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.
git clone --depth 1 https://github.com/gonzalezpazmonica/saviaWrote 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/commands/gonzalezpazmonica/savia/cache-warm)<a href="https://agentmods.dev/commands/gonzalezpazmonica/savia/cache-warm"><img src="https://agentmods.dev/badge/commands/gonzalezpazmonica/savia/cache-warm/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/commands/gonzalezpazmonica/savia/cache-warm"><img src="https://agentmods.dev/badge/commands/gonzalezpazmonica/savia/cache-warm.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 | $0.00017 | $0.00832 |
| Opus 5.5 | $0.00007 | $0.00333 |
| Sonnet 5.5 | $0.00003 | $0.00166 |
| Haiku 4.5 | $0.00002 | $0.00083 |
Grade A, and why
cache-warm 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- cache-warm — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/cache-warm
🦉 Savia pre-calienta el caché de forma predictiva — por hora, por rol, por sprint.
Cargar perfil de usuario
Grupo: Context Engineering — cargar:
identity.md— rol del usuarioworkflow.md— hora de actividad, eventos del sprint
Ver docs/rules/domain/context-map.md.
Parámetros
--role Pre-calentar contexto del rol actual
--time auto|HH:MM Asumir hora (auto = ahora, o especificar hora)
--lang es|en Idioma del output
Flujo
Paso 1 — Detectar hora y rol
- Leer hora actual o parámetro
--time - Leer rol de
identity.md(PM, Tech Lead, Developer, QA, etc.) - Leer
workflow.mdpara saber si hay eventos hoy (sprint-planning, retro, etc.)
Paso 2 — Mapear contexto probable por hora
Morning (08:00-10:30)
- Daily standup context → sprint status, team workload
- Load:
workflow.md(rutina diaria), team status
Late Morning (10:30-12:00)
- Focus time → project context
- Load: proyecto activo, specs, decisions
Afternoon (13:00-15:00)
- Refinement/grooming
- Load: backlog, reglas negocio, estimación
End of Day (15:00-17:00)
- Reporting → DORA, KPIs
- Load: histórico sprints, métricas
Friday PM (16:00-18:00)
- Sprint review + retro
- Load: sprint items, decision-log, retrospective patterns
Paso 3 — Mapear contexto por rol
PM/Scrum Master
- Always: workflow.md, sprint status, team capacity
- If daily: standup context
- If friday: review + retro context
- If wednesday: backlog grooming context
Tech Lead
- Always: tech-radar, team skills matrix
- If code-focused day: PR reviews, specs, architecture
- If friday: incident postmortems
Developer
- Always: my-sprint, my-focus (current task)
- If morning: standup, task context
- If afternoon: refocus on task, code patterns
QA Engineer
- Always: qa-dashboard
- If pre-release: test plans, bug triage
- If regression day: test cases, known issues
Paso 4 — Ejecutar warm-up
- Identificar ficheros a cargar (máx 5 fragmentos)
- Cargar fragmentos en caché (sin mostrar contenido)
- Registrar warm-up en context-tracking
- Mostrar banner:
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 · 126 lines · 17 tokens per session scan A f15079fe1e3a
cache-warm is a command published in the GitHub repository gonzalezpazmonica/savia (51 stars, last pushed today), licensed MIT. It adds 17 tokens to every session and 832 once invoked, about $0.0001 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 2026-09-06.
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