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 commands/dsb-117/brainblast/brainblast-oraclegit clone --depth 1 https://github.com/DSB-117/brainblastWrote 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/commands/dsb-117/brainblast/brainblast-oracle)<a href="https://agentmods.dev/commands/dsb-117/brainblast/brainblast-oracle"><img src="https://agentmods.dev/badge/commands/dsb-117/brainblast/brainblast-oracle.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 | $0.00000 | $0.00387 |
| Opus 5 | $0.00000 | $0.00193 |
| Sonnet 5 | $0.00000 | $0.00077 |
| Haiku 4.5 | $0.00000 | $0.00039 |
Grade A, and why
brainblast-oracle 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 5d 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
/brainblast-oracle
Live On-Chain Intelligence: is the oracle fresh? Before you price anything against a Pyth / Switchboard / Chainlink feed, check when its account was last written.
Provider-agnostic — instead of parsing each oracle's binary layout, it measures the one universal signal: the slot of the most recent transaction touching the account vs. the current slot. A feed that hasn't updated recently is exactly how protocols get drained at the wrong price.
Usage
/brainblast-oracle <account> [--rpc URL] [--max-staleness-slots N | --max-staleness-seconds N] [--json]
npx brainblast oracle $ARGUMENTS
--rpc URL— use your own endpoint (the public RPC is rate-limited; pass Helius/Triton for reliable results).--max-staleness-slots N— staleness threshold in slots (default 150 ≈ 60s).--max-staleness-seconds N— threshold in seconds (converted at ~400ms/slot).--json— machine-readable result for an agent.
Reports FRESH / STALE / NO_HISTORY with how many slots/seconds ago the feed last updated. Exit 1 on STALE or NO_HISTORY — wire it into a pre-trade gate. A markdown report is written to .agent-research/oracle-freshness.md.
Related:
brainblast trust-graph <programId…>now classifies upgrade authority live — single-key vs multisig (Squads) vs DAO (SPL Governance) — by reading the authority account's owner program, and shows an at-a-glance trust line (authority · verified build · audited).
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.
- 5d ago First seen · 25 lines · 0 tokens per session scan A eb411db1fb2b
brainblast-oracle is a command published in the GitHub repository DSB-117/brainblast (100 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 387 tokens. 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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checklist
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clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
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analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.