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/lagrowthmachine/gtm-system/weekly-performance-advisornpx skills add LaGrowthMachine/gtm-system --skill weekly-performance-advisorgit clone --depth 1 https://github.com/LaGrowthMachine/gtm-systemWrote 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/lagrowthmachine/gtm-system/weekly-performance-advisor)<a href="https://agentmods.dev/skills/lagrowthmachine/gtm-system/weekly-performance-advisor"><img src="https://agentmods.dev/badge/skills/lagrowthmachine/gtm-system/weekly-performance-advisor.svg" alt="Measured on agentmods" 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 | $0.00215 | $0.08223 |
| Opus 5 | $0.00108 | $0.04111 |
| Sonnet 5 | $0.00043 | $0.01645 |
| Haiku 4.5 | $0.00021 | $0.00822 |
Grade A, and why
weekly-performance-advisor scanned grade A with 1 finding 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
(or the curl one-liner the repo's README provides). Auth is **browser OAuth** — there is **no API How it starts
The opening of the file, as written. The whole thing — 482 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Weekly Performance Advisor
Generate the user's own Weekly Performance Advisor: a two-tab live artifact built from their La Growth Machine (LGM) data. This skill is fully self-contained — every rule needed to detect the environment, score campaigns, classify replies, and fill the dashboard is written below. It references no other document.
Two hard rules, always:
- Only ever show the downloading user's data. Pull exclusively from their connected MCPs. Never inject numbers, campaign names, replies, or examples from anyone else. The template ships empty; it is filled at runtime with their live values. If you cannot pull a value, render the documented empty state — never a placeholder number and never a value borrowed from somewhere else.
- The output is a LIVE ARTIFACT, not a saved HTML file. In Generate mode you fill the template
in memory and render it as a live artifact using the available artifact tool (whatever the
current Cowork build exposes for creating/updating an artifact — do not hard-code a tool name).
On a refresh, update the existing artifact rather than creating a new one. The
assets/dashboard-template.htmlfile is the build source only.
Two modes
- Setup mode (first run, or when LGM isn't connected / no identity chosen yet): interactive. Detect the environment, guide install if needed, ask the scoping questions. Conversational.
- Generate mode (every run once setup is done): run the engine, fill the template, emit the artifact + a short handoff. Apply output discipline here — return the artifact and a few lines of handoff, no step-by-step narration.
If setup was already done in this project (a ./.lgm-wpa/ snapshot exists and LGM is connected),
skip straight to Generate mode; only re-ask a question if something is missing.
Phase 0 — Detect (silent, no questions)
Check your own tool list — do not ask the user what they have installed.
- LGM MCP present? True if tools named
mcp__*for La Growth Machine are available, i.e. any oflist_identities,list_campaigns,get_campaign_stats,get_conversations_to_reply,get_conversation_messages,search_conversations. (In a terminal you could also confirm withclaude mcp listshowing an LGM server, but tool presence is enough — never ask the user.) - CRM / deal MCP present? Is a HubSpot MCP available (deal/company/contact tools)?
campaign-impact-analyzerskill available? (used to build the optional deal/€ layer.)
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 482 lines · 215 tokens per session scan A b554464a865c
weekly-performance-advisor is a skill published in the GitHub repository LaGrowthMachine/gtm-system (34 stars, last pushed 17d ago), licensed MIT. It adds 215 tokens to every session and 8,223 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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