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.
git 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/commands/smart-ai-memory/attune-ai/release)<a href="https://agentmods.dev/commands/smart-ai-memory/attune-ai/release"><img src="https://agentmods.dev/badge/commands/smart-ai-memory/attune-ai/release/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/commands/smart-ai-memory/attune-ai/release"><img src="https://agentmods.dev/badge/commands/smart-ai-memory/attune-ai/release.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 | $0.00010 | $0.01003 |
| Opus 5.5 | $0.00004 | $0.00401 |
| Sonnet 5.5 | $0.00002 | $0.00201 |
| Haiku 4.5 | $0.00001 | $0.00100 |
Grade A, and why
release 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
release
Release preparation, security scanning, and publishing hub.
Quick Shortcuts
| Shortcut | Action |
|---|---|
/release prep |
Full release preparation workflow |
/release security |
Pre-release security audit |
/release health |
Full project health check |
/release publish |
Build and publish to PyPI |
/release version <v> |
Bump version number |
Natural Language
Describe what you need:
- "prepare for release"
- "run a security scan before shipping"
- "is the project healthy enough to release?"
- "publish to PyPI"
- "bump version to 5.2.0"
CRITICAL: Workflow Execution Instructions
When this command is invoked with arguments, you MUST execute the workflow, not answer ad-hoc.
Context Gathering (ALWAYS DO FIRST)
Before executing any action below, gather current project context:
- Run:
git status --short - Run:
git log --oneline -5 - Run:
git branch --show-current - Run:
grep '^version' pyproject.toml(current version)
Use this context to inform release decisions (e.g., uncommitted changes, current version, branch).
Reasoning Approach
For release decisions, use structured reasoning to make a go/no-go recommendation:
Shortcut Routing (EXECUTE THESE)
| Input | Action |
|---|---|
/release prep |
Run Release-Prep wizard: version info → readiness check → changelog → decompose tasks → preview → confirm |
/release security |
Run Security wizard: define scope → scan → generate fixes → decompose remediation → preview |
/release health |
Run pytest + coverage + ruff + bandit, report aggregate results |
/release publish |
uv run python -m build && uv run twine upload dist/* |
/release version <v> |
Update version in pyproject.toml and src/attune/__init__.py |
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 · 116 lines · 10 tokens per session scan A 6845339d041f
release is a command published in the GitHub repository Smart-AI-Memory/attune-ai (10 stars, last pushed 5d ago), licensed Apache-2.0. It adds 10 tokens to every session and 1,003 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 2026-09-03.
Other commands, from other repositories
pm-competitive
Competitive teardown — for a given competitor or for the whole landscape around a JTBD. Spawns market-analyst. Outputs structured brief with positioning gaps.
pm-ownership
Show who owns what across initiatives, gates, drafts, and Beads issues. Surfaces orphaned artefacts (no owner) and over-loaded owners.
pm-pricing
Author or refresh a pricing plan — 2–3 monetization models with willingness-to-pay rationale per audience. Spawns pricing-strategist.
pm-save
Extract lessons from this session and save them to .great-pm/lessons.md. Optional cross-project promotion to /.great-pm/decisions.md for patterns seen 3+ times (proposed, never auto-promoted).
pm-burn
Cost burn-rate — LLM cost over the last N days vs a human-equivalent baseline (savingsx). Flags cost outliers and abnormal-burn agents.
agentos-status
Show AgentOS system status — agents, workers, health.