himalaya

A workflow guide for using Himalaya inside Stram, including readiness checks, planning, approvals, and local artifacts. Himalaya is the specific tool or service this skill supports.

In plain words
What is it for?
Use it for Himalaya planning, execution, verification, troubleshooting, and creating drafts or other artifacts.
Why use it?
It provides a controlled process for checking setup and preparing actions before anything is submitted to an external service.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/codeinfinity1/stram/himalaya
Any agent
npx skills add CodeInfinity1/Stram --skill himalaya
Clone the repo
git clone --depth 1 https://github.com/CodeInfinity1/Stram

Made for: Claude Code, Codex.

Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 482 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 83% 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 $0.00035 $0.00482
Opus 5 $0.00017 $0.00241
Sonnet 5 $0.00007 $0.00096
Haiku 4.5 $0.00003 $0.00048

Measured 2d ago against content hash 12e8aa1b6d2f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

himalaya 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 2d 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

83% identical to shop-app — 12 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.

skills/communications/himalaya/SKILL.md · 52 lines

How it starts

The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Himalaya

This is a Stram-native skill. It is authored inside this repository and uses only Stram-owned tools, approval gates, artifacts, and optional dependency records.

When To Use

Use this skill when the user asks for himalaya planning, execution, verification, troubleshooting, or artifact creation inside Stram.

Tool Map

  • tool_search
  • tool_describe
  • capability_surface
  • write_note
  • native_security_policy
  • tool_output_store
  • himalaya_email_operation_prepare
  • channel_message_prepare
  • channel_message_send
  • shopping_comparison_create
  • shopping_comparison_inspect
  • google_workspace_operation_prepare
  • memory
  • provider_registry

Workflow

  1. Clarify the user's concrete himalaya objective, target environment, credentials already configured, and expected artifact or action.
  2. Use tool_search or capability_surface to find the native Stram tools for the domain before choosing a path.
  3. Run safe inspection/readiness steps first and write bounded notes or artifacts under the workspace or data directory.
  4. Prepare drafts, comparisons, finance models, commerce plans, or channel messages as local artifacts before external submission.
  5. Keep purchases, sends, telephony, and account actions approval-gated.
  6. Summarize what ran, what was skipped, what remains blocked, and the exact files or records created.

Safety And Boundaries

  • Do not import, execute, or vendor upstream assistant code for this skill.
  • Do not store raw secrets; store only environment variable names, secret references, or readiness booleans.
  • Use approvals for writes, sends, purchases, desktop control, process launches, provider calls, and destructive operations.
  • Treat personal data, messages, calendars, reminders, contacts, and location data as sensitive.

Verification

  • Record concrete evidence paths or tool outputs before claiming completion.
  • Prefer dry-run or prepared artifacts when credentials, hardware, licenses, or live services are missing.
  • If a provider-specific runtime is not configured, report the missing credential or binary by name and stop before live execution.

Read the full file on GitHub · 52 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. 2d ago First seen · 52 lines · 35 tokens per session scan A 12e8aa1b6d2f

Subscribe to this mod's changes

himalaya is a skill published in the GitHub repository CodeInfinity1/Stram (10 stars, last pushed 22d ago), licensed MIT. It adds 35 tokens to every session and 482 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 83% identical to shop-app, differing in 12 lines, and is treated as a copy.