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/skills/sol-optimize/SKILL.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/skills/cgfixit/azureai-copilotstudio-personalagent-instructions/sol-optimize)<a href="https://agentmods.dev/skills/cgfixit/azureai-copilotstudio-personalagent-instructions/sol-optimize"><img src="https://agentmods.dev/badge/skills/cgfixit/azureai-copilotstudio-personalagent-instructions/sol-optimize.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 5.1 | $0.00073 | $0.00777 |
| Opus 5 | $0.00036 | $0.00388 |
| Sonnet 5 | $0.00015 | $0.00155 |
| Haiku 4.5 | $0.00007 | $0.00078 |
Grade A, and why
sol-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 8d 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sol Optimize
Optimize deployable examples only. Do not edit TEMPLATE.md, CI, or unrelated repo
surfaces unless the user explicitly expands scope.
Workflow
- Establish scope.
- If the user names an
examples/*.mdfile, target only that file. - Otherwise inventory every example (with the sol suffix in file name)and select the smallest coherent set with a concrete Sol-specific problem.
- Run
python .codex/scripts/repo_audit.py analyze .before editing. - Treat its o3 guidance result as baseline hygiene, not proof of Sol readiness.
- If the user names an
- Refresh current model guidance.
- Use
$openai-docsto fetch the live GPT-5.6 model guidance and itsPrompting best practicessection. - If that skill is unavailable, use only
https://developers.openai.com/api/docs/guides/model-guidance?model=gpt-5.6. - Treat live OpenAI documentation as canonical. Do not hardcode pricing, limits, availability, or optional feature behavior in example prompts.
- Use
- Audit each target against the Sol rubric below.
- Make the smallest behavior-preserving edit in the file's existing dialect.
- Validate every changed example and report measured versus wording-only results.
Sol Rubric
Preserve domain facts and every safety invariant: authoritative-source hierarchy, version strictness, forbidden actions, escalation, security/privacy, connected-tool scope, checkpoints, and required output formats.
Prefer:
- lean, outcome-oriented instructions that state each rule once;
- explicit goals, context, hard constraints, required evidence, success criteria, stopping conditions, and output format;
- one clear autonomy and approval policy that permits safe in-scope work and stops before external, destructive, costly, or scope-expanding actions;
- targeted clarification only when ambiguity materially changes correctness or safety;
- concise, precise descriptions for tools that are actually available;
- observable verification before claiming completion.
Remove or tighten only when redundant or harmful:
What ships with it
1 file 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.
- 8d ago First seen · 74 lines · 73 tokens per session scan A 6ac4f530d231
sol-optimize is a skill published in the GitHub repository cgfixit/AzureAI-CopilotStudio-PersonalAgent-Instructions (1 stars, last pushed 6d ago), licensed MIT. It adds 73 tokens to every session and 777 once invoked, about $0.0004 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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