What is pasteguard AGENTS.md?

Project instructions for PasteGuard, a Bun and Hono privacy proxy for language-model requests. It masks personal information and secrets before forwarding requests, then restores placeholders in supported responses.

Use it when developing or maintaining PasteGuard, especially its request masking, provider forwarding, logging, configuration, and public health or information endpoints.

It provides the project’s stack, endpoints, testing commands, and safety rules so changes follow its existing design and protect sensitive data.

pasteguard AGENTS.md — Instructions file by sgasser

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 instructions/sgasser/pasteguard/agents-md

Clone the repo

git clone --depth 1 https://github.com/sgasser/pasteguard

Made for: Codex, OpenCode.

Per session 456 This file is loaded in full into every session.

When invoked 456 The same file — it is already loaded in full.

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.

Model	Per session	Once invoked
Fable 5	$0.00456	$0.00456
Opus 5	$0.00228	$0.00228
Sonnet 5	$0.00091	$0.00091
Haiku 4.5	$0.00046	$0.00046

Measured 3d ago against content hash 41cf13336760, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pasteguard AGENTS.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 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.

AGENTS.md · 53 lines

What it actually says

PasteGuard Agent Instructions

Project

PasteGuard is a Bun/Hono privacy proxy for LLMs. It masks PII and secrets before forwarding requests to configured providers, then restores placeholders in responses where supported.

Primary endpoints:

POST /openai/v1/chat/completions
POST /anthropic/v1/messages
POST /codex/responses
GET /health
GET /info

Stack

Runtime: Bun
Web framework: Hono
Validation: Zod
Styling: Tailwind CSS v4
Database: SQLite at data/pasteguard.db
PII detection: GLiNER + regex/checksum detector service (detector/) exposing /analyze
Formatting/linting: Biome

Commands

bun run dev - development server
bun run start - production server
bun run build - build to dist/
bun test - test suite
bun run typecheck - TypeScript check
bun run check - Biome lint and format check
bun run format - apply Biome formatting for src/

Workflow

Prefer existing route/provider/extractor patterns over new abstractions.
Add or update tests when changing masking, provider forwarding, logging, config parsing, or public endpoints.
Run bun test, bun run typecheck, and bun run check before handing off code changes.
Update README and docs when public endpoints, provider config, or user setup steps change.
Do not commit tracked config.yaml changes.
Do not create commits or push branches unless the user explicitly asks.

Architecture Pointers

src/index.ts mounts routes and prints startup provider info.
src/config.ts owns YAML config loading and defaults.
src/routes/ contains HTTP route handlers.
src/providers/ contains provider clients and stream transformers.
src/masking/extractors/ contains provider-specific text extraction and insertion.
src/logging/logger.ts owns SQLite dashboard logging.
docs/mint.json registers API reference docs.

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.

3d ago First seen · 53 lines · 456 tokens per session scan A 41cf13336760

Subscribe to this mod's changes

pasteguard AGENTS.md is an instructions file published in the GitHub repository sgasser/pasteguard (739 stars, last pushed 8d ago), licensed Apache-2.0. It adds 456 tokens to every session, about $0.0023 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.

LLM Security anthropic claude openai pii privacy

gptme AGENTS.md

AGENTS.md instructions for gptme/gptme, covering agent instructions for gptme, git workflow, code style, testing and project structure.

gptme/gptme · 933 tokens

AstrBot copilot-instructions.md

Copilot instructions for AstrBotDevs/AstrBot, covering astrbot development instructions, working effectively, bootstrap and install dependencies, running the application and dashboard build (vue.js/node.js).

AstrBotDevs/AstrBot · 736 tokens

ima2-gen AGENTS.md

Instructions for lidge-jun/ima2-gen, covering ima2-gen — ai context, what this project does, tech stack, project structure and agent skills (packaged).

lidge-jun/ima2-gen · 1,235 tokens

ai AGENTS.md

AGENTS.md instructions for vercel/ai, covering agents.md, project overview, repository structure, key directories and core package dependencies.

vercel/ai · 2,900 tokens

GPT-RAG config-python.instructions.md

Instructions for Azure/GPT-RAG, a project described as: Sharing the learning along the way we been gathering to enable Azure OpenAI at enterprise scale in a secure manner. GPT-RAG core is a Retrieval-Augmented Generation pattern running in Azure, using Azure Cognitive Search for retrieval and Azure OpenAI large…

Azure/GPT-RAG · 180 tokens

dify CLAUDE.md

Claude Code instructions for langgenius/dify, a project described as: Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.

langgenius/dify · 3 tokens