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 dfs_lineup_buildinggit 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/dfs_lineup_building)<a href="https://agentmods.dev/skills/danieltomaro13/sportsdata-agents/dfs_lineup_building"><img src="https://agentmods.dev/badge/skills/danieltomaro13/sportsdata-agents/dfs_lineup_building/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/dfs_lineup_building"><img src="https://agentmods.dev/badge/skills/danieltomaro13/sportsdata-agents/dfs_lineup_building.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 | $0.00033 | $0.00491 |
| Opus 5 | $0.00016 | $0.00246 |
| Sonnet 5 | $0.00007 | $0.00098 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
dfs_lineup_building 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
DFS lineup building
Build daily-fantasy lineups: projections in, optimal lineup out — with the judgment calls made explicit.
Before optimising, establish (ask the user what you can't infer)
- Site + contest rules: roster slots, salary cap, scoring system. They differ (DraftKings/FanDuel/local AU sites); never assume.
- Projection source: the user's numbers, or build them from stats (per-game averages adjusted for opponent/pace/minutes). State which you used.
- Contest type: cash games want the highest floor (consistent scorers); GPP tournaments want ceiling + leverage (lower-owned players whose upside separates you from the field).
Using optimize_lineup
- Pass EVERY candidate player with
positions,salary,projection— the tool does all the math (deterministic beam search; near-optimal). lockedforces players in (the user's picks or a stack);excludedremoves injured/benched players. Re-run with different locks to compare builds.- Multi-position eligibility matters: pass all listed positions; "G"/"F"/"UTIL" slots accept their families automatically.
Judgment the optimiser does NOT make (you do, and say so)
- Stacking: correlated players (QB+WR, same-team hitters) raise ceiling for GPP — lock the stack, optimise the rest.
- Late swap / news: confirm lineups against the latest scratchings/injury news before presenting; flag any player whose status is uncertain.
- Ownership leverage: in GPP, an equal-projection pivot at lower ownership is usually the better tournament play.
Honesty rules
- Projections are estimates; report the lineup's projected points as a point estimate, not a promise.
- Always state the slots/cap/scoring you optimised for, and the source of every projection. Advisory only.
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 · 41 lines · 33 tokens per session scan A 5954d72bb291
dfs_lineup_building is a skill published in the GitHub repository DanielTomaro13/sportsdata-agents (5 stars, last pushed 8d ago), licensed MIT. It adds 33 tokens to every session and 491 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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