Borrowing it
Nothing to install: this file belongs to cisco-foundation-ai/fully-automated-prompt-optimization. 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/cisco-foundation-ai/fully-automated-prompt-optimization/main/.claude/commands/reset-tenant.mdgit clone --depth 1 https://github.com/cisco-foundation-ai/fully-automated-prompt-optimizationWrote 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/cisco-foundation-ai/fully-automated-prompt-optimization/reset-tenant)<a href="https://agentmods.dev/commands/cisco-foundation-ai/fully-automated-prompt-optimization/reset-tenant"><img src="https://agentmods.dev/badge/commands/cisco-foundation-ai/fully-automated-prompt-optimization/reset-tenant/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/cisco-foundation-ai/fully-automated-prompt-optimization/reset-tenant"><img src="https://agentmods.dev/badge/commands/cisco-foundation-ai/fully-automated-prompt-optimization/reset-tenant.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 | $0.00000 | $0.01705 |
| Opus 5 | $0.00000 | $0.00852 |
| Sonnet 5 | $0.00000 | $0.00341 |
| Haiku 4.5 | $0.00000 | $0.00170 |
Grade C, and why
reset-tenant scanned grade C with 1 finding 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 12d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
Remove contents of these directories if they exist (these are gitignored, use `rm -rf`): How it starts
The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
description: > Reset a tenant to baseline (variant-001), removing all optimization artifacts. TRIGGER when: user wants to reset a tenant, start fresh, clear optimization history, revert to baseline, undo all prompt iterations, or clean-slate a tenant. DO NOT TRIGGER when: user wants to run evals (use eval-runner), optimize prompts (use optimization agent), or create synthetic data (use synthetic-samples).
Reset Tenant to Baseline
Overview
Remove all optimization artifacts (non-baseline prompt variants, chain variants, iteration memory, optimization changelog entries) from a tenant, leaving it in a clean baseline state as if no optimization had ever been performed. Git history preserves the work.
Inputs
tenant_id(required): The tenant directory name undertenants/. If not provided, ask the user.
Pre-flight
-
Validate tenant exists: Confirm
tenants/<tenant_id>/exists. Abort if not. -
Detect prompt layout (per-tenant, not assumed globally):
- Modules layout:
tenants/<tenant_id>/prompts/modules/exists and contains subdirectories with variant files (e.g. hotpotqa) - Flat layout:
tenants/<tenant_id>/prompts/variants/contains variant files directly (e.g. aime2025, cti_rcm) - If neither directory exists, warn and skip prompt variant cleanup.
- Modules layout:
-
Inventory what will be reset — scan and list:
- Non-baseline prompt variants (
variant-002and above) in whichever layout applies - Chain variant files in
chains/variants/(if directory exists) - Config files referencing non-baseline variants in
configs/ - Changelog entries in
docs/change-log.mdreferencingvariant-002or higher - Iteration memory in
docs/iteration-memory.jsonl(if it exists and is non-empty) - Local eval outputs in
evals/tmp/andreports/(if they exist)
- Non-baseline prompt variants (
-
Show the inventory to the user and ask for explicit confirmation before proceeding. If there is nothing to reset, report that the tenant is already at baseline and stop.
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.
- 12d ago First seen · 151 lines · 0 tokens per session scan C a3049961ebcf
reset-tenant is a command published in the GitHub repository cisco-foundation-ai/fully-automated-prompt-optimization (107 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,705 tokens. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
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clarify
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specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.