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AB fetch-substack-stats

Pulls substacker's weekly Substack stats directly from the dashboard via Claude-in-Chrome browser automation. Navigates to substack.com/stats, parses the posts table and subscribers table, and produces the same typed WeekExport object that ingest-substack-csv produces — but without requiring a manual CSV export. The writer keeps Chrome signed in to Substack; this skill opens the dashboard in a new tab, reads the rendered stats, closes the tab. Primary data path for the Growth Analyst; ingest-substack-csv is the fallback when browser automation is unavailable. Trigger keywords — fetch stats, Substack dashboard, auto stats, Chrome stats, dashboard scrape, live stats, no CSV.

lyndonkl/claude Agent Skills author: lyndonkl 1 file body ≈ 1 380 tokens Open the sourcegithub.com↗ analyzed 16 h ago

Pulls substacker's weekly Substack stats directly from the dashboard via Claude-in-Chrome browser automation.

As a process B 67/100 · Nearly there — weak spots: when it triggers

ProcedureData and analyticstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
B
67/100
Nearly there
When it triggers w 12
20
Failures and branches w 10
50
Tools and files w 18
60
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 67/100

    • 20When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 32 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1380 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +3Description length 681: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 32 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.