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/razz-team/brighty-agent-toolkit/claude-mdgit clone --depth 1 https://github.com/razz-team/brighty-agent-toolkitWrote 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/razz-team/brighty-agent-toolkit/claude-md)<a href="https://agentmods.dev/instructions/razz-team/brighty-agent-toolkit/claude-md"><img src="https://agentmods.dev/badge/instructions/razz-team/brighty-agent-toolkit/claude-md.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 | $0.02219 | $0.02219 |
| Opus 5 | $0.01110 | $0.01110 |
| Sonnet 5 | $0.00444 | $0.00444 |
| Haiku 4.5 | $0.00222 | $0.00222 |
Grade A, and why
brighty-agent-toolkit CLAUDE.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 4d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository context for Claude
This file is loaded automatically by Claude Code, Cursor, and similar tools when working in this repository. It captures the conventions and invariants that aren't obvious from the file tree alone.
What this repository is
brighty-agent-toolkit is a monorepo containing three things stitched together:
- An Anthropic plugin (
.claude-plugin/) — wraps everything below into a single installable unit - A TypeScript MCP server (
packages/mcp-server/) — exposes the Brighty banking API as MCP tools (stdio in v0.1) - AgentSkills-spec skills (
skills/) — teach AI agents how to use those tools effectively
Specialized agents (agents/) and slash commands (commands/) are planned for v0.1 — not present in v0.0.1, not declared in plugin.json. The server is stdio-only by design; there is no hosted/HTTP mode and one is not planned.
Skills follow the open AgentSkills standard (https://agentskills.io). The plugin wrapper is Anthropic-specific. Same skills work in Codex, Cursor, OpenClaw — the wrapper does not.
Critical invariants
These must hold across every change. CI enforces all of them:
- Every tool name referenced in a
SKILL.mdexists inpackages/mcp-server/src/tools/. Cross-checked byscripts/check-tool-references.mjs. - Every
SKILL.mdvalidates against the AgentSkills spec viaskills-ref validate. SKILL.mdbody stays under 500 lines. Detailed material lives inreferences/and loads on demand.- Skill
namein frontmatter matches the parent directory exactly (spec requirement). - No skill executes arbitrary code or fetches arbitrary URLs. Skills only orchestrate calls to MCP tools.
Workflows
Adding a new skill
- Create
skills/<skill-name>/SKILL.mdwith required frontmatter (name,description). - The
descriptionfield is what the agent uses to decide when to activate the skill. Format: what the skill does + when to use it + 3-5 trigger keywords. Spec max is 1024 chars; aim for under 300. - Reference MCP tools by their actual snake_case name (e.g.,
brighty_create_payout). - Add the skill path to
.claude-plugin/plugin.jsonunderskills. - Run
yarn validateandyarn check-tools.
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.
- 4d ago First seen · 146 lines · 2,219 tokens per session scan A 0202c21a6f86
brighty-agent-toolkit CLAUDE.md is an instructions file published in the GitHub repository razz-team/brighty-agent-toolkit (2 stars, last pushed 23d ago), licensed MIT. It adds 2,219 tokens to every session, about $0.0111 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 2026-08-31.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.