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 derekrbreese/fantasy-football-skills --skill trade-evaluationgit clone --depth 1 https://github.com/derekrbreese/fantasy-football-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/derekrbreese/fantasy-football-skills/trade-evaluation)<a href="https://agentmods.dev/skills/derekrbreese/fantasy-football-skills/trade-evaluation"><img src="https://agentmods.dev/badge/skills/derekrbreese/fantasy-football-skills/trade-evaluation/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/derekrbreese/fantasy-football-skills/trade-evaluation"><img src="https://agentmods.dev/badge/skills/derekrbreese/fantasy-football-skills/trade-evaluation.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 | $0.00123 | $0.02322 |
| Opus 5 | $0.00062 | $0.01161 |
| Sonnet 5 | $0.00025 | $0.00464 |
| Haiku 4.5 | $0.00012 | $0.00232 |
Grade A, and why
trade-evaluation 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 12d 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trade Evaluation: Two-Sided Assessment
Judge a specific trade from both rosters' perspectives. Raw player value is the start, not the verdict — value only counts when it reaches a starting lineup.
Step 1: Load context
Read leagues.md from the project root first — the fields that matter here are scoring, starting slots, roster/bench size, playoff weeks, trade deadline, and whether trades face a veto vote. If the file is missing or blank, ask and suggest running fantasy-league-setup:league-config. If more than one league is defined, use the one marked (default).
Gather both full rosters, both records/standings, and the exact terms. Without the other team's roster only half an evaluation is possible — say so and evaluate provisionally.
For any in-season evaluation, make the timing explicit:
- State the verdict as of a concrete date/time.
- Refresh injuries, suspensions, depth-chart changes, and any same-week news if the inputs are stale or undated. Trade advice that turns on a Tuesday hamstring report should not be delivered as if it were timeless.
- For any consequential injury-based value swing, require both the official team/game status and a second credible source. One unsupported report is not enough to move a player multiple tiers.
Step 2: Who originated the offer? — ask this first
An incoming offer is adversely selected. The proposer built it after looking at both rosters and concluded it helps them. That is not bad faith; it is what proposing means. It does change the prior:
- Offers you received: require a clearly positive edge, not merely an even one. "Even" plus adverse selection is a small loss on average.
- Offers you constructed: even is genuinely fine, and mutual benefit is the normal shape of a good trade.
This is the step most trade advice skips, and it flips the verdict on marginal incoming offers.
Step 3: Raw value pass
Assign each player a rest-of-season value from projections the user supplies, a consensus source read from the browser (name it and the date), or reasoned judgment (label it as such). Sum both sides.
Live platform source routing. Honor a browser the user explicitly names. If leagues.md records a Preferred browser, use that when it has a signed-in session for the platform. Otherwise use any authenticated browser the current assistant already has. For Yahoo league data, prefer an authenticated browser over a connector. If a Yahoo connector returns 403, unauthorized, or an equivalent authorization failure, do not retry it during the same task. For non-Yahoo platforms, use a purpose-built connector when it is available and returns complete current data; otherwise use the browser. Read league rosters, the free-agent pool, standings, transaction history, and any rankings site directly instead of making the user paste them. Timestamp live data and name the source. The session rules from roster-ops apply unchanged: the user's session is the auth; never ask for, read, store, or type credentials; use the visible UI rather than platform endpoints; and stop and hand back on any login, 2FA, captcha, consent, or unusual-activity screen. If no usable live source exists, state the access gap and do not fabricate league-specific analysis.
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.
- 12d ago First seen · 89 lines · 123 tokens per session scan A 14e74f94f9dc
trade-evaluation is a skill published in the GitHub repository derekrbreese/fantasy-football-skills (4 stars, last pushed 28d ago), licensed MIT. It adds 123 tokens to every session and 2,322 once invoked, about $0.0006 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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