word-aligner

A tool for drawing interactive diagrams that connect matching words between two or more texts. It can show translations, including languages that read from right to left.

In plain words
What is it for?
Use it to align a phrase with its translation, explain grammar or word order, and share the result as a web link.
Why use it?
It makes word-by-word translation relationships easier to understand, especially when several source words map to one target word or vice versa.

Skill for Claude CodeCodex

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 skills/tinygodsdev/bitext-word-alignment/word-aligner-skill
Any agent
npx skills add tinygodsdev/bitext-word-alignment --skill word-aligner-skill
Clone the repo
git clone --depth 1 https://github.com/tinygodsdev/bitext-word-alignment

Made for: Claude Code, Codex.

Per session 102 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,854 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 $0.00102 $0.01854
Opus 5 $0.00051 $0.00927
Sonnet 5 $0.00020 $0.00371
Haiku 4.5 $0.00010 $0.00185

Measured 2d ago against content hash df3805644b01, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

word-aligner 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 2d 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.

word-aligner-skill/SKILL.md · 127 lines

How it starts

The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Word Aligner

Word Aligner generates shareable interactive diagrams showing which words in one text correspond to which words in another. Words are connected by colored arcs; tokens sharing a connection group (many-to-one or one-to-many) get the same color automatically.

API endpoint: POST https://aligner.tinygods.dev/api/align
Returns: { "url": "https://aligner.tinygods.dev/?data=..." } — give this URL to the user.

Minimal request

{
  "lines": ["I sleep", "Я сплю"],
  "alignments": [[0, 0, 1, 0], [0, 1, 1, 1]]
}

alignments entries are [lineA, wordA, lineB, wordB]: word wordA of line lineA links to word wordB of line lineB. All indices are 0-based, and the two lines must be vertically adjacent (|lineA − lineB| = 1).

Workflow

  1. Translate the phrase yourself (or use the user's existing translation).
  2. Identify which source words correspond to which target words.
  3. Call the API.
  4. Return the url to the user with a brief explanation.

Word index counting (read carefully — this is the #1 source of mistakes)

Word indices are token positions, so you must tokenize a line exactly the way the service does before assigning indices:

  1. Whitespace always splits. "I have been going"I[0] have[1] been[2] going[3].
  2. The tokenSplitChars characters also split, and are then removed from the output. The default set is .-|. So "go.PST.IPFV" becomes three separate tokens go PST IPFV and the dots disappear from the rendered diagram. This is usually not what you want for Leipzig glosses — see the gloss pattern below, which sets tokenSplitChars to "-|" to keep the dots.
  3. Punctuation stays attached by default. "Hello, world!"Hello,[0] world![1] (the comma and exclamation mark are part of the tokens, not separate).
  4. The merge char + joins parts into one token rendered with a space: "is+playing" is a single token (index counts as one word) that displays as is playing.
  5. RTL lines: word 0 is the logically first word (the rightmost one on screen for Hebrew/Arabic). Index in reading order, not visual order.

Read the full file on GitHub · 127 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2d ago First seen · 127 lines · 102 tokens per session scan A df3805644b01

Subscribe to this mod's changes

word-aligner is a skill published in the GitHub repository tinygodsdev/bitext-word-alignment (5 stars, last pushed 11d ago), licensed MIT. It adds 102 tokens to every session and 1,854 once invoked, about $0.0005 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.

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