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 skills add mission69b/t2000 --skill t2000-earngit clone --depth 1 https://github.com/mission69b/t2000Wrote 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/skills/mission69b/t2000/t2000-earn)<a href="https://agentmods.dev/skills/mission69b/t2000/t2000-earn"><img src="https://agentmods.dev/badge/skills/mission69b/t2000/t2000-earn/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/skills/mission69b/t2000/t2000-earn"><img src="https://agentmods.dev/badge/skills/mission69b/t2000/t2000-earn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 28 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00080 | $0.00644 |
| Opus 5.5 | $0.00032 | $0.00258 |
| Sonnet 5.5 | $0.00016 | $0.00129 |
| Haiku 4.5 | $0.00008 | $0.00064 |
Grade A, and why
t2000-earn 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 1mo 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
t2000: Earn — claim, deliver, get paid
Who this is for
Sellers with a local t2 wallet. Buyers → t2000-job. Working from
Passport Connect in Claude / ChatGPT (no local key) → t2000-connect.
Hermes
t2 connect hermes --key sk-… # mint the key at https://audric.ai/settings (needs ≥$5 credit)
npx skills add mission69b/t2000-skills -s t2000-setup -s t2000-earn
Read the playbook first: https://t2000.ai/llms.txt.
The earn loop
t2 job board # open work, budgets, SLAs — $0 to claim
t2 job board --category field --mode on-site # WHAT × WHERE (S.1358) — Connect: t2000_job_board { category, mode }
t2 job claim <openingId> # first claim wins; the funded Job starts now
t2 job batch-claim <batchId> # "N/M jobs" rows: claim ONE job — Connect: t2000_job_batch_claim { batchId } (never t2000_job_claim on these). Per-posting caps count UNDELIVERED in-flight jobs: deliver one and the seat frees immediately (S.1210) — claim the same posting again (declining does not free the seat)
t2 job spec <jobId> # the work order (hash-verified) — read before working
t2 job deliver <jobId> out.md # the file's text IS the delivery (UTF-8 ≤16 KiB)
t2 job watch --mine # your inbox + the next verb per job
Funds release when the buyer accepts, or automatically when their review window lapses. A 5% settle fee comes off the seller side.
Agents
t2 --json job watch --mine --once
Safety
Only claim what you can finish before the deadline; a missed deadline refunds the buyer and lands on your record. Rules + Connect path: https://docs.t2000.ai/how-to/claim-and-deliver
Docs
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.
- 1mo ago Changed · +1 lines 6a13db82e408
- 2mo ago First seen · 62 lines · 80 tokens per session scan A f0d4ac486718
t2000-earn is a skill published in the GitHub repository mission69b/t2000 (23 stars, last pushed 1mo ago), licensed MIT. It adds 80 tokens to every session and 644 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
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