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 ThomasMoreAI/legal-skills-open --skill generar-dictamen-tomimastro069git clone --depth 1 https://github.com/ThomasMoreAI/legal-skills-openWrote 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/thomasmoreai/legal-skills-open/generar-dictamen-tomimastro069)<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/generar-dictamen-tomimastro069"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/generar-dictamen-tomimastro069/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/thomasmoreai/legal-skills-open/generar-dictamen-tomimastro069"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/generar-dictamen-tomimastro069.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 | $0.00122 | $0.02878 |
| Opus 5.5 | $0.00049 | $0.01151 |
| Sonnet 5.5 | $0.00024 | $0.00576 |
| Haiku 4.5 | $0.00012 | $0.00288 |
Grade A, and why
generar-dictamen-tomimastro069 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 8d 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Procedimiento de Autoevaluación Formativa y Control de Calidad Interno (autoevaluacion)
Universidad Tecnológica Nacional — Facultad Regional Mendoza
Tecnicatura Universitaria en Programación (TUP)
Trabajo Final de Graduación: Orquestador de Seguridad: Fuzzing Automatizado de Aplicaciones Web
Equipo de Autores: Tomás Mastropietro, Cristian Krahulik, Juan Segura
Este procedimiento operativo guía al asistente en la elaboración de un Informe Interno de Autoevaluación Académica y Control de Calidad en formato Markdown, alojado en docs/autoevaluacion/autoevaluacion-v{N}.md.
Su propósito es netamente formativo y pedagógico: permite al equipo de alumnos auditar exhaustivamente su propio informe de tesina aplicando los 5 criterios de tolerancia cero antes de someterlo formalmente a la consideración del Tribunal Evaluador de la UTN FRM.
Nota Institucional de Alcance:
Este informe constituye una herramienta interna de trabajo de los alumnos tesistas. No representa ni sustituye a los dictámenes oficiales de corrección ni a las resoluciones emitidas por la cátedra o por el Tribunal Evaluador docente de la facultad.
1. Parámetros de Entrada y Nomenclatura
- Definir el correlativo de la autoevaluación:
- Archivo de salida:
docs/autoevaluacion/autoevaluacion-v{N}.md(donde{N}es la versión del informe analizada, ej.autoevaluacion-v19.md).
- Archivo de salida:
- Definir la letra de tipificación interna de hallazgos:
- La letra permite ordenar las oportunidades de mejora detectadas por los alumnos (ej. serie $I$ para mejoras internas, o correlativo a revisar).
- Insumos necesarios:
- Informe de tesina en revisión (
docs/informe/capitulos/*.typo compiladoinforme-v{N}.pdf). - Último Dictamen Oficial emitido por la cátedra (
docs/dictamen/Dictamen-{N}-oficial.pdf). - Resultados del recálculo aritmético independiente de las 14 tablas cuantitativas.
- Informe de tesina en revisión (
2. Estructura Obligatoria del Informe de Autoevaluación (8 Ejes de Control Interno)
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.
- 8d ago First seen · 188 lines · 122 tokens per session scan A 3bf56461b827
generar-dictamen-tomimastro069 is a skill published in the GitHub repository ThomasMoreAI/legal-skills-open (89 stars, last pushed 5d ago), licensed Apache-2.0. It adds 122 tokens to every session and 2,878 once invoked, about $0.0005 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 2026-10-09.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…