Trellis is an engineering framework that stores project specifications, tasks, and working memory in a repository so coding agents can follow consistent development practices across sessions. Teams use it to organize AI-assisted planning, implementation, review, and validation across multiple coding platforms. The catalogue entries provide Trellis commands, agents, hooks, skills, instructions, and settings.
Borrowing it
Nothing to install: this file belongs to mindfold-ai/Trellis. 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/mindfold-ai/Trellis/main/.agents/skills/trellis-start/SKILL.mdgit clone --depth 1 https://github.com/mindfold-ai/TrellisWrote 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/mindfold-ai/trellis/trellis-start)<a href="https://agentmods.dev/skills/mindfold-ai/trellis/trellis-start"><img src="https://agentmods.dev/badge/skills/mindfold-ai/trellis/trellis-start.svg" alt="Measured on agentmods" 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 | $0.00073 | $0.00668 |
| Opus 5 | $0.00036 | $0.00334 |
| Sonnet 5 | $0.00015 | $0.00134 |
| Haiku 4.5 | $0.00007 | $0.00067 |
Grade A, and why
trellis-start 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 7d 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.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- 7d ago First seen · 65 lines · 73 tokens per session scan A 79a5ba7a2aff
trellis-start is a skill published in the GitHub repository mindfold-ai/Trellis (14,488 stars, last pushed 10d ago), licensed AGPL-3.0. It adds 73 tokens to every session and 668 once invoked, about $0.0004 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.
Other skills, from other repositories
ospec-goal
Create or advance a full OSpec goal using the current document, task graph, worker, review, and evidence workflow.
ospec
Document-driven OSpec workflow for initialization, change/goal routing, validation, archiving, and durable project knowledge.
ospec-change
Create or advance a lightweight OSpec change using the classic fast workflow.
krypton-execution
Use when executing an approved Krypton plan, GOAL.md, or implementation plan that already defines intent, ownership, contract, cutover, task boundaries, and acceptance evidence. Use for main-agent execution with explorer, plan-reviewer, reviewer, maintainer, or verifier gates.
krypton-planning
Use when a user has a feature request, bugfix, refactor, migration, architecture change, or product goal and needs an implementation plan before coding. Use especially when wrong ownership, duplicate paths, stale contracts, weak evidence, or unclear cutover would make plausible agent work dangerous.
dotcraft-unity
Use when dotcraft-unity MCP, CLI, or unityexecutecsharp is available, or when the user asks to inspect, automate, capture, or debug Unity Editor state, scenes, assets, Console logs, or GameView output. Provides background-first Unity Editor automation through MCP or CLI.