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flaim: Skill for Claude Code

.agents/skills/analyze-matchup/SKILL.md

analyze-matchup is a skill for Claude Code from jdguggs10/flaim. It costs 42 tokens per session (758 once invoked), scanned A, original, MIT.

A fantasy sports matchup report showing the current score, remaining players or games, and a fact-based forecast. A head-to-head matchup is a direct contest against one opponent for a week or scoring period.

In plain words
What is it for?
Use it to review the current week's head-to-head matchup in a supported Flaim league, including points or category formats, remaining games, injuries, and probable starters.
Why use it?
It gathers the relevant league state and schedule information so you can judge how the matchup may finish.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: installed under .agents/ (shared by several agents).

This is jdguggs10/flaim's own configuration. It tells Claude Code how to work on flaim itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything flaim configures →

Part of the flaim-fantasy plugin — 3 skills, 1 MCP server shipped together

not rated 17repo +1 changed 3d ago A scan 42 tokens original MIT
View source ↗ jdguggs10/flaim flaim.app
Reuse

Borrowing it

Nothing to install: this file belongs to jdguggs10/flaim. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/jdguggs10/flaim/main/.agents/skills/analyze-matchup/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/jdguggs10/flaim

Made for: Claude Code.

Or install flaim-fantasy, the plugin that ships this one along with the rest of its 3 skills, 1 MCP server.

Wrote 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.

agentmods badge for analyze-matchup

README.md
[![agentmods](https://agentmods.dev/badge/skills/jdguggs10/flaim/analyze-matchup.svg)](https://agentmods.dev/skills/jdguggs10/flaim/analyze-matchup)
Your own site
<a href="https://agentmods.dev/skills/jdguggs10/flaim/analyze-matchup"><img src="https://agentmods.dev/badge/skills/jdguggs10/flaim/analyze-matchup.svg" alt="Measured on agentmods" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 758 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00042 $0.00758
Opus 5 $0.00021 $0.00379
Sonnet 5 $0.00008 $0.00152
Haiku 4.5 $0.00004 $0.00076

Measured 3d ago against content hash 4831e58d812a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

analyze-matchup 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 3d 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.

.agents/skills/analyze-matchup/SKILL.md · 83 lines

How it starts

The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Analyze Matchup

Assess the user's current head-to-head matchup with a fact-based forecast of what remains.

Scope and data rules

  • Fantasy league data must come from Flaim MCP tools.
  • Use web search for live schedule context, injury updates, probable starters, and remaining real-world games.

Arguments

  • $ARGUMENTS is the requested matchup week.
  • If no argument is provided, use the current week.

Workflow

1. Resolve the target league

  • Reuse a usable successful get_user_session result from this chat. Call it if that context is missing, after a successful league refresh, or when the user confirms account, connection, league-list, or default changes. Do not repeat it just for a follow-up or a switch to another league already in the session result. Follow the tool's error guidance if a lookup fails.
  • If the user explicitly names a league, platform, or sport, honor that.
  • Otherwise treat this as a vague singular request: use defaultLeague when present, otherwise the relevant sport entry in defaultLeagues.
  • If there is no applicable default and multiple leagues still match, ask which league.
  • Call get_league_info for the selected league before matchup analysis so team names, scoring type, owner/team mapping, and roster context are resolved.

2. Determine whether matchup analysis applies

Use get_league_info to identify scoring format:

  • H2H Points: proceed
  • H2H Categories: proceed
  • Roto or any other non-H2H format: explain that this skill only applies to head-to-head leagues and offer standings or roster analysis instead.

3. Pull matchup and roster context

  • Call get_matchups using $ARGUMENTS as the requested week, or the current week if no argument was provided
  • Identify the opponent's team_id from the matchup data before fetching their roster
  • Call get_roster for the user's team
  • Call get_roster for the opponent using that team_id

4. Determine what remains to be played

Use web search to establish remaining real-world volume:

Read the full file on GitHub · 83 lines

Changes

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.

  1. 3d ago Changed 4831e58d812a
  2. 8d ago First seen · 83 lines · 42 tokens per session scan A a01ee5a45004

Subscribe to this mod's changes

analyze-matchup is a skill published in the GitHub repository jdguggs10/flaim (17 stars, last pushed today), licensed MIT. It adds 42 tokens to every session and 758 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 2026-08-30.

Analytics and metricsaichatgptclaudecloudflare-workersmcp-serversports
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