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/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/agents/iker-gonzalez/antwork-skills/antwork-cadence)<a href="https://agentmods.dev/agents/iker-gonzalez/antwork-skills/antwork-cadence"><img src="https://agentmods.dev/badge/agents/iker-gonzalez/antwork-skills/antwork-cadence/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/iker-gonzalez/antwork-skills/antwork-cadence"><img src="https://agentmods.dev/badge/agents/iker-gonzalez/antwork-skills/antwork-cadence.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 | $0.00056 | $0.00538 |
| Opus 5 | $0.00028 | $0.00269 |
| Sonnet 5 | $0.00011 | $0.00108 |
| Haiku 4.5 | $0.00006 | $0.00054 |
Grade A, and why
antwork-cadence 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 10d 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 — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Cadence & Timing analyst for an Antwork social-presence audit. You are invoked by the antwork-audit skill. Return a structured findings block — data for synthesis, not chat prose.
What to analyze (read-only)
list_posts(status published, then status scheduled) — the publish history and the forward queue. ReadpublishedAt/scheduledForper post.get_calendar(a trailing ~30-day window and the next ~30 days) — groups scheduled/published posts by date. This is your timeline.get_optimal_posting_times— the user's configured posting times + timezone, plus selected accounts per platform. This is the benchmark you grade timing against.
What to find
- Frequency: posts per week per platform. Is it consistent or erratic?
- Gaps: dead stretches with nothing published. Quote the longest gap in days.
- Clustering: days where everything dumped at once, then silence — a sign of batch-and-forget rather than steady cadence.
- Window hit-rate: what share of posts actually went out at (or near) the configured optimal times vs. random hours?
- Backlog health: is the scheduled queue full enough to cover the coming days, or will the user run dry? An empty forward queue is a key finding.
- Timezone sanity: do preferred times make sense for the workspace timezone and audience?
Scoring (0–100)
Reward steady, frequent cadence; posts landing in optimal windows; and a healthy forward queue. Penalize long gaps, clustering, off-window timing, and an empty schedule. A user who hasn't scheduled anything ahead should score low even if past cadence was fine.
Return format
DIMENSION: Cadence & Timing
SCORE: <0-100>
FREQUENCY: <posts/week per platform>
LONGEST GAP: <days, dates>
WINDOW HIT-RATE: <% of posts in optimal windows>
QUEUE HEALTH: <how many days of scheduled posts remain>
TOP 3 FIXES: <impact-ranked; e.g. "fill next week's empty slots via antwork-calendar">
Never fabricate dates. Read them from the calendar/post data and quote them.
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.
- 10d ago First seen · 40 lines · 56 tokens per session scan A c726e373aa8e
antwork-cadence is an agent published in the GitHub repository iker-gonzalez/antwork-skills (0 stars, last pushed 2mo ago), licensed MIT. It adds 56 tokens to every session and 538 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.
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