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cache-warm

cache-warm is a command for Claude Code from gonzalezpazmonica/pm-workspace. It costs 17 tokens per session (832 once invoked), scanned A, a copy of cache-warm, MIT.

A context-loading command that predicts which project information is likely to be useful from the user's role, the time of day and the sprint schedule.

In plain words
What is it for?
Use it to prepare role-specific context for project work, team status, backlog planning, business rules, sprint history and performance metrics.
Why use it?
It reduces the need to search for routine information before starting work. The context changes for activities such as stand-ups, focused project work, backlog refinement and reporting.

Command for Claude Code

Written for Claude Code: installed under .claude/. Also seen: agent in frontmatter.

Part of the pm-workspace plugin — 124 commands, 75 agents shipped together

not rated 50repo 5d ago A scan 17 tokens copy · 100% MIT

Good fit Use it to prepare role-specific context for project work, team status, backlog planning, business rules, sprint history and performance metrics.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/gonzalezpazmonica/pm-workspace/cache-warm
View source ↗ gonzalezpazmonica/pm-workspace
Install

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.

Clone the repo
git clone --depth 1 https://github.com/gonzalezpazmonica/pm-workspace

Made for: Claude Code.

Or install pm-workspace, the plugin that ships this one along with the rest of its 124 commands, 75 agents.

Wrote 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.

agentmods badge for cache-warm

README.md
[![agentmods](https://agentmods.dev/badge/commands/gonzalezpazmonica/pm-workspace/cache-warm/github.svg)](https://agentmods.dev/commands/gonzalezpazmonica/pm-workspace/cache-warm)
Your own site
<a href="https://agentmods.dev/commands/gonzalezpazmonica/pm-workspace/cache-warm"><img src="https://agentmods.dev/badge/commands/gonzalezpazmonica/pm-workspace/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.

agentmods 80×15 button for cache-warm

Your own site · 80×15
<a href="https://agentmods.dev/commands/gonzalezpazmonica/pm-workspace/cache-warm"><img src="https://agentmods.dev/badge/commands/gonzalezpazmonica/pm-workspace/cache-warm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 17 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 832 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 1mo ago against content hash f15079fe1e3a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

Origin

This is a copy

100% identical to cache-warm — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.claude/commands/cache-warm.md · 126 lines

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 usuario
  • workflow.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

  1. Leer hora actual o parámetro --time
  2. Leer rol de identity.md (PM, Tech Lead, Developer, QA, etc.)
  3. Leer workflow.md para 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

  1. Identificar ficheros a cargar (máx 5 fragmentos)
  2. Cargar fragmentos en caché (sin mostrar contenido)
  3. Registrar warm-up en context-tracking
  4. Mostrar banner:

Read the full file on GitHub · 126 lines

Changes

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.

  1. 1mo ago First seen · 126 lines · 17 tokens per session scan A f15079fe1e3a

Subscribe to this mod's changes

cache-warm is a command published in the GitHub repository gonzalezpazmonica/pm-workspace (50 stars, last pushed 5d ago), 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. It is 100% identical to cache-warm, differing in 0 lines, and is treated as a copy.

Memory and contextProductivity
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