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/finom/vovk/toolsnpx skills add finom/vovk --skill toolsgit clone --depth 1 https://github.com/finom/vovkWhat 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 | $0.00261 | $0.05890 |
| Opus 5 | $0.00130 | $0.02945 |
| Sonnet 5 | $0.00052 | $0.01178 |
| Haiku 4.5 | $0.00026 | $0.00589 |
Grade A, and why
tools 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 3d 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 — 490 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vovk.ts LLM tools
Vovk produces LLM-consumable tool definitions — { name, description, parameters, execute, … } — via two entry points:
deriveTools({ modules })— turn existing procedures (controllers, RPC modules, OpenAPI mixins) into tools auto.createTool({ name, description, inputSchema?, outputSchema?, execute, … })— hand-build standalone tool, no procedure backing. Use when body is plain code (SDK wrappers, calculators, file ops).
Both shapes interoperable — mix in one array, feed to OpenAI / Anthropic / Vercel AI SDK / MCP servers.
Out of scope: procedure authoring (procedure), @operation for OpenAPI docs (openapi), third-party OpenAPI mixin setup (mixins). MCP server transport / hosting outside Vovk; for Next.js, recommended runtime is mcp-handler npm package — example below.
Import path note. Code samples import from
'vovk-client'— composed client +jstemplate default, re-exported fromnode_modules/.vovk-client. Withtstemplate, import fromcomposedClient.outDir(e.g.@/client). With segmented client, import from@/client/<segment>. Call shape identical. Seerpcskill.
deriveTools — core shape
import { deriveTools } from 'vovk';
import { TaskRPC, PetstoreAPI } from 'vovk-client';
import UserController from '@/modules/user/user-controller';
const { tools, toolsByName } = deriveTools({
modules: { UserController, TaskRPC, PetstoreAPI },
});
modules accepts record of:
- Controllers — execute via
.fn()in-process, no HTTP. - RPC modules (from
vovk-clientor@/client[/segment]per layout) — execute via HTTP using standard fetcher. - OpenAPI mixins (same client surface) — execute via HTTP against third-party API. See
mixinsskill.
Each module yields one tool per procedure with @operation schema, not hidden.
Return shape
const { tools, toolsByName } = deriveTools({ modules: { TaskRPC } });
// Array — feed to LLM SDKs
llm.chat({ tools: tools.map(t => ({ name: t.name, description: t.description, input_schema: t.parameters })) });
// Map — dispatch tool calls without scanning
const result = await toolsByName[call.name].execute(call.arguments);
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.
- 3d ago First seen · 490 lines · 261 tokens per session scan A 45d4e4c60634
tools is a skill published in the GitHub repository finom/vovk (52 stars, last pushed 6d ago), licensed MIT. It adds 261 tokens to every session and 5,890 once invoked, about $0.0013 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.
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