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/tierzeroai/tierzero-cursor/tierzero-fetchnpx skills add TierZeroAI/tierzero-cursor --skill tierzero-fetchgit clone --depth 1 https://github.com/TierZeroAI/tierzero-cursorWhat 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 | $0.00078 | $0.00578 |
| Opus 5 | $0.00039 | $0.00289 |
| Sonnet 5 | $0.00016 | $0.00116 |
| Haiku 4.5 | $0.00008 | $0.00058 |
Grade A, and why
tierzero-fetch 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 2d 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
TierZero: Fetch Context
Load saved TierZero context (a chat thread, investigation, or artifact) so the agent can act on it.
When to use
- The user pastes a TierZero URL (
https://app.tierzero.ai/chat/c/...orhttps://app.tierzero.ai/investigations/...). - The user pastes a bare artifact UUID (e.g.
bf904904-afdc-4cf2-94d8-76a4a8bb4f75). - The user says "load that investigation" / "pull in the context from TierZero" / similar.
How to call
Use the tierzero_fetch_context MCP tool exposed by the tierzero MCP server registered by this plugin.
Arguments:
url(string, required): the chat URL, investigation URL, or artifact UUID.include_sources(bool, optional, defaultfalse): set totrueonly when the user asks for source-by-source breakdowns or you need to cite specific log lines / traces.
Supported inputs:
| Type | Example |
|---|---|
| Chat URL | https://app.tierzero.ai/chat/c/<GlobalID> |
| Investigation URL | https://app.tierzero.ai/investigations/<GlobalID> |
| Artifact UUID | bf904904-afdc-4cf2-94d8-76a4a8bb4f75 |
After the call
Parse the response and surface what's relevant for the current task:
- Conversations — walk the messages (use
messageTypeandoutput); summarize the conclusion, then note any open questions. - Investigations — present the
outputJsonresult; quote findings, list evidence sources. - Artifacts — show the artifact
valueandtype; if it's a log/metric snapshot, summarize what it contains.
Only include source metadata if the user explicitly asks for it (and call with include_sources: true). Otherwise it's noise.
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.
- 2d ago First seen · 48 lines · 78 tokens per session scan A 607ecef715e2
tierzero-fetch is a skill published in the GitHub repository TierZeroAI/tierzero-cursor (0 stars, last pushed 3mo ago), licensed MIT. It adds 78 tokens to every session and 578 once invoked, about $0.0004 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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