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 skills add ZahiriNatZuke/local-delegate --skill delegacion-localgit clone --depth 1 https://github.com/ZahiriNatZuke/local-delegateWrote 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/zahirinatzuke/local-delegate/delegacion-local)<a href="https://agentmods.dev/skills/zahirinatzuke/local-delegate/delegacion-local"><img src="https://agentmods.dev/badge/skills/zahirinatzuke/local-delegate/delegacion-local/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/skills/zahirinatzuke/local-delegate/delegacion-local"><img src="https://agentmods.dev/badge/skills/zahirinatzuke/local-delegate/delegacion-local.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 | $0.00137 | $0.01570 |
| Opus 5 | $0.00068 | $0.00785 |
| Sonnet 5 | $0.00027 | $0.00314 |
| Haiku 4.5 | $0.00014 | $0.00157 |
Grade A, and why
delegacion-local 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.
How it starts
The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Delegación a modelos locales (MCP local-delegate)
Tienes un servidor MCP (local-delegate) que expone modelos corriendo en una GPU propia
(vía llama-swap, Ollama, LM Studio o vLLM) como herramientas texto/imagen→texto. Delegar
a ellas conserva cuota de la suscripción: la generación verbosa y los inputs grandes (o
una imagen entera) se quedan fuera de tu contexto.
Regla de oro
¿Puedo describir el paso en UNA frase con un formato de salida explícito? → sí → usa una tool
local_*. → no (necesita razonamiento, arquitectura, criterio, multi-fuente) → hazlo tú.
El mayor ahorro: path en vez de text
Para archivos/documentos grandes, pasa path (no leas el archivo tú primero). Las
tools que aceptan path leen el archivo del lado del servidor, así el contenido
completo nunca entra a tu contexto — solo recibes el resultado corto.
El coste de no delegar
Leer un archivo de 100 KB con Read cuesta ≈ 25 000 tokens de tu contexto. La misma
tarea con local_summarize(path=…) cuesta ≈ 200 tokens (solo el resumen que vuelve).
Esa diferencia es la que se pierde cada vez que se lee un archivo grande a mano en vez
de delegarlo.
Catálogo de tools
| Tool | Cuándo | Args clave | Devuelve |
|---|---|---|---|
local_summarize |
Resumir texto o archivo largo | path o text, max_words |
Resumen (prosa) |
local_classify |
Etiquetar en categorías fijas | text, labels[] |
Una etiqueta |
local_extract |
Sacar campos estructurados | fields[], path o text |
JSON |
local_boilerplate |
Generar código repetitivo | spec, language, target (ruta absoluta), overwrite? |
Recibo: ruta y tamaño (el código va al archivo, no a tu contexto) |
local_delegate |
Escape genérico texto→texto | task, input, output_format, model?, chunk? |
Texto |
local_lint_summary |
Resumir salida de lint/tests/CI | path o text, max_words |
Resumen agrupado por archivo |
local_commit_msg |
Mensaje de commit desde un diff | diff o path, style? |
Mensaje (revísalo siempre) |
local_translate |
Traducir texto o archivo | target_lang, text o path |
Traducción |
local_explain_code |
Explicar qué hace un código | code o path, question? |
Explicación (prosa) |
local_describe_image |
Describir una imagen o responder una pregunta sobre ella | path, question? |
Descripción (prosa) |
local_status |
Diagnóstico de solo lectura | — | Backend/catálogo/log/VRAM |
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 Changed · +1 lines 32f928beb99f
- 10d ago First seen · 90 lines · 137 tokens per session scan A 3241b4380c4b
delegacion-local is a skill published in the GitHub repository ZahiriNatZuke/local-delegate (5 stars, last pushed yesterday), licensed MIT. It adds 137 tokens to every session and 1,570 once invoked, about $0.0007 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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