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/uppifyagency/bettercallclaudegrowthWrote 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/uppifyagency/bettercallclaudegrowth/gtm-content)<a href="https://agentmods.dev/commands/uppifyagency/bettercallclaudegrowth/gtm-content"><img src="https://agentmods.dev/badge/commands/uppifyagency/bettercallclaudegrowth/gtm-content/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/uppifyagency/bettercallclaudegrowth/gtm-content"><img src="https://agentmods.dev/badge/commands/uppifyagency/bettercallclaudegrowth/gtm-content.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 | $0.00023 | $0.00504 |
| Opus 5 | $0.00012 | $0.00252 |
| Sonnet 5 | $0.00005 | $0.00101 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
gtm-content 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 9d 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 — 29 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/gtm-content - Content strategy and editorial calendar
Apply the doing-content-right skill to the user's input.
Respect userConfig: write in output_language (IT by default), calibrate tone and vocabulary to brand_voice, contextualize everything to the industry, and favor default_channel when choosing distribution channels.
Steps
-
Load the skill. Invoke the
doing-content-rightskill by name (it activates from its description; do not use file paths) and apply its frameworks, going deeper with the cheatsheet, patterns, and the relevant chapter (niche, distribution, SEO, monetization) when needed. -
Apply the frameworks to
$ARGUMENTSand the industry. Do not copy the book's content: use these frameworks by name and adapt them to the concrete case:- Personal Monopoly + niche & positioning → define the defensible niche and the positioning (including the "what for who" in a single sentence).
- distribution channels → select and prioritize the channels consistent with
default_channeland the industry. - SEO → identify the topics with informational intent and the long-tail opportunities.
- audience growth and monetization → indicate the growth lever and the monetization horizon consistent with the positioning.
-
Produce the structured output:
- Content strategy — (a) Niche & positioning; (b) Prioritized distribution channels with rationale; (c) 3-5 editorial pillars anchored to the Personal Monopoly and the industry.
- Editorial calendar — a 4-week table: for each release indicate date/week, pillar, format, channel, angle/title, and intent (informational/awareness/conversion).
Keep the output actionable and faithful to the brand_voice; flag where tactics or metrics from the book (2020) need verification before acting.
Red-team (optional). Invoke the
gtm-criticagent to stress-test the strategy and calendar (is the niche truly defensible? are the pillars anchored to the Personal Monopoly or generic? are the channels consistent with the archetype?), then incorporate the fixes.
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.
- 9d ago First seen · 29 lines · 23 tokens per session scan A 0fbaa8cde74b
gtm-content is a command published in the GitHub repository uppifyagency/bettercallclaudegrowth (5 stars, last pushed 3mo ago), licensed MIT. It adds 23 tokens to every session and 504 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
recall-save
Generate / overwrite .recall/context.md with Recall's local offline summarizer.
notebook-query
Query the notebook knowledge base (SQLite) built by /agy:notebook — precise, grounded, cited. Ask in natural language ("sum the amounts by category", "which docs mention 'Acme Corp'", "build a project timeline") or pass raw SQL. Read-only. Use this when you need exact aggregates/lookups across a document corpus…
ccc-orchestrate
Sequential and tmux/worktree orchestration guidance for multi-agent workflows.
standup
Show a daily standup summary with completed, in-progress, and blocked tasks across all active epics.
design
A command that turns an existing plan into a detailed technical design for building the feature.
audit-project-github
This file contains GitHub integration for /audit-project.