Borrowing it
Nothing to install: this file belongs to cgfixit/AzureAI-CopilotStudio-PersonalAgent-Instructions. 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/cgfixit/AzureAI-CopilotStudio-PersonalAgent-Instructions/main/.codex/commands/azureai-optimize.mdgit clone --depth 1 https://github.com/cgfixit/AzureAI-CopilotStudio-PersonalAgent-InstructionsWrote 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/cgfixit/azureai-copilotstudio-personalagent-instructions/azureai-optimize)<a href="https://agentmods.dev/commands/cgfixit/azureai-copilotstudio-personalagent-instructions/azureai-optimize"><img src="https://agentmods.dev/badge/commands/cgfixit/azureai-copilotstudio-personalagent-instructions/azureai-optimize/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/cgfixit/azureai-copilotstudio-personalagent-instructions/azureai-optimize"><img src="https://agentmods.dev/badge/commands/cgfixit/azureai-copilotstudio-personalagent-instructions/azureai-optimize.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 | $0.00108 |
| Opus 5 | $0.00000 | $0.00054 |
| Sonnet 5 | $0.00000 | $0.00022 |
| Haiku 4.5 | $0.00000 | $0.00011 |
Grade A, and why
azureai-optimize 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 9d 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
AzureAI Optimize
Use .codex/skills/azureai-optimize/SKILL.md as the source of truth for periodic
repo improvement passes.
When the user asks to optimize prompt quality, Codex setup, or CI hygiene:
- run
python .codex/scripts/repo_audit.py analyze . - pick the smallest justified fix from the findings
- preserve each file's dialect and safety wording
- finish with
python .codex/scripts/repo_audit.py preflight .if Markdown changed
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.
- 9d ago First seen · 12 lines · 0 tokens per session scan A ded38d4bec4f
azureai-optimize is a command published in the GitHub repository cgfixit/AzureAI-CopilotStudio-PersonalAgent-Instructions (1 stars, last pushed 7d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 108 tokens. 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.
Other commands, from other repositories
fest-show
Show festival progression (in-progress tasks, roadmap, and dependency view).
superpowers-execute
Execute the current GSD phase plan with Superpowers instead of gsd-execute-phase.
synthesise-reviews
Deduplicate and reconcile multiple completed review reports into one prioritised revision plan with conflicts and dependencies made explicit. Use when parallel reviewers have returned findings that need a single action sequence. Not for running the reviews; use $review-cluster.
triage
Triage ServiceNow incidents — list open incidents, assess priority, investigate a specific INC, or analyze trends.
scan
Scan AWS account for cost optimization.
setup
Diagnose-first project setup with state machine — scans, confirms, interviews, writes.