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/epistates/sparx/analyzenpx skills add Epistates/sparX --skill analyzegit clone --depth 1 https://github.com/Epistates/sparXWrote 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/epistates/sparx/analyze)<a href="https://agentmods.dev/skills/epistates/sparx/analyze"><img src="https://agentmods.dev/badge/skills/epistates/sparx/analyze.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 | $0.00045 | $0.01958 |
| Opus 5 | $0.00023 | $0.00979 |
| Sonnet 5 | $0.00009 | $0.00392 |
| Haiku 4.5 | $0.00005 | $0.00196 |
Grade A, and why
analyze 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 3d 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze X Post Performance via Browser
Read real engagement data directly from X's interface and run Phoenix scoring analysis — no manual data entry needed.
Input
The user provides one of:
- A post URL — analyze that specific post
- "recent" — analyze the most recent posts from their profile
- Their X username — navigate to their profile to analyze recent posts
- Nothing — ask what they want to analyze
Process
Step 1 — Get Browser Context
mcp__claude-in-chrome__tabs_context_mcp(createIfEmpty: true)
Create a new tab or reuse an existing x.com tab.
Step 2 — Navigate to the Content
For a specific post URL:
mcp__claude-in-chrome__navigate(url: "<post_url>", tabId: <tab>)
mcp__claude-in-chrome__computer(action: "wait", duration: 3, tabId: <tab>)
For recent posts (navigate to profile):
mcp__claude-in-chrome__navigate(url: "https://x.com", tabId: <tab>)
mcp__claude-in-chrome__computer(action: "wait", duration: 2, tabId: <tab>)
Find and click on the user's profile:
mcp__claude-in-chrome__find(query: "profile link or avatar in sidebar", tabId: <tab>)
Verify logged-in state — take a screenshot:
mcp__claude-in-chrome__computer(action: "screenshot", tabId: <tab>)
If not logged in, stop and tell the user to log in first.
Step 3 — Read Post Metrics
For a specific post:
Navigate to the post and read its engagement metrics. X shows metrics below each post (replies, reposts, likes, bookmarks, views).
- Read the page to find metric elements:
mcp__claude-in-chrome__read_page(tabId: <tab>, filter: "all", depth: 10)
- Or use JavaScript to extract metrics from the post detail page:
mcp__claude-in-chrome__javascript_tool(action: "javascript_exec", text: "
// Extract metrics from post detail page
const metrics = {};
const groups = document.querySelectorAll('[role=\"group\"]');
const ariaLabels = Array.from(document.querySelectorAll('[aria-label]'))
.map(el => el.getAttribute('aria-label'))
.filter(label => label && (
label.includes('repl') || label.includes('repost') ||
label.includes('like') || label.includes('bookmark') ||
label.includes('view') || label.includes('impression')
));
JSON.stringify(ariaLabels);
", tabId: <tab>)
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.
- 3d ago First seen · 212 lines · 45 tokens per session scan A 236f75aadb87
analyze is a skill published in the GitHub repository Epistates/sparX (3 stars, last pushed 5mo ago), licensed MIT. It adds 45 tokens to every session and 1,958 once invoked, about $0.0002 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.
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