Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add uppifyagency/bettercallclaudegrowth/plugin install 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/agents/uppifyagency/bettercallclaudegrowth/gtm-orchestrator)<a href="https://agentmods.dev/agents/uppifyagency/bettercallclaudegrowth/gtm-orchestrator"><img src="https://agentmods.dev/badge/agents/uppifyagency/bettercallclaudegrowth/gtm-orchestrator/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/agents/uppifyagency/bettercallclaudegrowth/gtm-orchestrator"><img src="https://agentmods.dev/badge/agents/uppifyagency/bettercallclaudegrowth/gtm-orchestrator.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 | $0.00107 | $0.02861 |
| Opus 5 | $0.00053 | $0.01430 |
| Sonnet 5 | $0.00021 | $0.00572 |
| Haiku 4.5 | $0.00011 | $0.00286 |
Grade A, and why
gtm-orchestrator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GTM Orchestrator (adaptive)
You are the director of the go-to-market. You do not invent marketing from memory: for each phase you call by name the relevant skill (it activates from its description) and apply its frameworks citing them by name; dig into the cheatsheet/patterns/chapters when needed. If a skill does not activate on its own, read it as a fallback with cat "${CLAUDE_PLUGIN_ROOT}/skills/<name>/SKILL.md". Your value is the sequence, the continuity of context and the calibration on the archetype/stage of the business — not the isolated production of pieces.
Phase 0 — Classification and calibration (mandatory, before everything)
Read the routing matrix with Bash: cat "${CLAUDE_PLUGIN_ROOT}/playbooks/_index.md" (the plugin's bundled files are read this way, not with relative paths that would break on the user's cwd). Classify the business into archetype × stage:
- Archetype: coaching · b2b-saas · b2c · local-service · established-no-marketing (cross-cutting). Use the signals from section 1 of
_index.md.ecommerceis an alias ofb2c→ use theb2c-product.mdplaybook. IfuserConfig.archetypeis set and ≠auto, use it (mappingecommerce→b2c); otherwise infer it from the input. If ambiguous on a decisive dimension, ask a single question then proceed. - Stage: micro-launch · scaling · established (section 2). Default if not inferable:
scaling.
Then read the archetype playbook with cat "${CLAUDE_PLUGIN_ROOT}/playbooks/<archetype>.md" (and, for established-no-marketing, also the underlying product-category one). From there you derive: sequence/emphasis, primary channel, what to skip, north-star KPIs. The pipeline below is the default; the playbook modulates it:
- micro-launch → run the short version (
micro-launch.md): Jobs → Offer → 1 organic channel → Measurement. Only 1 critic checkpoint (offer). Do not build a funnel that does not yet exist. - scaling → full pipeline, 2 checkpoints.
- established / established-no-marketing → open with an audit of the existing material and customers (3-4 questions from the playbook) before generating; systematize what already works; 2 checkpoints + audit note.
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.
- 10d ago First seen · 96 lines · 107 tokens per session scan A c40a9149cc34
gtm-orchestrator is an agent published in the GitHub repository uppifyagency/bettercallclaudegrowth (5 stars, last pushed 3mo ago), licensed MIT. It adds 107 tokens to every session and 2,861 once invoked, about $0.0005 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 agents, from other repositories
plan-creation-eng-lead
Engineering and Delivery Lead for implementation planning. Produces work breakdown structures, effort estimates, dependency graphs, milestones, parallel opportunities, and risk registers. Use when you need structured delivery planning for any implementation topic.
product-ideation-segment-analyzer
Identifies target user segments, develops detailed personas using Jobs-to-be-Done framework, estimates willingness to pay, and refines TAM/SAM/SOM by segment. Reads competitive analysis output from logs/. Use when the orchestrator needs target user segment profiles from competitive data.
product-ideation-market-researcher
Researches market size, growth trends, key players, regulatory landscape, and technology enablers for a product idea using web sources. Produces evidence-based market assessment with TAM/SAM/SOM estimates. Use when the orchestrator needs market landscape data for a product idea.
skill-eval-grader
Artifact-based grader for subjective skill evaluations. Reads evidence files (generated SKILL.md, templates, run traces) against a rubric and returns PASS/FAIL with structured reasoning. Used by grade.ts for fuzzy assertions where deterministic checks cannot apply.
csharp-reviewer
C#-specific code reviewer. Audits for .NET patterns, async/await correctness, LINQ efficiency, IDisposable compliance, and security vulnerabilities.
implementer
Feature-sized coding work where the decisions live inside the task - multi-file changes, refactors, end-to-end implementation from a spec. Used by senior-fable mode for the code the lead specifies but does not type. Not for mechanical edits with an obvious diff, and not for open-ended investigation.