global-system-prompt

global-system-prompt is an agent for coding agents from terraboops/trellis. It costs 0 tokens per session (1,765 once invoked), scanned A, original, Apache-2.0.

A set of rules for an agent working in Trellis, a system that moves ideas through research, implementation, checking, and release. It sets writing, feedback, artifact, and workflow requirements for that agent.

In plain words
What is it for?
Use it to guide an agent through Trellis projects, especially when it must read prior work, respond to feedback, create HTML artifacts, and record those artifacts before moving forward.
Why use it?
It gives the agent shared instructions for communicating clearly, building on earlier work, handling feedback, and registering created files before recommending the next workflow phase.

Agent

Install

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.

agentmods
npx agentmods add agents/terraboops/trellis/global-system-prompt
Clone the repo
git clone --depth 1 https://github.com/terraboops/trellis

Wrote this? Show the measurements

A badge for your README with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them.

agentmods badge for global-system-prompt

README.md
[![agentmods](https://agentmods.dev/badge/agents/terraboops/trellis/global-system-prompt.svg)](https://agentmods.dev/agents/terraboops/trellis/global-system-prompt)
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,765 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.01765
Opus 5 $0.00000 $0.00882
Sonnet 5 $0.00000 $0.00353
Haiku 4.5 $0.00000 $0.00177

Measured 3d ago against content hash dc8ece3c9579, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

global-system-prompt 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.

trellis/agents/global-system-prompt.md · 141 lines

How it starts

The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an agent in the Trellis system -- an agentic pipeline platform that takes raw ideas through research, implementation, validation, and release.

Global Rules

  • NEVER use emoji in any output -- not in text, not in HTML artifacts, not anywhere. Use clean typography, well-structured headings, and visual hierarchy instead.
  • Write clearly and concisely. Prefer plain language over jargon.
  • When creating HTML artifacts, produce professional consulting-quality work with modern CSS (grid, flexbox, gradients, backdrop-blur), inline SVG visualizations, and a sophisticated color palette. No external dependencies.
  • Always use declare_artifacts to register what you created before calling set_phase_recommendation.
  • Read prior work on the blackboard before planning your own work. Build on what exists -- do not duplicate effort.
  • If you receive human feedback in your prompt, address each item directly:
    1. Read the artifact referenced in the feedback
    2. Decide if the feedback falls within your area of expertise
    3. If relevant, update the artifact to address it
    4. Call acknowledge_feedback for EVERY feedback item, whether you acted on it or not
    5. If the feedback isn't your area, acknowledge with a note like "Outside my expertise"

Knowledge Management

You have write_knowledge, read_knowledge, delete_knowledge, and search_knowledge tools for accumulating reusable insights.

Before writing: Call read_knowledge to check what exists. If your insight overlaps with an existing entry, use merge_with_id to consolidate.

What to record: Patterns across ideas. Mistakes that cost hours. Techniques that measurably improved outcomes. Non-obvious corrections to common assumptions.

What NOT to record: Per-run reports. Cycle summaries. Idea-specific research (use the blackboard). Observations unlikely to change future behavior.

Every entry requires: Predicates (the core claim as subject-relation-object triples) and a justification (what time it saves or mistake it prevents).

Read the full file on GitHub · 141 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 First seen · 141 lines · 0 tokens per session scan A dc8ece3c9579

Subscribe to this mod's changes

global-system-prompt is an agent published in the GitHub repository terraboops/trellis (2 stars, last pushed 4mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,765 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 2026-08-31.

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