Borrowing it
Nothing to install: this file belongs to 1cFE/fusion-tea. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/1cFE/fusion-tea/main/.agents/skills/analyze-models/SKILL.mdgit clone --depth 1 https://github.com/1cFE/fusion-teaWrote 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/1cfe/fusion-tea/analyze-models)<a href="https://agentmods.dev/skills/1cfe/fusion-tea/analyze-models"><img src="https://agentmods.dev/badge/skills/1cfe/fusion-tea/analyze-models/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/1cfe/fusion-tea/analyze-models"><img src="https://agentmods.dev/badge/skills/1cfe/fusion-tea/analyze-models.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 | $0.00020 | $0.01190 |
| Opus 5.5 | $0.00008 | $0.00476 |
| Sonnet 5.5 | $0.00004 | $0.00238 |
| Haiku 4.5 | $0.00002 | $0.00119 |
Grade A, and why
analyze-models 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 24d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Before executing this skill, read .agentic-mbse/claude.md in Claude Code or .agentic-mbse/codex.md in Codex. Resolve supporting paths from this skill’s installed directory; keep generated outputs in the project or a temporary directory. Read referenced skills from .agents/skills/<name>/SKILL.md when their guidance is needed.
Analyze Models Command
Purpose: UNDERSTAND current model state — structure, compliance, and health indicators.
Input: User-specified analysis scope (which models, which aspects)
Output: work/analysis/YYYYMMDD-HHMMSS_topic.md
This is internal analysis — examining what's already built, not exploring external sources (that's /research). It produces operational intelligence: reports that inform what to work on next, where debt is accumulating, and whether the models meet project standards.
When invoked without a scope, ask what the user wants to analyze and suggest options: full project health, a specific package, compliance audit, or debt inventory.
Skills Referenced
- project-structure: Library vs designs separation, file organization, 4-directory model. Consult when analyzing package structure and cross-file dependencies.
- model-validation: Quality pyramid, validation levels, CLI usage. Consult when computing health indicators and running validation checks.
Process
1. Define Scope
Ask the user what to analyze. Three common scopes:
- Full project health: All models, all aspects — structure, compliance, health
- Package-focused: A specific directory (e.g.,
models/library/calculations/power_balance/) - Aspect-focused: One concern across all models (e.g., "which PR-XXX rules are violated?", "what has no test coverage?")
Confirm scope before proceeding. For large projects, a focused scope produces more actionable results.
2. Analyze
Run the applicable analyses in parallel using sub-agents for efficiency — spawn Explore agents to inventory model files, check compliance, and scan for debt markers concurrently. Not all analyses apply to every scope — pick the relevant ones.
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.
- 24d ago Changed · +4 lines eb5025950e73
- 1mo ago First seen · 98 lines · 20 tokens per session scan A 6c2dcd3496b6
analyze-models is a skill published in the GitHub repository 1cFE/fusion-tea (5 stars, last pushed 24d ago), licensed MIT. It adds 20 tokens to every session and 1,190 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-29.
analyze-models compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| analyze-models1cFE/fusion-tea | Skill | 5 | 24d ago | MIT | A | 20 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |