Borrowing it
Nothing to install: this file belongs to petar-djukic/writing-skills. 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/petar-djukic/writing-skills/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/petar-djukic/writing-skillsWrote 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/instructions/petar-djukic/writing-skills/copilot-instructions)<a href="https://agentmods.dev/instructions/petar-djukic/writing-skills/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/petar-djukic/writing-skills/copilot-instructions/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/instructions/petar-djukic/writing-skills/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/petar-djukic/writing-skills/copilot-instructions.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 | $0.08894 | $0.08894 |
| Opus 5 | $0.04447 | $0.04447 |
| Sonnet 5 | $0.01779 | $0.01779 |
| Haiku 4.5 | $0.00889 | $0.00889 |
Grade A, and why
writing-skills copilot-instructions.md 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 4d 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 — 886 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Copilot Instructions
This file is self-contained: it inlines the agent instructions and the
repository rules so the .github tree works as a bare symlink into another
repository. Commands live in .github/prompts/*.prompt.md (full workflow
each) and skills in .github/skills/.
Agent instructions
Agent Instructions
Issue tracking uses GitHub Issues via the gh CLI. The /do-work and /git-issue-pop commands handle the full workflow: fetching issues, assigning tasks, tracking sub-issues, and opening pull requests.
Environment
The skills that shell out to Python run in a pixi-managed environment that ships inside the agent directory (pixi.toml and pixi.lock at its root, provisioned by scripts/ensure-env.sh). Because the agent directory is symlinked into target repositories, the environment travels with it.
On opening a repository — or at the latest before running any skill that invokes a Python script — run the preflight from the agent directory:
scripts/ensure-env.sh
It checks for pixi (installing it if absent, unless SKILL_ENV_NO_INSTALL is set), then materializes the locked environment. It is idempotent and fast once provisioned. Run skill scripts through it with pixi run --manifest-path <agent-dir>/pixi.toml python <script>. The filter-tells detectors need only bash and the Python stdlib, so they run without this step.
Pre-Commit Quality Gate
Before committing, run mage audit and fix all reported YAML schema errors. The audit target checks cross-artifact consistency (PRDs, use cases, test suites, roadmap) and validates YAML fields against Go structs. Unrecognized fields cause data loss in the measure prompt. Do not commit with audit errors.
Commit After Every Edit
After creating or editing any file, run mage audit, fix any errors, then commit. Do not accumulate uncommitted changes across multiple turns. Each round of edits gets its own commit before responding to the user. This applies to all file types: code, docs, rules, config.
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.
- 4d ago Changed · +16 lines · +238 tokens per session 9952cb785b70
- 9d ago First seen · 870 lines · 8,656 tokens per session scan A a633b74458a5
writing-skills copilot-instructions.md is an instructions file published in the GitHub repository petar-djukic/writing-skills (4 stars, last pushed 6d ago), licensed MIT. It adds 8,894 tokens to every session, about $0.0445 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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