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.
npx agentmods add instructions/monkey1wizard/golem-agents-legion/copilot-instructionsgit clone --depth 1 https://github.com/monkey1wizard/Golem-Agents-LegionWrote 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/instructions/monkey1wizard/golem-agents-legion/copilot-instructions)<a href="https://agentmods.dev/instructions/monkey1wizard/golem-agents-legion/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/monkey1wizard/golem-agents-legion/copilot-instructions.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 | $0.01805 | $0.01805 |
| Opus 5 | $0.00903 | $0.00903 |
| Sonnet 5 | $0.00361 | $0.00361 |
| Haiku 4.5 | $0.00180 | $0.00180 |
Grade A, and why
Golem-Agents-Legion copilot-instructions.md 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 today.
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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generated by
/gal initfor GitHub Copilot. Do not edit manually.
Copilot Instructions
Named Workflow Obedience
Binding. When the user invokes any GAL named workflow — $gal-pipeline, $gal-finalize, $gal-status, $deep-planning, $refining-plan, $plan-to-prompt — or expresses repo-work intent (implement, plan, finalize, review, 實作, 規劃, 跑 pipeline, finalize), your first action MUST be to load and execute the corresponding SKILL.md before taking any action. Generic autonomous coding, batch edits, or a summary response that bypasses the named workflow is a named workflow obedience failure.
Critical Stop Rules
The GAL critical runtime pack — binding stop rules for headless and interactive runs alike:
$gal-pipeline: the first implementation edit is gated ongal pipeline-preflight <prompt> --receipt <path>returningpass— make no edit before that.- When more than one plan is active, require an explicit
'#file:<prompt>'path. Never auto-select the first active-plan row. - If a receipt/log write fails under sandbox denial, STOP and rerun the exact
galcommand after approval — do not fall back to role-playing pipeline phases in chat. - The goal-backward verify pass is orchestrator-owned and always runs in-process. It is never a dispatch phase.
Working Hours
Interactive/chat work and direct golem calls honor Wrap-up Time and Hard Stop when enabled. /gal pipeline execution itself is exempt. Read plugins/gal-core/conventions/working-hours.md for the current rule before assuming either state.
Cold Start Order
.dev/project.md2..dev/state.md3. the active plan's*.prompt.md, resolved via the.dev/state.mdActive Plans row — never a hardcoded transient filename 4.docs/manual.md/plugins/gal-core/workflows/coding.mdonly when the current task needs them.
Project Context
What This Is
GAL is a document-driven AI working system for solo developers who want a stable workflow across GitHub Copilot, Antigravity CLI, Codex CLI, and Claude Code. It combines a small control-plane command surface, specialized golem agents, and repo-local state files so planning, implementation, testing, review, and research can move between tools without losing context.
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.
- today First seen · 112 lines · 1,805 tokens per session scan A 7fcd5d0e9fb3
Golem-Agents-Legion copilot-instructions.md is an instructions file published in the GitHub repository monkey1wizard/Golem-Agents-Legion (15 stars, last pushed 2d ago), licensed MIT. It adds 1,805 tokens to every session, about $0.0090 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 2026-09-04.
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