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 DanielTomaro13/sportsdata-agents --skill reading_line_movementgit clone --depth 1 https://github.com/DanielTomaro13/sportsdata-agentsWrote 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/danieltomaro13/sportsdata-agents/reading_line_movement)<a href="https://agentmods.dev/skills/danieltomaro13/sportsdata-agents/reading_line_movement"><img src="https://agentmods.dev/badge/skills/danieltomaro13/sportsdata-agents/reading_line_movement/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/danieltomaro13/sportsdata-agents/reading_line_movement"><img src="https://agentmods.dev/badge/skills/danieltomaro13/sportsdata-agents/reading_line_movement.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 | $0.00032 | $0.00349 |
| Opus 5 | $0.00016 | $0.00175 |
| Sonnet 5 | $0.00006 | $0.00070 |
| Haiku 4.5 | $0.00003 | $0.00035 |
Grade A, and why
reading_line_movement 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 11d 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.
What it actually says
Reading line movement
query_line_movement gives the change-point series. What it means:
- Steam (price shortening): money agrees with the side. If your model's edge was computed at the OLD price, it may already be consumed — recompute at the current price before calling it value. Fast multi-book steam usually means sharp/insider flow.
- Drift (price lengthening): the market disagrees with your model. Drift into your pick raises the price (more apparent edge) while telling you informed money leans the other way — report BOTH facts, never just the bigger edge number.
- The close is the benchmark: the most informed market state. Persistent edge vs the close (CLV) is the strongest evidence a process works (quant_concepts). When an event is settled, compare entry vs close in the report.
- No movement = one first-sighting row, not "no data" — the price simply hasn't changed since capture began. Say which.
- Cross-book divergence: one book lagging a market-wide move is the classic value window — flag the book and the lag explicitly when the series shows it.
Always state the capture cadence honestly: a 5-minute feed cannot see intra-minute steam, and gaps in the series are coverage gaps, not calm markets.
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.
- 11d ago First seen · 27 lines · 32 tokens per session scan A 367a8b837886
reading_line_movement is a skill published in the GitHub repository DanielTomaro13/sportsdata-agents (5 stars, last pushed 8d ago), licensed MIT. It adds 32 tokens to every session and 349 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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