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/pharosone/vector-plugin/gemini-mdgit clone --depth 1 https://github.com/pharosone/vector-pluginWhat 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 | $0.00710 | $0.00710 |
| Opus 5 | $0.00355 | $0.00355 |
| Sonnet 5 | $0.00142 | $0.00142 |
| Haiku 4.5 | $0.00071 | $0.00071 |
Grade A, and why
vector-plugin GEMINI.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 yesterday.
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 — 29 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vector context for Gemini CLI
This Gemini CLI session has access to Vector, a red-team scanning service for LLM agents published by Pharos One. The Vector MCP server is bridged in through mcp-remote and exposes tools that mirror the public REST API (create_session, get_session, list_attacks, submit_results, wait_for_report, get_report, plus the agents.* CRUD).
When to use MCP tools vs skills
- Use MCP tools when the user wants to do something with Vector data right now from this session: start a scan, fetch the latest report, list attacks for a session, save an agent profile. These return JSON; you summarize.
- Use a skill when the user wants to change their codebase in response to Vector output: integrate scanning into the repo / CI (
integrate), fix a single FAIL (harden-from-finding), batch-fix many FAILs (batch-fix-findings), or generate an AgentContext JSON for the cabinet (create-agent-context).
Skills in Gemini CLI are not invoked through slash-commands — they activate when the user's plain-language request matches the skill's description. So "integrate Vector into this repo" maps to the integrate skill; "help me fix these red-team findings" maps to batch-fix-findings.
Defaults
- Cabinet (browser UI):
https://vector.pharosone.ai. - REST API base URL:
https://vector-api.pharosone.ai. - MCP endpoint:
https://vector-api.pharosone.ai/api/v1/mcp/(trailing slash matters — the server 307-redirects the bare/mcp; overridable via theVECTOR_MCP_URLenv var for private deployments). - Auth split (important):
- MCP tools (this session) use OAuth 2.1 via Clerk — browser flow on first call, tokens cached by
mcp-remote. No key for you to handle. - REST API (the CI runner that the
integrateskill writes into the user's repo) usesAuthorization: Bearer ak_..., a long-lived Clerk API Key minted by the user in the cabinetSettings → API keyspage. Do NOT ask the user to paste the API key value into this chat — the value belongs in their secret manager and a gitignored.env, never in your context window.
- MCP tools (this session) use OAuth 2.1 via Clerk — browser flow on first call, tokens cached by
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.
- yesterday First seen · 29 lines · 710 tokens per session scan A 738879062b57
vector-plugin GEMINI.md is an instructions file published in the GitHub repository pharosone/vector-plugin (1 stars, last pushed 3mo ago), licensed MIT. It adds 710 tokens to every session, about $0.0036 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.
Other instructions, from other repositories
midplane AGENTS.md
Instructions for midplaneai/midplane, covering agent operating notes — midplane-cloud, monorepo layout (one codebase, two deployables), design system, client-component imports from @midplane-cloud/db and server actions: return state, don't throw, for user input.
midplane CLAUDE.md
Instructions for midplaneai/midplane, covering claude code — midplane-cloud and skill routing (claude code).
niuma-engine CLAUDE.md
Instructions for Destined-at-Dawn/niuma-engine, covering startup sequence (every conversation -- mandatory), project rules, r21 -- three-layer file protection (critical), think before act and no blind overwrite (critical).
agentbreak CLAUDE.md
Instructions for mnvsk97/agentbreak, covering claude code — agentbreak, what this repo is, quick commands, skill and verification.
pattern8 AGENTS.md
Instructions for Aquifer-sea/pattern8, covering agents.md — p8 global instructions (all agents must follow), pattern 8 (p8) — agent behavior constraints, core constraints, five patterns (cannot be skipped) and 1. pipeline.
awesome-copilot-id AGENTS.md
Instructions for GulajavaMinistudio/awesome-copilot-id, covering communication, explanation and documentation, markdown formatting, user communication style and workflow & methodology.