tw

tw is a command for coding agents from olehsvyrydov/AI-development-team. It costs 30 tokens per session (115 once invoked), scanned A, original, MIT.

A command for a senior technical writer who prepares software documentation. It covers API reference pages, README files, architecture diagrams, changelogs, and guides for bringing new contributors up to speed.

In plain words
What is it for?
Use it when writing or improving API documentation, README files, architecture diagrams, release notes, or onboarding guides. It is also intended for documentation-related commit messages.
Why use it?
It helps turn complex code and system decisions into documentation that developers can follow. It also provides a consistent way to handle common documentation tasks and commit messages.

Command

Part of the ai-dev-team plugin — 7 skills, 50 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/olehsvyrydov/ai-development-team/tw
Clone the repo
git clone --depth 1 https://github.com/olehsvyrydov/AI-development-team

Or install ai-dev-team, the plugin that ships this one along with the rest of its 7 skills, 50 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 tw

README.md
[![agentmods](https://agentmods.dev/badge/commands/olehsvyrydov/ai-development-team/tw.svg)](https://agentmods.dev/commands/olehsvyrydov/ai-development-team/tw)
Your own site
<a href="https://agentmods.dev/commands/olehsvyrydov/ai-development-team/tw"><img src="https://agentmods.dev/badge/commands/olehsvyrydov/ai-development-team/tw.svg" alt="Measured on agentmods" height="20"></a>
Per session 30 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 115 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 $0.00030 $0.00115
Opus 5 $0.00015 $0.00057
Sonnet 5 $0.00006 $0.00023
Haiku 4.5 $0.00003 $0.00012

Measured 5d ago against content hash a25db3661752, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

tw 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 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.

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.

claude/commands/tw.md · 10 lines

What it actually says

/tw — Technical Writer

Invoke the technical-writer skill (claude/skills/specialized/technical-writer/SKILL.md).

Use for documentation work and commit messages: API docs (Javadoc/JSDoc), READMEs, architecture diagrams (C4, Mermaid), changelogs, and onboarding guides. Consult the workflow-engine for handoffs.

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 · 10 lines · 30 tokens per session scan A a25db3661752

Subscribe to this mod's changes

tw is a command published in the GitHub repository olehsvyrydov/AI-development-team (16 stars, last pushed 26d ago), licensed MIT. It adds 30 tokens to every session and 115 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 2026-08-30.

Related

Other commands, from other repositories

ingest-collection

Bulk-ingest source collections such as Git doc repos, MediaWiki sources, CSV/JSON message archives, and Wayback CDX snapshots into raw sources.

nvk/llm-wiki · 31 tokens

output

Generate output artifacts from active wiki content — summaries, reports, study guides, slide outlines, timelines, glossaries, comparisons. Outputs are filed back into the wiki.

nvk/llm-wiki · 33 tokens

paper-trail-ingest-all

Batch INGEST across the entire vault. Scans all SOTAs, identifies those with bibliographic sections containing free-text citations, then runs /paper-trail:ingest on each one sequentially. Reports per-SOTA summary at the end. The single batch entry point to make a legacy vault fully conform to the paper-trail pipeline.

roomi-fields/paper-trail · 69 tokens

paper-trail-inject-url

Injecte une URL OA connue (HAL, dépôt uni, NIME, page perso) pour une ref dont la cascade automatique a échoué, puis relance l'acquisition + validation page 1.

roomi-fields/paper-trail · 41 tokens

paper-trail-acquire

Troisième passe du pipeline cible refondu. Lance la cascade PDF (10 sources : Crossref OA + arXiv + OpenAlex + Unpaywall + HAL + CORE + éditeur par DOI + archive.org + WebSearch ; jusqu'à 17 avec les voies par navigateur et les sources étendues opt-in) ciblée sur les refs d'un SOTA donné. Différent de pipeline run qui…

roomi-fields/paper-trail · 114 tokens

paper-trail-cascade

Acquire PDFs via the 8-source cascade (11 with opt-in extended sources) for a single ref by slug, or a batch filtered by state. Validates page 1 anti-homonymy on each download.

roomi-fields/paper-trail · 44 tokens