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/ucsandman/dashclaw/copilot-instructionsgit clone --depth 1 https://github.com/ucsandman/DashClawWhat 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 | $0.01691 | $0.01691 |
| Opus 5 | $0.00846 | $0.00846 |
| Sonnet 5 | $0.00338 | $0.00338 |
| Haiku 4.5 | $0.00169 | $0.00169 |
Grade A, and why
DashClaw 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 2d 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DashClaw — GitHub Copilot Instructions
DashClaw is a production Next.js 16 governance runtime for AI agents. Copilot should treat the repo's own CLAUDE.md, PROJECT_DETAILS.md, and docs/architecture/runtime-api.md as the source of truth for architecture and API shape. The section below is the canonical design tone — apply it to any UI, marketing, or copy change.
Design Context
Users
DashClaw has two overlapping audiences who see the same surfaces but read them differently:
- Primary: AI-agent developers and platform engineers. They're integrating DashClaw into Claude Code, Claude Managed Agents, LangChain, CrewAI, OpenAI Agents SDK, custom runtimes, or MCP hosts. They live in terminals, read code more naturally than prose, and judge a product in the first 60 seconds by the quality of its README, SDK ergonomics, and error messages. Their job-to-be-done: "Let my agent act in production without it doing something expensive, irreversible, or embarrassing."
- Secondary: governance / compliance / security stakeholders. They rarely write code but need to audit agent behavior, approve risky actions, and produce evidence. Their job-to-be-done: "Show me, verifiably, what the agents did, why it was allowed, and who approved anything sensitive."
The context of use is almost always professional, focused, and consequential. Operators open Approvals because an agent is running in prod. Developers open /connect because they're wiring up a live integration. No one is idly browsing. Every pixel should respect that — no decorative filler, no tutorials-for-their-own-sake, no "welcome to your new dashboard" fluff.
Brand Personality
Three words: Serious · Precise · Trustworthy.
DashClaw is a governance runtime. It sits on the critical path between an AI agent's intent and the real world. The visual and verbal tone must match the weight of that position:
- Voice: direct, technical, declarative. Short sentences. Verbs like intercept, enforce, record, verify. No hype, no exclamation marks, no "unleash your agents."
- Tone shift: slightly warmer on marketing pages (landing,
/connect, docs intros), strictly neutral on operational surfaces (Approvals, Decisions, Policies). - Emotional target for operational surfaces: quiet confidence — "things are under control." When an operator opens Approvals, the room should feel like a calm instrument panel, not an alarm board. Status should be obvious at a glance. Brand orange appears only when attention is actually required, not as decoration.
- Emotional target for marketing surfaces: confident competence. We are the adults in the AI-safety room.
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.
- 2d ago First seen · 66 lines · 1,691 tokens per session scan A feae1211dca6
DashClaw copilot-instructions.md is an instructions file published in the GitHub repository ucsandman/DashClaw (296 stars, last pushed 4d ago), licensed MIT. It adds 1,691 tokens to every session, about $0.0085 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 instructions, from other repositories
holon AGENTS.md
Instructions for holon-run/holon, covering repository guidelines, project structure & module organization, product intent, development priorities and coding style & naming conventions.
Jixu AGENTS.md
Instructions for joe960913/Jixu, covering jixu repository instructions, 1. read order, 2. sources of truth, 3. canonical concepts and 4. architecture invariants.
holon CLAUDE.md
Instructions for holon-run/holon: This file is read by Claude Code and other agent tooling.
kdcube AGENTS.md
Instructions for kdcube/kdcube, covering agents.md — operating rules for coding agents, shared ground rules (both classes), a. platform contributors, git and shared-tree etiquette and code architecture.
Core-Memory CLAUDE.md
Instructions for JohnnyFiv3r/Core-Memory, covering claude.md — core memory, what this repo is, guiding principle — engineering simplicity, boring primitives, rich views and mapping to the current codebase.
OpenMAO AGENTS.md
Instructions for OpenMAO/OpenMAO, covering agents.md - openmao agent protocol, start here, stay on course, hard rules and working protocol.