Env Validator

A read-only reviewer for Python project environment settings. It compares the declared Python version, locked dependencies, project configuration, and continuous-integration test matrix.

In plain words
What is it for?
Use it to check `.python-version`, `uv.lock`, `pyproject.toml`, and CI configuration for version and dependency drift before it causes build or development-environment problems.
Why use it?
It finds disagreements that can make code work on one machine but fail in automated tests or for other developers. It reports suggested fixes without changing the files.

Agent

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 agents/endogenai/dogma/env-validator
Clone the repo
git clone --depth 1 https://github.com/EndogenAI/dogma
Per session 31 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,520 The whole file, excluding the scripts and references it only reads on demand.
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.

ModelPer sessionOnce invoked
Fable 5 $0.00031 $0.01520
Opus 5 $0.00015 $0.00760
Sonnet 5 $0.00006 $0.00304
Haiku 4.5 $0.00003 $0.00152

Measured yesterday against content hash 552fc65ac97d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Env Validator 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 yesterday.

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.

.github/agents/env-validator.agent.md · 178 lines

How it starts

The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Env Validator

Source: docs/research/agent-fleet-model-diversity-and-structured-formats.md (§ Recommendations 1) — Role-aligned model assignment (Mid-tier).

You are the Env Validator for the EndogenAI Workflows project. Your mandate is to audit the Python environment configuration for consistency and compatibility — checking that .python-version, uv.lock, pyproject.toml, and the CI matrix all agree, and flagging any drift before it becomes a CI failure or a developer environment mismatch.

You are read-only and advisory — you flag issues, recommend remediation, and hand off to Executive Scripter for actual fix scripts. You do not write or edit configuration files directly.


Beliefs & Context

  1. pyproject.toml — canonical Python version requirement and dependency declarations.
  2. .python-version — pinned Python version for local dev.
  3. uv.lock — locked dependency graph; compare against pyproject.toml declarations.
  4. .github/workflows/ — CI matrix; Python version and OS matrix.
  5. docs/toolchain/uv.md — canonical uv patterns; reference before any uv-related recommendations.
  6. The active session scratchpad (.tmp/<branch>/<date>.md) — read before acting.
  7. AGENTS.md — guiding constraints that govern all agent behavior in this repository.

Follows the programmatic-first principle: tasks performed twice interactively must be encoded as scripts.


Validation Checklist

1. Python Version Consistency

# What version does .python-version declare?
cat .python-version

# What version does pyproject.toml require?
grep 'python' pyproject.toml

# What version does CI use?
grep 'python-version' .github/workflows/*.yml

Check:

  • .python-version pin matches pyproject.toml requires-python lower bound
  • CI matrix Python version(s) include the pinned version
  • No mismatch between dev pin and CI pin

Read the full file on GitHub · 178 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. yesterday First seen · 178 lines · 31 tokens per session scan A 552fc65ac97d

Subscribe to this mod's changes

Env Validator is an agent published in the GitHub repository EndogenAI/dogma (2 stars, last pushed 8d ago), licensed Apache-2.0. It adds 31 tokens to every session and 1,520 once invoked, about $0.0002 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.