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 skills add iker-gonzalez/antwork-skills --skill antwork-analyticsgit clone --depth 1 https://github.com/iker-gonzalez/antwork-skillsWrote 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/iker-gonzalez/antwork-skills/antwork-analytics)<a href="https://agentmods.dev/skills/iker-gonzalez/antwork-skills/antwork-analytics"><img src="https://agentmods.dev/badge/skills/iker-gonzalez/antwork-skills/antwork-analytics/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/skills/iker-gonzalez/antwork-skills/antwork-analytics"><img src="https://agentmods.dev/badge/skills/iker-gonzalez/antwork-skills/antwork-analytics.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 | $0.00100 | $0.00873 |
| Opus 5 | $0.00050 | $0.00436 |
| Sonnet 5 | $0.00020 | $0.00175 |
| Haiku 4.5 | $0.00010 | $0.00087 |
Grade A, and why
antwork-analytics 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 9d 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reporting on performance in Antwork
Antwork's analytics tools return BigQuery-style tabular data — { schema: { fields }, rows, rowCount } — not charts. Your job is to pull the right table, then synthesize it into a decision: what's working, on which platform, and what to make more of. Numbers without a recommendation are not a report.
1. Pick the right query — don't pull everything
| Question | Tool | Notes |
|---|---|---|
| "What are my best posts?" | get_performance(limit) |
Lifetime totals per published post (likes, comments, shares, impressions, totalEngagement). Best for rankings. 1–50, default 30. |
| "How is engagement trending?" | get_engagement_history(days) |
Daily series per platform + an "all" aggregate, plus platformTotals/rangeTotals. Best for trends over time. 1–365 days, default 30. |
| "How did this post grow?" | get_post_history(post_id, days?) |
Per-day metrics for one post, both cumulative and daily-delta. Best for single-post lifecycle. Omit days for full history. |
| "When should I post?" | get_optimal_posting_times() |
The workspace's configured times + timezone + selected accounts. |
Start with get_performance for almost any "how am I doing" ask, then drill in with the others.
2. Don't burn live quota by reflex
refresh_post_metrics(post_ids) hits the platform APIs live, right now — ~1–2s per post, max 25, and it spends real platform rate-limit quota. The stored numbers are already refreshed by a nightly cron, so they're at most a day stale. Only call refresh_post_metrics when the user explicitly needs up-to-the-minute numbers (e.g. a post that just went viral this morning), and cap it to the handful of posts that matter.
3. Read the table, then interpret
The rows are raw. Turn them into findings:
- Top performers — rank by
totalEngagement, but look past the number to the pattern. What do the top 3 share — format, hook style, topic, length, platform, posting time? - Per-platform trends — from
get_engagement_historyplatformTotals: which platform is growing, which is flat, where's the effort/return mismatch. - Outliers — one post 5× the median is a signal, not noise. Name what made it land.
- Gaps — platforms with no recent posts, or with traffic but no posting cadence.
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.
- 9d ago First seen · 45 lines · 100 tokens per session scan A 112bda35717b
antwork-analytics is a skill published in the GitHub repository iker-gonzalez/antwork-skills (0 stars, last pushed 2mo ago), licensed MIT. It adds 100 tokens to every session and 873 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.
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