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 skills add Alloy-Systems/work-with-alloy --skill review-alloy-operationsgit clone --depth 1 https://github.com/Alloy-Systems/work-with-alloyWrote 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/skills/alloy-systems/work-with-alloy/review-alloy-operations)<a href="https://agentmods.dev/skills/alloy-systems/work-with-alloy/review-alloy-operations"><img src="https://agentmods.dev/badge/skills/alloy-systems/work-with-alloy/review-alloy-operations/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/skills/alloy-systems/work-with-alloy/review-alloy-operations"><img src="https://agentmods.dev/badge/skills/alloy-systems/work-with-alloy/review-alloy-operations.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 | $0.00047 | $0.00722 |
| Opus 5 | $0.00023 | $0.00361 |
| Sonnet 5 | $0.00009 | $0.00144 |
| Haiku 4.5 | $0.00005 | $0.00072 |
Grade A, and why
review-alloy-operations 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 11d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Alloy Operations
Use this skill together with work-with-alloy.
This skill is for operational reviews of an Alloy org: teammates, instruction skills, workflows, MCP setup, recent activity, run evidence, and optimization opportunities.
When to Use
Use this when the user wants any of the following:
- an org audit of AI teammates, instruction skills, workflows, or MCPs
- a review of what happened over a date range
- a review of teammate or workflow configuration quality
- a review of run logs or operational patterns
- optimization recommendations for how the org is set up
Do not use this for normal one-off teammate creation, small workflow edits, or ordinary Storage note work.
Required references
Before starting, read:
../work-with-alloy/references/teammates-and-workflows.md../work-with-alloy/references/skills.mdwhen reviewing shared instruction skills../work-with-alloy/references/workflows.md../work-with-alloy/references/multi-agent.mdwhen delegation is neededreferences/operational-review-pattern.md
Use references/review-note-template.md for per-object notes.
Scope gate
Before starting the review, determine the review scope:
- full org review
- subset review
If the user does not specify, ask which they want.
If subset review, clarify the minimum needed scope:
- which teammates, instruction skills, workflows, MCPs, or areas
- date range
- whether the focus is configuration, run evidence, optimization, or all of them
Review flow
- Confirm scope:
- full org review or subset review
- exact objects and date range when the scope is partial
- Build the audit surface:
- active AI teammates only
- current org and teammate-assigned workflows
- shared instruction skills under
.skillswhen they are in scope - MCP servers
- Exclude soft-deleted objects.
- Treat workflow-list results only as candidates. Verify existence, readability, and ownership:
employee_id = nullmeans organization-owned; a populatedemployee_idmeans teammate-assigned. Reconcile with the UI when needed. - If the task is broad and subagents are available, fan out one subagent per teammate, workflow, or instruction skill in scope. Keep each subagent narrow and require it to write its note before returning.
- Review runs selectively. Start with run lists, then inspect only failed, high-volume, suspicious, long-running, or representative successful runs.
- Exclude clear internal testing from production conclusions, but still note real config or safety issues exposed by those runs.
- Synthesize both:
- per-object findings
- cross-cutting findings
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 82 lines · 47 tokens per session scan A 0c3a1b463d29
review-alloy-operations is a skill published in the GitHub repository Alloy-Systems/work-with-alloy (1 stars, last pushed 12d ago), licensed Apache-2.0. It adds 47 tokens to every session and 722 once invoked, about $0.0002 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 2026-08-31.
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