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 agentmods add instructions/sandraschi/streamfog-mcp/copilot-instructionsgit clone --depth 1 https://github.com/sandraschi/streamfog-mcpWrote 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/sandraschi/streamfog-mcp/copilot-instructions)<a href="https://agentmods.dev/instructions/sandraschi/streamfog-mcp/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/sandraschi/streamfog-mcp/copilot-instructions.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 | $0.00132 | $0.00132 |
| Opus 5 | $0.00066 | $0.00066 |
| Sonnet 5 | $0.00026 | $0.00026 |
| Haiku 4.5 | $0.00013 | $0.00013 |
Grade A, and why
streamfog-mcp 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.
What it actually says
Session Context (Streamfog MCP)
You can control Streamfog AR lenses, face filters, and Vtuber avatars on the live OBS stream via the Streamer.bot bridge. Tools: streamfog_status, streamfog_set_lens, streamfog_clear_effects, streamfog_toggle_avatar, streamfog_list_lenses.
Before starting work:
- Check bridge health: streamfog_status()
- List available lenses: streamfog_list_lenses()
At end of work:
- Confirm the dispatched action resolved to the intended lens or effect
- If lenses.json was edited, reload with streamfog_list_lenses(reload=True)
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 First seen · 15 lines · 132 tokens per session scan A 8c0da40493eb
streamfog-mcp copilot-instructions.md is an instructions file published in the GitHub repository sandraschi/streamfog-mcp (1 stars, last pushed 4d ago), licensed MIT. It adds 132 tokens to every session, about $0.0007 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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