis, reproduction steps, and impact assessment. Investigation-only — finds why bugs occur and where to fix them, no code. Use when a bug needs RCA before a fix.
trail
Investigating git history, analyzing regression root causes, and performing code archaeology. Time-travels through commits to uncover truth. Use for git history investigation.