Borrowing it
Nothing to install: this file belongs to zarfld/copilot-instructions-template. 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/zarfld/copilot-instructions-template/master/.github/prompts/operational-profile-create.prompt.mdgit clone --depth 1 https://github.com/zarfld/copilot-instructions-templateWrote 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/zarfld/copilot-instructions-template/operational-profile-create)<a href="https://agentmods.dev/commands/zarfld/copilot-instructions-template/operational-profile-create"><img src="https://agentmods.dev/badge/commands/zarfld/copilot-instructions-template/operational-profile-create/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/zarfld/copilot-instructions-template/operational-profile-create"><img src="https://agentmods.dev/badge/commands/zarfld/copilot-instructions-template/operational-profile-create.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 | $0.00038 | $0.06045 |
| Opus 5.5 | $0.00015 | $0.02418 |
| Sonnet 5.5 | $0.00008 | $0.01209 |
| Haiku 4.5 | $0.00004 | $0.00605 |
Grade A, and why
operational-profile-create 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 14d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 14d ago First seen · 654 lines · 38 tokens per session scan A 97dc293f9048
operational-profile-create is a command published in the GitHub repository zarfld/copilot-instructions-template (1 stars, last pushed 15d ago), with no licence file. It adds 38 tokens to every session and 6,045 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-15.
Other commands, from other repositories
verify-math
Verify a self-authored mathematical result end to end by routing claims across adversarial review, numerical falsification, symbolic or CAS checks, and Lean, then aggregating one report. Use when a theorem, proposition, conjecture, or paper-wide mathematical argument needs the appropriate combination of verification…
cross-language-check
Replicate a quantitative analysis in a second language (R↔Python↔Stata↔Julia) and compare outputs for implementation errors. Use when an existing empirical result needs independent cross-language verification. Not for reviewing one implementation in place; use $code-suite.
lean-check
Formalize a self-authored lemma or theorem in Lean 4/mathlib and require a clean lake build without sorry. Use when the mathematical claim can be stated faithfully and machine-checked. For numerical falsification or symbolic algebra, use $numerical-check or $symbolic-check.
synthetic-data
Generate structurally realistic synthetic datasets for pipeline prototyping, test coverage, or prospective power analysis. Use when code or design must be exercised before real data are available or accessible. Never substitute synthetic records for governed raw data.
eval
Evaluate the migrate-nextflow-code skill.
thesis-gate
Run or check a Cross-Validation Gate for the current thesis workflow phase. Validates wave outputs and records results.