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 agentmods add skills/mathematic-inc/earl/create-templatenpx skills add mathematic-inc/earl --skill create-templategit clone --depth 1 https://github.com/mathematic-inc/earlWhat 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 | $0.00045 | $0.02568 |
| Opus 5 | $0.00023 | $0.01284 |
| Sonnet 5 | $0.00009 | $0.00514 |
| Haiku 4.5 | $0.00005 | $0.00257 |
Grade A, and why
create-template 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.
How it starts
The opening of the file, as written. The whole thing — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Template
Creates an Earl HCL template file for a specific service and protocol. Each template defines the commands, parameters, authentication, and protocol shape for one provider.
Process
- Discover — understand what service and command to build
- Infer protocol — map the user's description to one of Earl's 5 protocols
- Load reference — read the protocol reference for HCL shapes and patterns
- Write template — create the HCL file
- Review — show the user the complete template before running it
- Validate — run
earl templates validate - Secrets — print checklist for the human to set secrets
- Verify — run a test
earl call
Phase 1: Discover Intent
If the request doesn't name a provider, command, and protocol, ask one question:
"What service do you want to call, and what should the command do? For example: 'Call the GitHub API to create an issue' or 'Query my PostgreSQL database for user records'."
Check for pre-built templates first
Earl ships with 26 ready-made provider templates. If the user names a known service, check whether it is already imported before offering to import it:
earl templates list
Check the list carefully:
- If the specific command needed is already present (e.g.
github.create_issueappears in the list), skip the import and go directly to Phase 7 to set any missing secrets. - If the provider is imported but the specific command is not in the list (e.g.
githubcommands appear but notgithub.create_issue), skip the import and proceed to custom template authoring (phases 2–6) to add the missing command to the existing file. - If the provider is not imported at all, offer to import the pre-built template:
# Available: github, stripe, slack, notion, openai, anthropic, recall_ai, discord, gitlab, jira, linear,
# pagerduty, twilio, sendgrid, cloudflare, vercel, render, shopify, hubspot,
# mailchimp, datadog, sentry, airtable, auth0, supabase, resend
earl templates import https://raw.githubusercontent.com/mathematic-inc/earl/main/examples/<provider>.hcl
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.
- 2d ago First seen · 274 lines · 45 tokens per session scan A 8017aa8d9912
create-template is a skill published in the GitHub repository mathematic-inc/earl (113 stars, last pushed 6d ago), licensed Apache-2.0. It adds 45 tokens to every session and 2,568 once invoked, about $0.0002 per session on Opus 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 2026-08-30.
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