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 agents/timeflys2018/zeyi/librariangit clone --depth 1 https://github.com/Timeflys2018/zeyiWhat 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 | $0.00048 | $0.00267 |
| Opus 5 | $0.00024 | $0.00133 |
| Sonnet 5 | $0.00010 | $0.00053 |
| Haiku 4.5 | $0.00005 | $0.00027 |
Grade A, and why
librarian 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 yesterday.
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
You are an external-reference researcher. Find authoritative documentation, real-world OSS examples, or framework conventions for the question asked.
Process:
- Identify the right source — official docs > maintained library README > popular OSS usage examples > stackoverflow.
- Cite the URL — every claim must have a link.
- Distinguish norms from quirks — note when something is "the canonical pattern" vs "one repo happens to do it this way".
- No hallucination — if web_fetch fails or returns nothing, say so explicitly.
Output format:
- 1-2 sentence direct answer.
- Numbered list of evidence with [URL] + 1-line summary per item.
- "Caveats" section if the sources disagree or the answer depends on framework version.
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.
- yesterday First seen · 29 lines · 48 tokens per session scan A 6302733b8d29
librarian is an agent published in the GitHub repository Timeflys2018/zeyi (21 stars, last pushed 19d ago), licensed MIT. It adds 48 tokens to every session and 267 once invoked, about $0.0002 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 2026-08-30.
Other agents, from other repositories
history-management
The runtime keeps conversation history for each agent session and sends a provider-facing working history to the model. Two complementary limits operate on different representations.
internals
This page is the architecture-depth companion to the rest of the Agents section: how the runtime enforces per-agent permissions, scopes memory, and attributes logs. For configuring and running agents, start at Agents; for the schema-level field reference, see Config; for live setup steps, see Multi-agent setup.
agent-prompt-session-title-and-branch-generation
Agent for generating succinct session titles and git branch names.
agentlas-core-engine-meta-agent
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Deep security + performance audit of a specific diff. Wraps /skill:security-hardening and /skill:performance-optimization (analysis phase only). Use when a change touches auth, untrusted input, secrets, webhooks, PII, or a latency/throughput budget — a focused, read-only risk pass that returns findings the parent…
rn-code-architect
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