TrainDocs

TrainDocs is a command for coding agents from Evyasys-Software-Solutions/EvyaGovernance. It costs 97 tokens per session (1,112 once invoked), scanned A, original, MIT.

A command that scans a project and creates a set of documents describing its architecture, coding rules, testing, security, deployment, design, and accessibility standards.

In plain words
What is it for?
Use it to create or refresh project guidance in `.evyasys/docs/`, including rules for dependencies, hooks, styling, unit tests, WCAG 2.1 AA accessibility, and visual quality.
Why use it?
It gives the coding agent a shared reference for how the project should be built and checked. It can also update only documents affected by recent code changes.

Command

Part of the evyasys plugin — 15 skills, 15 commands shipped together

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 commands/evyasys-software-solutions/evyagovernance/traindocs
Clone the repo
git clone --depth 1 https://github.com/Evyasys-Software-Solutions/EvyaGovernance

Or install evyasys, the plugin that ships this one along with the rest of its 15 skills, 15 commands.

Wrote 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.

agentmods badge for TrainDocs

README.md
[![agentmods](https://agentmods.dev/badge/commands/evyasys-software-solutions/evyagovernance/traindocs.svg)](https://agentmods.dev/commands/evyasys-software-solutions/evyagovernance/traindocs)
Your own site
<a href="https://agentmods.dev/commands/evyasys-software-solutions/evyagovernance/traindocs"><img src="https://agentmods.dev/badge/commands/evyasys-software-solutions/evyagovernance/traindocs.svg" alt="Measured on agentmods" height="20"></a>
Per session 97 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,112 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00097 $0.01112
Opus 5 $0.00048 $0.00556
Sonnet 5 $0.00019 $0.00222
Haiku 4.5 $0.00010 $0.00111

Measured 5d ago against content hash f99b9be83edf, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

TrainDocs scanned grade A with 1 finding 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 5d 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.

Reads agent configuration directorieslowAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

macOS / Linux (Bash): `EVYA_AI=$(find "$HOME/.claude/plugins" -maxdepth 6 -type d -name ".ai" 2>/dev/null | grep -i "EvyaGovernance" | head -1); [ -z "$EVYA_AI" ] && EVYA_AI=".ai"; echo "$EVYA_AI"`

Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.

commands/TrainDocs.md · 49 lines

How it starts

The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are running /evyasys:TrainDocs $ARGUMENTS.

Step 0 — Pre-flight

0a. Check .evyasys/docs/ for existing files: - No docs → proceed with full generation (all 37 documents). - Docs exist and $ARGUMENTS is empty → ask: "Docs already exist. Regenerate all, update specific, retrain, or abort?" - $ARGUMENTS is --update → confirm: "Regenerate all 37 documents?" - $ARGUMENTS is --update <filename> → confirm: "Regenerate .evyasys/docs/<filename> only?" - $ARGUMENTS is --retrain → switch to retrain mode (see PROMPT.md Step 0-R): read last generation date from INDEX.md, detect changed areas via git log, regenerate only affected docs. Note: 37 documents total — 35 core + fe/ACCESSIBILITY.md + fe/VISUAL_QUALITY.md (skip if no frontend layer). 0b. Read CLAUDE.md from project root if present. Carry its content into ARCHITECTURE.md and RULES.md. 0c. Find the plugin's installed workflow directory, then load AGENT.md, PROMPT.md, and DOC_MANIFEST.md from it:

macOS / Linux (Bash): `EVYA_AI=$(find "$HOME/.claude/plugins" -maxdepth 6 -type d -name ".ai" 2>/dev/null | grep -i "EvyaGovernance" | head -1); [ -z "$EVYA_AI" ] && EVYA_AI=".ai"; echo "$EVYA_AI"`

Windows (PowerShell): `$EVYA_AI = (Get-ChildItem "$env:USERPROFILE\.claude\plugins" -Recurse -Directory -Filter ".ai" -ErrorAction SilentlyContinue | Where-Object { $_.FullName -like '*EvyaGovernance*' } | Select-Object -First 1 -ExpandProperty FullName); if (-not $EVYA_AI) { $EVYA_AI = ".ai" }; Write-Output $EVYA_AI`

Load `<plugin-ai>/workflows/create-docs/AGENT.md`, `<plugin-ai>/workflows/create-docs/PROMPT.md`, and `<plugin-ai>/workflows/create-docs/DOC_MANIFEST.md` (replace `<plugin-ai>` with the printed path). If any file is not found at the plugin path, fall back to the same filename under `.ai/workflows/create-docs/`.

Phase 1 — Project scan (complete before writing any document)

  1. Tech stack: read package.json, requirements.txt, pyproject.toml, Cargo.toml, go.mod, pom.xml, tsconfig.json, docker-compose.yml, Dockerfile*.
  2. Source structure: Glob src/**, app/**, lib/**, components/**, pages/**, api/**, services/**, models/**, repositories/** — map folder layout and naming.
  3. Tooling: read .eslintrc*, .prettierrc*, .editorconfig, jest.config.*, vitest.config.*, playwright.config.*, tailwind.config.*, prisma/schema.prisma.
  4. CI/CD: read .github/workflows/**, azure-pipelines.yml, Jenkinsfile.
  5. Code sampling: read 3–5 representative source files per layer to infer patterns, naming, and conventions.
  6. Existing docs: read README.md, CONTRIBUTING.md, any files under docs/.

Read the full file on GitHub · 49 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. 5d ago First seen · 49 lines · 97 tokens per session scan A f99b9be83edf

Subscribe to this mod's changes

TrainDocs is a command published in the GitHub repository Evyasys-Software-Solutions/EvyaGovernance (7 stars, last pushed 23d ago), licensed MIT. It adds 97 tokens to every session and 1,112 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.