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 Quinoto-Tech/QuinotoSpec --skill quinotospec-retrospectivegit clone --depth 1 https://github.com/Quinoto-Tech/QuinotoSpecWrote 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/quinoto-tech/quinotospec/quinotospec-retrospective)<a href="https://agentmods.dev/skills/quinoto-tech/quinotospec/quinotospec-retrospective"><img src="https://agentmods.dev/badge/skills/quinoto-tech/quinotospec/quinotospec-retrospective/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/quinoto-tech/quinotospec/quinotospec-retrospective"><img src="https://agentmods.dev/badge/skills/quinoto-tech/quinotospec/quinotospec-retrospective.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00044 | $0.01209 |
| Opus 5.5 | $0.00018 | $0.00484 |
| Sonnet 5.5 | $0.00009 | $0.00242 |
| Haiku 4.5 | $0.00004 | $0.00121 |
Grade A, and why
quinotospec-retrospective 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 1mo 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Objetivo: aprender de las propuestas completadas para mejorar la adopción de la metodología, la precisión de estimaciones y la calidad del proceso.
Precondiciones
.quinoto-spec/proposals/_archived/debe contener al menos 1 propuesta archivada.- Debe existir changelog (v1 en
.quinoto-spec/quinoto-spec-changelog.mdo v2 en.quinoto-spec/changelog/). - Si no hay propuestas archivadas, el workflow muestra un mensaje y sugiere completar una propuesta primero.
Paso 1 — Recolectar datos de propuestas completadas
- Listar todas las carpetas en
.quinoto-spec/proposals/_archived/. - Para cada propuesta archivada, leer
proposal.mdy extraer:- Título, Prioridad, Complejidad
- Servicios Afectados
- Estado (debe ser
✅ Completadao🔴 Archivada)
- Contar el total de propuestas completadas en el período.
Paso 2 — Extraer métricas del changelog
- Ejecutar
@quinotospec.changelog-view --jsonpara obtener todas las entradas (auto-detecta formato v1/v2). - Para cada propuesta archivada, filtrar sus entradas del JSON resultante.
- Extraer de cada entrada:
**Tiempo Ahorrado**: ~{Tiempo Humano} (IA: {Tiempo IA} vs Humano: {Tiempo Humano})
- Calcular métricas agregadas:
| Métrica | Cálculo |
|---|---|
| Tiempo total ahorrado | Suma de todos los Tiempo Humano |
| Velocidad promedio | Tareas completadas / días del período |
| Precisión de estimaciones | % de tareas donde estimado ≈ real |
| Propuestas por mes | Conteo absoluto |
Paso 3 — Identificar patrones
- Archivos más modificados: agrupar por archivo, contar frecuencia.
- Servicios más impactados: agrupar por servicio, contar frecuencia.
- Tipos de cambio más frecuentes: feature vs bugfix vs refactor.
- Tareas con rollback: buscar entradas de changelog que mencionen "rollback" o "revertir".
- Tareas con mayor tiempo ahorrado: top 3 por
Tiempo Humano.
Paso 4 — Solicitar input cualitativo (opcional)
Si NO se usa --quick, hacer 3 preguntas al usuario:
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.
- 1mo ago First seen · 138 lines · 44 tokens per session scan A eae39928dd9a
quinotospec-retrospective is a skill published in the GitHub repository Quinoto-Tech/QuinotoSpec (21 stars, last pushed yesterday), licensed MIT. It adds 44 tokens to every session and 1,209 once invoked, about $0.0002 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 2026-09-03.
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