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/pipeline)<a href="https://agentmods.dev/commands/smart-ai-memory/attune-ai/pipeline"><img src="https://agentmods.dev/badge/commands/smart-ai-memory/attune-ai/pipeline.svg" alt="Measured on agentmods" 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 | $0.00065 |
| Opus 5 | $0.00005 | $0.00032 |
| Sonnet 5 | $0.00002 | $0.00013 |
| Haiku 4.5 | $0.00001 | $0.00006 |
Grade A, and why
pipeline 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.
What it actually says
pipeline (Retired)
The /pipeline command has been replaced by /spec.
Type /spec to start spec-driven development —
brainstorm, plan, review, and execute with quality
gates and approval at every step.
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 · 13 lines · 10 tokens per session scan A ed2b67784f16
pipeline is a command published in the GitHub repository Smart-AI-Memory/attune-ai (10 stars, last pushed today), licensed Apache-2.0. It adds 10 tokens to every session and 65 once invoked, about $0.0001 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.
Other commands, from other repositories
speckit.specjudge.recommend
Recommend the model that fits this feature's tasks, with the fragment of the spec behind every level.
learn
Extract patterns and learnings from current session.
fire-resurrect
Autonomous Resurrection Mode — reverse-engineer intent from messy code, then rebuild clean from scratch.
fire-1b-research
Research, vision selection, and roadmap generation for a new project (Dominion Flow).
fire-execute-plan
Execute a single plan with segment-based routing, per-task atomic commits, and test enforcement.
fire-verify-uat
Conversational User Acceptance Testing with automatic parallel diagnosis on failures.