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 CodeInfinity1/Stram --skill wacli-operationsgit clone --depth 1 https://github.com/CodeInfinity1/StramWrote 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/codeinfinity1/stram/wacli-operations)<a href="https://agentmods.dev/skills/codeinfinity1/stram/wacli-operations"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/wacli-operations/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/codeinfinity1/stram/wacli-operations"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/wacli-operations.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 | $0.00025 | $0.00668 |
| Opus 5.5 | $0.00010 | $0.00267 |
| Sonnet 5.5 | $0.00005 | $0.00134 |
| Haiku 4.5 | $0.00003 | $0.00067 |
Grade A, and why
wacli-operations 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WhatsApp CLI Companion
Purpose
Provide a tightly scoped companion path for explicitly requested WhatsApp CLI operations while keeping normal assistant chat inside the Stram channel gateway.
When To Use
Use this skill only when the user explicitly asks to message someone else on WhatsApp or asks to sync/search WhatsApp history through a local CLI. Do not use this for normal active WhatsApp chats with the assistant.
Tool Map
external_integrations_statusrun_shell_commandchannel_manifestchannel_message_preparechannel_outbox
Workflow
- Check for
wacli. - Authenticate with QR pairing outside the prompt:
wacli authwacli doctor
- For history, run:
wacli sync --follow
- Prefer
channel_message_preparefor message drafts and approval review. - Use
run_shell_commandforwaclisends only when the user explicitly approved exact recipient and exact message/file.
Safety
- Require exact recipient and message text.
- Confirm before sending.
- Use
wacli chats listto resolve a JID, but do not guess from fuzzy names. - Keep QR/session state in the CLI store, not in Stram setup JSON.
Native Implementation Boundaries
- Normal WhatsApp assistant conversations go through
channel-gatewayand Stram channel tools. wacliis a local CLI adapter path invoked throughrun_shell_command, not an imported external reference/third-party runtime dependency.- Missing
wacli, unauthenticated QR state, ambiguous JIDs, or send errors must be reported as blockers.
Search
wacli chats list --limit 20 --query "name or number"
wacli messages search "invoice" --limit 20 --chat <jid>
wacli messages search "invoice" --after 2026-01-01 --before 2026-12-31
Backfill
wacli history backfill --chat <jid> --requests 2 --count 50
Send
Text:
wacli send text --to "+14155551212" --message "Hello. Are you free at 3pm?"
Group:
wacli send text --to "[email protected]" --message "Running 5 min late."
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 · 88 lines · 25 tokens per session scan A 47ec339d82c7
wacli-operations is a skill published in the GitHub repository CodeInfinity1/Stram (11 stars, last pushed 2mo ago), licensed MIT. It adds 25 tokens to every session and 668 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 2026-09-03.
Other skills, from other repositories
ask-agents
Send a task or question to Claude Code and/or Gemini as external subagents and report back what they said. Use when the user asks to ask Claude, ask Gemini, ask both, get a second opinion, split reviewer roles, or compare external agents.
review-plan
Review a proposed plan with a single-pass structured critique and a clear verdict. Use when the user asks to review a plan, stress-test a plan, critique a workflow, identify risks, or improve an execution sequence.
alive:settings
The human wants to adjust how the system behaves — not what it contains, but how it feels. Voice, rhythm, preferences, walnut-level config, full permissions toggleable, named squirrel config, action logging toggle. The system adapting to them. Routes to preferences.yaml or walnut config.yaml depending on scope. For…
lark-contact
A Feishu (Lark) contacts tool for finding users or bots and looking up their profiles and contact details.
oci-services-expert
Expert guidance on Oracle Cloud Infrastructure services, architecture patterns, cost optimization, and deployment strategies. Use when designing on OCI, selecting OCI services, estimating cost, or applying OCI enterprise best practices.
openai-agentkit
Build production multi-agent systems with OpenAI AgentKit and the Agents SDK — orchestration, handoffs, and routines. Use when writing agents against OpenAI's AgentKit/Agents SDK or porting an agent design to the OpenAI stack.