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/stefaniuk/loadoutWrote 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/stefaniuk/loadout/enforce.python)<a href="https://agentmods.dev/commands/stefaniuk/loadout/enforce.python"><img src="https://agentmods.dev/badge/commands/stefaniuk/loadout/enforce.python/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/stefaniuk/loadout/enforce.python"><img src="https://agentmods.dev/badge/commands/stefaniuk/loadout/enforce.python.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 | $0.00009 | $0.00086 |
| Opus 5.5 | $0.00004 | $0.00034 |
| Sonnet 5 | $0.00002 | $0.00017 |
| Haiku 4.5 | $0.00001 | $0.00009 |
Grade A, and why
enforce.python 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 16d 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.
This is a copy
78% identical to enforce.docker — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
This prompt delegates to the enforcement-audit skill.
Run the enforcement-audit skill for Python.
$ARGUMENTS
Pass through the user input above as additional context for the audit.
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.
- 16d ago First seen · 16 lines · 9 tokens per session scan A 44040b688e6f
enforce.python is a command published in the GitHub repository stefaniuk/loadout (1 stars, last pushed today), licensed MIT. It adds 9 tokens to every session and 86 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 78% identical to enforce.docker, differing in 4 lines, and is treated as a copy.
Other commands, from other repositories
sddp-implement-qc-loop
Command description: Run implement and QC in a continuous loop. Argument hint: [optional: feature directory or branch name] Command category: orchestration Prerequisites: spec, plan, tasks.
sddp-prd
Command description: Create or refine the canonical product document. Argument hint: [rough product idea, users, domain, or market opportunity] Command category: project-bootstrap Prerequisites: none.
sddp-qc
Command description: Run quality control against the implemented feature. Argument hint: [optional: testing focus such as unit tests, security audit, requirements sync] Command category: feature-delivery Prerequisites: spec, plan, tasks, implementation:complete.
sddp-specify
Command description: Create a feature specification from a feature description. Argument hint: [feature description] Command category: feature-delivery Prerequisites: project-instructions.
sddp-amend
Command description: Propagate a bootstrap change across canonical project artifacts and the project plan. Argument hint: [project-level change to propagate across bootstrap artifacts] Command category: project-bootstrap Prerequisites: project-instructions, product-document, technical-context, project-plan.
sddp-analyze
Command description: Audit spec, plan, and tasks for consistency and quality. Argument hint: [optional: analysis focus or remediation request] Command category: feature-delivery Prerequisites: spec, plan, tasks.