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/binary16labs/prime-silo/benny-pilotnpx skills add binary16labs/prime-silo --skill benny-pilotgit clone --depth 1 https://github.com/binary16labs/prime-siloWrote 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/binary16labs/prime-silo/benny-pilot)<a href="https://agentmods.dev/skills/binary16labs/prime-silo/benny-pilot"><img src="https://agentmods.dev/badge/skills/binary16labs/prime-silo/benny-pilot.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 5.1 | $0.00089 | $0.02439 |
| Opus 5 | $0.00044 | $0.01220 |
| Sonnet 5 | $0.00018 | $0.00488 |
| Haiku 4.5 | $0.00009 | $0.00244 |
Grade A, and why
Benny pilot 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.
How it starts
The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use this skill when the user is working in the Bridge cockpit — the one page that unifies the cognitive mesh (memory, documents→knowledge, code, flows, runs). Your job is to be aware of what's on the stage and answer grounded in it, so the operator never has to be their own institutional memory.
load helper
const pilot = await import("/mod/_prime_silo/memoray_client/ext/skills/benny-pilot/benny-pilot.js")- Start with
pilot.readContext()— it returns the live page state{ mode, selection, workspace, lastRun, conformance, route }. Let that tell you which mode the user is in and what they've selected. - All data calls are same-origin through the shell proxies; no endpoint config. If a call reports Memo-Ray offline/disabled, relay the fix (boot
scripts/memoray.ps1, or enable it in the wizard) — do not retry in a loop.
helpers
readContext()-> live{ mode, selection, workspace, lastRun, conformance, route }lifelog(limit?)-> unified activity feed (sessions, artifacts, git commits), newest firstrecentSessions({ agent?, limit? })->[{ id, title, agent, project, timestamp, link }]sessionDetail(id)-> full lineage detail for a selected session{ nodes, edges, … }— use when the operator has clicked a session in the Memory sidebarsearch(query)->{ sessions:[{…, link}], files, actions }runs(limit?)->[{ runId, status, requirement, link }]codeGraph(workspace?)->{ nodes, edges }of the Tree-Sitter code graphknowledgeStats(workspace?)->{ node_types, relationship_types, … }— per-label counts (Document, Concept, Source) for the Documents mode knowledge graphdocumentSources(workspace?)-> de-duplicated list of ingested source document namesknowledgeGraph(workspace?, { page?, pageSize?, showAll? })->{ nodes, edges }page of the document-derived concept graphbridgeLink(mode, id?)-> relative hash fragment for a Bridge mode/selection — format as a markdown link[label](/#/_prime_silo/bridge?mode=memory&id=…), do NOT output bare URL stringsworkspaceFileList(workspace?)-> list files inside the Python backend workspaceworkspaceFileRead(path, workspace?)-> preview/read the contents of a file in the workspace
guidance
- The dispatched prompt already carries the truth: read the
(Bridge context — …)andLive data:lines you were given and answer from them.readContext()often returnsnullfor you (your sandbox runs in the shell window, not the Bridge iframe) — treat it as a bonus, never block waiting for it. - Selection is primary. When the Bridge context says
selected: <title> (id: <uuid>), that is the operator's focus — answer about that item first, then offer the wider list. Use the id to callsessionDetail(id),runs(), etc. - Never demand a selection. "No node selected" is a normal, answerable state, not a blocker. When nothing is selected, describe the whole stage: in
codemode summarize the graph's composition and biggest hubs; indocumentsmode summarize how many documents/concepts exist and name a few sources; inmemory/runssummarize the recent items. Then offer to drill into a node — don't ask the user to pick one first. - Links must be clickable markdown.
bridgeLink()returns a relative hash fragment like#/_prime_silo/bridge?mode=memory&id=…. Always wrap it:[Open in Bridge](/#/_prime_silo/bridge?mode=memory&id=…). Never output bare URL strings. - For Documents, use
knowledgeStats()+documentSources()(fast, reliable) to report what's ingested. Do not rely on the Documents 3D view rendering — its/kg3d/ontologysource can be slow/unavailable; the stats + sources still tell the truth. - If you need to list or read files in the active workspace (paths beginning with
src/incodemode), do NOT usespace.api.fileList/space.api.fileRead— those point at host space dirs and will fail. UseworkspaceFileList()andworkspaceFileRead()instead. - Lead with the answer, then offer the link. Summarize — never dump raw JSON.
- This is read-only/observe-and-explain. The page's own buttons perform actions (Plan, Run, Ingest); your role is to ground, recommend, and link — not to mutate.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 181 lines · 89 tokens per session scan A e4098b062a97
Benny pilot is a skill published in the GitHub repository binary16labs/prime-silo (5 stars, last pushed yesterday), licensed MIT. It adds 89 tokens to every session and 2,439 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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