pincer: Instructions file for Codex

AGENTS.md

pincer AGENTS.md is an instructions file for Codex, OpenCode from pincerhq/pincer. It costs 1,658 tokens per session, scanned A, original, MIT.

A repository instruction file for the Pincer project, documenting its architecture, coding conventions, development commands, and testing workflow.

In plain words
What is it for?
It helps agents work on this Python project by describing how to install dependencies, run tests, lint code, format files, and understand the system.
Why use it?
It gives a coding agent project-specific guidance so its changes and commands match the repository's existing practices.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions AGENTS.md; mentions Codex.

This is pincerhq/pincer's own configuration. It tells Codex and OpenCode how to work on pincer itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything pincer configures →

Reuse

Borrowing it

Nothing to install: this file belongs to pincerhq/pincer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/pincerhq/pincer/dev/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/pincerhq/pincer

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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README.md
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Per session 1,658 This file is loaded in full into every session.
When invoked 1,658 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.01658 $0.01658
Opus 5 $0.00829 $0.00829
Sonnet 5 $0.00332 $0.00332
Haiku 4.5 $0.00166 $0.00166

Measured today against content hash 817fd9843e86, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-14, from the pricing page.

Security

Grade A, and why

pincer 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 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.

AGENTS.md · 65 lines

How it starts

The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This file provides guidance to Codex (Codex.ai/code) when working with code in this repository.

Project

Pincer (pincer-agent) is a self-hosted, security-first AI agent that operates across messaging channels (Telegram, WhatsApp, Discord, Slack, Signal, Email, Voice, Web) with 300+ native tools plus unlimited tools via MCP. Pure Python 3.12+ / asynciono agent framework (no LangChain, CrewAI, etc.), just provider SDKs (anthropic, openai) directly. The codebase is intentionally auditable. When building or extending LLM-facing functionality, prefer the latest Codex models and consult the Codex-api skill for current model IDs.

Commands

Use uv (preferred). Tests run from the repo root; pyproject.toml sets pythonpath = ["src"] and asyncio_mode = "auto".

uv sync --all-extras                 # install everything incl. dev + workspace MCP packages
uv run pytest                        # full suite
uv run pytest tests/test_agent.py    # one file
uv run pytest -k "test_approval" --no-cov   # by name filter
uv run pytest --cov=pincer --cov-report=term-missing

uv run ruff check .                  # lint
uv run ruff format .                 # format (CI fails on `ruff format --check .`)
uv run mypy src/                     # type check (strict)
uv run bandit -r src/pincer -ll -s B101,B104,B310,B608   # security scan

uv run pincer run                    # start agent (all configured channels)
uv run pincer doctor                 # 40+ config/security health checks

CI (.github/workflows/ci.yml) runs all of: pytest (incl. src/ms365-mcp/tests/), mypy on src/, ruff check, ruff format --check, and bandit. All must pass before merge.

Dashboard (React + Vite + TS in dashboard/, pnpm 10+): cd dashboard && pnpm install && pnpm dev (port 3000, proxies /api:8080). CI runs pnpm type-check, pnpm lint, pnpm test.

Architecture

Agent loopsrc/pincer/core/agent.py is the ReAct (reason+act) brain: receive message → load session + memories → call LLM with available tools → if tool_call, execute (in sandbox, with approval) → feed result back → repeat until text → deliver → persist session/memory/cost. This single loop is shared across every channel.

Read the full file on GitHub · 65 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. today First seen · 65 lines · 1,658 tokens per session scan A 817fd9843e86

Subscribe to this mod's changes

pincer AGENTS.md is an instructions file published in the GitHub repository pincerhq/pincer (50 stars, last pushed today), licensed MIT. It adds 1,658 tokens to every session, about $0.0083 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 2026-09-15.

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