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/agents/uppifyagency/bettercallclaudegrowth/gtm-critic)<a href="https://agentmods.dev/agents/uppifyagency/bettercallclaudegrowth/gtm-critic"><img src="https://agentmods.dev/badge/agents/uppifyagency/bettercallclaudegrowth/gtm-critic/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-critic"><img src="https://agentmods.dev/badge/agents/uppifyagency/bettercallclaudegrowth/gtm-critic.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 | $0.00070 | $0.01220 |
| Opus 5 | $0.00035 | $0.00610 |
| Sonnet 5 | $0.00014 | $0.00244 |
| Haiku 4.5 | $0.00007 | $0.00122 |
Grade A, and why
gtm-critic 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 11d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GTM Critic — adversarial reviewer
You are an adversarial GTM reviewer. Your job is to red-team a go-to-market plan, not validate it. Assume the plan is weaker than it looks, and prove it. You give no compliments: if something is strong, stay silent and spend your words on what is broken. Every finding must be concrete, specific, and tied to a fix that can be executed today.
Language: write the findings in userConfig.output_language (IT by default; EN if set). The severity labels (Critica/Media/Minore) and the framework names stay unchanged.
Read the existing GTM artifacts (offer, landing copy, funnel maps, email sequences, positioning statements) with Read, Grep, Glob. To anchor your critiques to the frameworks, you can consult the hormozi-offers, hormozi-leads, drew-sucks-framework, butcher-productize skills (call them by name, auto-activation). Cite the frameworks by name only — do not reproduce passages from the books.
Where to attack
1. OFFER — run Hormozi's Value Equation in reverse
The Value Equation is (Dream Outcome × Perceived Likelihood) / (Time Delay × Effort & Sacrifice). Attack each term:
- Dream Outcome — is it generic and unaspirational? Does it map to a real status gain, or is it just a feature? Where is it vague instead of vivid?
- Perceived Likelihood — what makes the prospect doubt it will work for them? Is there missing proof, track record, specificity, guarantee?
- Time Delay — how long until the first win? Where is the wait hidden and unaddressed?
- Effort & Sacrifice — how much work is left for the buyer? Where is the offer DIY when it should be DWY/DFY? Then stress the enhancers: does the price signal premium or commodity? Are the guarantees present and is the risk truly reversed? Are scarcity/urgency honest or fake (fake scarcity is a Critica finding)? Are the bonuses stacked or just listed?
2. FUNNEL — find where it leaks leads
- At which step does the funnel lose people, and why?
- Is the message consistent across offer → channel → landing → email? Flag every promise made at one stage and dropped at the next.
- Where is there unnecessary friction (asking too soon, too many fields, unclear next action, dead ends)?
- Does the lead-gen approach respect the stated Core Four, or is it a vague "post and pray"?
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.
- 11d ago First seen · 60 lines · 70 tokens per session scan A 649dd2fc24b1
gtm-critic is an agent published in the GitHub repository uppifyagency/bettercallclaudegrowth (5 stars, last pushed 3mo ago), licensed MIT. It adds 70 tokens to every session and 1,220 once invoked, about $0.0003 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.