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.
git clone --depth 1 https://github.com/SpillwaveSolutions/agent-brainWrote 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/spillwavesolutions/agent-brain/agent-brain-multi)<a href="https://agentmods.dev/commands/spillwavesolutions/agent-brain/agent-brain-multi"><img src="https://agentmods.dev/badge/commands/spillwavesolutions/agent-brain/agent-brain-multi/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/commands/spillwavesolutions/agent-brain/agent-brain-multi"><img src="https://agentmods.dev/badge/commands/spillwavesolutions/agent-brain/agent-brain-multi.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00015 | $0.01878 |
| Opus 5.5 | $0.00006 | $0.00751 |
| Sonnet 5.5 | $0.00003 | $0.00376 |
| Haiku 4.5 | $0.00002 | $0.00188 |
Grade A, and why
agent-brain-multi 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.
How it starts
The opening of the file, as written. The whole thing — 277 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Brain Multi-Mode Search
Purpose
Performs multi-mode fusion search combining BM25 keyword matching, semantic vector search, and GraphRAG relationships using Reciprocal Rank Fusion (RRF). This is the most comprehensive search mode, finding results from all angles.
Multi-mode search is ideal for:
- Complex queries requiring comprehensive results
- When you want both content matches AND relationships
- Investigating full implementation details
- Combining technical terms with conceptual understanding
- When you're not sure which mode would be best
Usage
/agent-brain:agent-brain-multi <query> [--top-k <n>] [--threshold <t>]
Parameters
| Parameter | Required | Default | Description |
|---|---|---|---|
| query | Yes | - | The comprehensive search query |
| --top-k, -k | No | 5 | Number of results (1-20) |
| --threshold, -t | No | 0.3 | Minimum relevance score (0.0-1.0) |
| --source-types | No | - | Filter by source type (doc,code,test) |
| --languages | No | - | Filter by programming language |
| --file-paths | No | - | Filter by file path patterns (wildcards) |
| --scores | No | false | Show individual vector/BM25 scores |
| --full | No | false | Show full text content |
| --json | No | false | Output as JSON |
| --url | No | from config | Server URL (env: AGENT_BRAIN_URL) |
How Multi-Mode Works
- BM25 Search: Finds exact term matches
- Vector Search: Finds semantically similar content
- Graph Search: Finds related entities and relationships
- RRF Fusion: Combines results using Reciprocal Rank Fusion
RRF_score(d) = Σ 1/(k + rank_i(d))
Where k is a constant (typically 60) and rank_i(d) is the rank of document d in result list i.
Execution
Pre-flight Check
# Verify server is running and capabilities
agent-brain status
Multi-mode works best with all indices available:
- BM25 index: Built during indexing
- Vector index: Requires embedding provider
- Graph index: Requires
ENABLE_GRAPH_INDEX=true
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 First seen · 277 lines · 15 tokens per session scan A 8a4dd51e26b7
agent-brain-multi is a command published in the GitHub repository SpillwaveSolutions/agent-brain (119 stars, last pushed 27d ago), licensed MIT. It adds 15 tokens to every session and 1,878 once invoked, about $0.0001 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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