Borrowing it
Nothing to install: this file belongs to lie5860/openai-search-mcp. 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/lie5860/openai-search-mcp/main/.cursor/commands/trellis-start.mdgit clone --depth 1 https://github.com/lie5860/openai-search-mcpWrote 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/commands/lie5860/openai-search-mcp/trellis-start)<a href="https://agentmods.dev/commands/lie5860/openai-search-mcp/trellis-start"><img src="https://agentmods.dev/badge/commands/lie5860/openai-search-mcp/trellis-start/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/commands/lie5860/openai-search-mcp/trellis-start"><img src="https://agentmods.dev/badge/commands/lie5860/openai-search-mcp/trellis-start.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 | $0.00000 | $0.02213 |
| Opus 5 | $0.00000 | $0.01107 |
| Sonnet 5 | $0.00000 | $0.00443 |
| Haiku 4.5 | $0.00000 | $0.00221 |
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 10d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- trellis-start — 91% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 367 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Start Session
Initialize your AI development session and begin working on tasks.
Operation Types
Operations in this document are categorized as:
| Marker | Meaning | Executor |
|---|---|---|
[AI] |
Bash scripts or file reads executed by AI | You (AI) |
[USER] |
Slash commands executed by user | User |
Initialization
Step 1: Understand Trellis Workflow [AI]
First, read the workflow guide to understand the development process:
cat .trellis/workflow.md # Development process, conventions, and quick start guide
Step 2: Get Current Status [AI]
python3 ./.trellis/scripts/get_context.py
This returns:
- Developer identity
- Git status (branch, uncommitted changes)
- Recent commits
- Active tasks
- Journal file status
Step 3: Read Project Code-Spec Index [AI]
Based on the upcoming task, read appropriate code-spec docs:
For Frontend Work:
cat .trellis/spec/frontend/index.md
For Backend Work:
cat .trellis/spec/backend/index.md
For Cross-Layer Features:
cat .trellis/spec/guides/index.md
cat .trellis/spec/guides/cross-layer-thinking-guide.md
Step 4: Check Active Tasks [AI]
python3 ./.trellis/scripts/task.py list
If continuing previous work, review the task file.
Step 5: Report Ready Status and Ask for Tasks
Output a summary:
## Session Initialized
| Item | Status |
|------|--------|
| Developer | {name} |
| Branch | {branch} |
| Uncommitted | {count} file(s) |
| Journal | {file} ({lines}/2000 lines) |
| Active Tasks | {count} |
Ready for your task. What would you like to work on?
Task Classification
When user describes a task, classify it:
| Type | Criteria | Workflow |
|---|---|---|
| Question | User asks about code, architecture, or how something works | Answer directly |
| Trivial Fix | Typo fix, comment update, single-line change, < 5 minutes | Direct Edit |
| Simple Task | Clear goal, 1-2 files, well-defined scope | Quick confirm → Task Workflow |
| Complex Task | Vague goal, multiple files, architectural decisions | Brainstorm → Task Workflow |
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.
- 10d ago First seen · 367 lines · 0 tokens per session scan A d3fda4b043c1
trellis-start is a command published in the GitHub repository lie5860/openai-search-mcp (13 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,213 tokens. 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 commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.