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 skills/pharosone/vector-plugin/create-agent-contextnpx skills add pharosone/vector-plugin --skill create-agent-contextgit 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 | $0.00062 | $0.01177 |
| Opus 5 | $0.00031 | $0.00589 |
| Sonnet 5 | $0.00012 | $0.00235 |
| Haiku 4.5 | $0.00006 | $0.00118 |
Grade A, and why
create-agent-context 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Goal
Generate an AgentContext payload for a Vector saved agent. The user will paste it into the New Agent page on the cabinet.
Context
- Cabinet (default SaaS deployment):
https://vector.pharosone.ai. REST API base:https://vector-api.pharosone.ai. If the user is on a different deployment, ask them for the URLs first. - Live schema (CORS-open, no auth):
https://vector-api.pharosone.ai/api/v1/public/agent-context-schema.json. Fetch this once at the start if your editor has web access — every field name used below must appear undercomponents.schemas.AgentContext.properties. If it doesn't, the schema has been updated and you should trust the fetched schema, not this skill.
The page has TWO inputs (you must produce TWO things)
- A plain text input labelled "Name" above the JSON editor — that's the agent's slug (e.g.
support-bot-v3). It is NOT inside the JSON. - The JSON editor — its content is exactly an
AgentContextobject (the 5-field schema below). No{ name, description, agent_context: {...} }wrapper around it.
AgentContext — use ONLY these 5 fields, with these EXACT names
Required:
description(string, 1–8000 chars) — Free-form prose: what the agent does, who it serves, what makes it risky, and (if relevant) which tools / data / external systems it can touch — written as prose, not a structured list. This is the single most important field; the planner reads it to choose attack categories. Aim for 3–6 sentences.
Optional, but each one sharpens a different attack class:
name(string, ≤200) — human-readable display label shown in cabinet/reports (NOT the slug).language_hints(string[]) — Always set to exactly["en"]. This deployment supports only English-language agents.restrictions(string[]) — short imperative lines listing things the agent must NEVER do. Drives rule-evasion / policy-bypass attacks. 3–8 entries is a good range.system_prompt_excerpt(string, target ≤500 chars; hard limit 4000) — a short, tight snippet of the user's real system prompt: 2–4 sentences picked specifically because they contain policy verbs ("do not", "never", "always", "must", "refuse", "only", "before") or hard limits ("up to $500", "max 3 retries"). The planner uses these as attack anchors — a multi-paragraph dump adds noise, a focused snippet sharpens attacks. Paraphrase only if the real prompt is confidential.
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 · 65 lines · 62 tokens per session scan A 7da3a1cef032
create-agent-context is a skill published in the GitHub repository pharosone/vector-plugin (1 stars, last pushed 3mo ago), licensed MIT. It adds 62 tokens to every session and 1,177 once invoked, about $0.0003 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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