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 commands/smart-ai-memory/attune-ai/specgit 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/spec)<a href="https://agentmods.dev/commands/smart-ai-memory/attune-ai/spec"><img src="https://agentmods.dev/badge/commands/smart-ai-memory/attune-ai/spec.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 | $0.00020 | $0.00451 |
| Opus 5 | $0.00010 | $0.00226 |
| Sonnet 5 | $0.00004 | $0.00090 |
| Haiku 4.5 | $0.00002 | $0.00045 |
Grade A, and why
spec 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.
What it actually says
Spec-driven development for $ARGUMENTS.
If no arguments, use AskUserQuestion to ask what the user wants to do:
- Start a new spec (brainstorm, decompose, save)
- Resume an in-progress spec (check for resumable plans)
- Import a spec file (load from another project/path)
- Execute a spec (review then task-by-task with approval)
Import
If the user provides a file path or chooses "Import":
- Validate path with
_validate_file_path() - Copy to
.claude/plans/if not already there - Load tasks with
read_spec(path) - If tasks found, proceed to Review
- If no tasks, offer to create a spec instead
Create
Run brainstorm flow (Context, Problem, Goals, End State).
Auto-decompose approach into XML <task> blocks. Save to
.claude/plans/.
Review
Load tasks with read_spec(plan_path). Show each task:
name, objective, files, risks. Use AskUserQuestion for
approve/edit/reject.
Execute
For each pending task:
- Show progress bar
- Show task detail
- Implement the task (create/modify files)
- Run quality gates via PipelineOrchestrator
- Severity-gated approval:
- HIGH severity (score < 50): only "Fix and retry" or "Acknowledge risk" (no auto-run)
- MEDIUM/LOW: "Approve" / "Redo" / "Auto-run remaining"
- Save state after each decision
Resume
Check find_resumable_plans() on startup. Offer to
resume incomplete specs.
Use from attune.spec import for all helpers:
present_tasks, present_task_detail, format_progress_bar,
load_state, save_state, find_resumable_plans,
get_pending_tasks, SpecState.
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 · 62 lines · 20 tokens per session scan A 767e1e86eb73
spec is a command published in the GitHub repository Smart-AI-Memory/attune-ai (10 stars, last pushed today), licensed Apache-2.0. It adds 20 tokens to every session and 451 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
ship-and-babysit
Commit, push to origin (fork), open PR to tinyhumansai/openhuman:main, then poll every 5min for CodeRabbit comments and CI failures, resolve them, and exit when clean.
agentos-status
Show AgentOS system status — agents, workers, health.
council-sweep
Walk the configured watch paths and run Council on every artifact modified in the last N hours (default 24h).
orchestrate
Orchestrate a complex multi-step task using the multi-agent system.
pm-agent-retire
Mark a great-pm agent as deprecated. Adds a deprecation banner to the agent file, files a Beads issue to remove dependent commands/workflows, and logs the rationale. NEVER deletes the file (history preserved).
pm-audit
Run the great-pm PM-health audit on a product, an initiative, or great-pm itself. 15 dimensions, severity-rated findings, Top-5 + Quick-Wins + Things-Look-Bad-But-Fine + Open Questions. Files findings as Beads tasks unless --read-only.