Agent skill

Call Cross Lingual Emotion Preservation

by CALLE-AI in CALLE-AI/awesome-phone-call-agents

Offline experimental QA helper for CALL-E relay transcripts.

MITAuto-check passedWriting & Content

Install Call Cross Lingual Emotion Preservation

skills CLI
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-cross-lingual-emotion-preservation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install CALLE-AI/awesome-phone-call-agents call-cross-lingual-emotion-preservation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/call-cross-lingual-emotion-preservation .claude/skills/call-cross-lingual-emotion-preservation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
call-cross-lingual-emotion-preservation
GitHub stars
107
Token cost
~1.2k tokens
SKILL.md length
509 words
Files
7 (incl. scripts, references)
Skills in repo
101
Repo updated
First seen
Licence
MIT

At a glance

Offline experimental QA helper for CALL-E relay transcripts.

  • Tasks that involve Translation
  • SKILL.md covers When To Use, When Not To Use, Workflow and Scientific Foundation, plus 1 more section
  • Runs Python scripts from its folder; calls python3

What it does

Call Cross Lingual Emotion Preservation is an agent skill from CALLE-AI/awesome-phone-call-agents. Offline experimental QA helper for CALL-E relay transcripts. Compares English urgency-marker levels in source and relay-agent text; both inputs must be English or operator-prepared English translations. Returns advisory lexical drift labels and suggested relay wording, without translating, measuring emotional state, certifying relay fidelity or placing calls.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/example-relay-transcript.json`, `references/example-source-context.json` and `references/examples.md`).

It sits in Writing & Content, covering Translation. The repository describes itself as: Portable phone-call Agent Skills, apps, examples, adapters, and scheduler recipes for AI agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Translation

Example prompts

  • “/call-cross-lingual-emotion-preservation”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 38d4118. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Call Cross Lingual Emotion Preservation loads about 1.2k tokens when it runs, and up to ~2.7k if it reads all its reference files. Until then it costs about 100 tokens; SKILL.md has 509 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~100
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from CALLE-AI/awesome-phone-call-agents at commit 38d4118, republished under its MIT licence (© CALLE-AI). 509 words, ~1,156 tokens.

Download SKILL.mdSave it as .claude/skills/call-cross-lingual-emotion-preservation/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
call-cross-lingual-emotion-preservation
description
Offline experimental QA helper for CALL-E relay transcripts. Compares English urgency-marker levels in source and relay-agent text; both inputs must be English or operator-prepared English translations. Returns advisory lexical drift labels and suggested relay wording, without translating, measuring emotional state, certifying relay fidelity or placing calls.
license
MIT

call-cross-lingual-emotion-preservation

When the message crosses a language, does the urgency survive?

language-bridge-call relays a request across languages in two legs. This skill is an experimental QA companion: it compares English urgency-marker levels in supplied text from both legs. It does not measure actual emotion or prove that a translation preserved it. A phrase such as "today, immediately, please" that arrives as "sometime this week would be fine" is a failed relay even when the words are translated correctly.

When To Use

  • after a language-bridge-call relay, to check the requester's urgency survived the second leg
  • after any translated CALL-E call where emotional subtext matters (escalations, care requests, time-critical arrangements)
  • to generate an intensity-calibrated relay goal for the next plan_call

When Not To Use

  • to relay or translate anything; use language-bridge-call
  • to detect sarcasm or stated-vs-meant mismatch; use call-verbal-irony-detector
  • to audit the relay callee's own emotions; only the relay agent's expressed intensity is measured, because the relay speaks on the requester's behalf
  • on non-English source OR relay text; the same English-only lexicon scores both. Provide operator-prepared English translations when needed; this script does not translate. A target-language parameter does not change the scorer. Non-English text can produce misleading low scores.

Workflow

Analyze a relay
bash
python3 scripts/emotion_preservation.py analyze --source-context path/to/source.json --relay-transcript path/to/relay.json

--source-context accepts the requester's call-result JSON (callee turns are used) or a plain-text operator note. --relay-transcript accepts the relay leg's CALL-E result (nested get_call_run or flat fixture shape). Both texts must be English or separately translated into English by the operator. The script does not detect or enforce language eligibility. Emits a card:

  • source_intensity / relay_intensity: {score, level, markers}; the relay side counts AGENT turns only
  • drift: FLATTENED / PRESERVED / AMPLIFIED (level comparison)
  • parity_score: 1.0 equal, 0.5 adjacent, 0.0 two steps apart
  • evidence: masked spans with matched markers, from both sides
  • emotion_assessment: "unclear" with a reason when the source context is empty or the relay has no agent turns
  • recommended_action: re_relay_with_calibrated_goal (with the goal text calibrated to the SOURCE intensity) or proceed

These are legacy action labels for human review. Scores and low/medium/high levels are illustrative lexicon thresholds, not empirically calibrated emotion measures. Neither proceed nor a re-relay suggestion authorizes a new call, emergency response or other consequential action.

Show full SKILL.md (150 more words)Show less
Craft the calibrated relay goal
bash
python3 scripts/emotion_preservation.py craft --scenario emotion-relay --intensity high --language en

Emits the plan_call inputs JSON whose goal is the same intensity- calibrated template the card recommends on drift (high / medium / low).

Scientific Foundation

ResearchRelevance
ZEST: Zero Shot Audio to Audio Emotion Transfer With Speaker Disentanglement (ICASSP 2024, arXiv 2401.04511)Zero-shot emotion transfer between speakers; motivates intensity-preserving relay design
EELE: Exploring Efficient and Extensible LoRA Integration in Emotional Text-to-Speech (2024, arXiv 2408.10852)Efficient emotional TTS control; motivates mapping intensity levels to concrete phrasing guidance

Both papers build neural emotion-transfer systems; this skill deliberately implements a lexical intensity mapper on transcripts only and labels every output analysis_mode: "heuristic" - it is informed by that research, not an implementation of it.

Differences from sibling skills

  • language-bridge-call performs the relay; this skill audits the relay's emotional fidelity and calibrates the next attempt.
  • call-semantic-barge-in-analyzer profiles how the callee participated; this skill measures what the relay agent expressed on someone's behalf.

© CALLE-AI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references) in skills/call-cross-lingual-emotion-preservation of CALLE-AI/awesome-phone-call-agents.

  • SKILL.md
  • references/example-relay-transcript.json
  • references/example-source-context.json
  • references/examples.md
  • references/safety.md
  • scripts/emotion_preservation.py
  • scripts/test_emotion_preservation.py

Open the folder on GitHubat commit 38d4118

Compare with similar skills

Call Cross Lingual Emotion Preservation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Call Cross Lingual Emotion Preservation compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Call Cross Lingual Emotion Preservation this skillCALLE-AI/awesome-phone-call-agents107—~1.2kAutomated safety check: PassMIT
Translation Diff ExportDevolutions/UniGetUI26k—~1.1kAutomated safety check: PassMIT
Sync Translationssymfony/symfony31k—~1.9kAutomated safety check: PassMIT
Translation Diff ImportDevolutions/UniGetUI26k—~750Automated safety check: PassMIT
Translation Diff TranslateDevolutions/UniGetUI26k—~934Automated safety check: PassMIT
Generate Translationspayloadcms/payload45k—~1.1kAutomated safety check: PassMIT

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Questions about Call Cross Lingual Emotion Preservation

What does Call Cross Lingual Emotion Preservation do?

Offline experimental QA helper for CALL-E relay transcripts. Call Cross Lingual Emotion Preservation is an agent skill from CALLE-AI/awesome-phone-call-agents. Offline experimental QA helper for CALL-E relay transcripts.

When should I use Call Cross Lingual Emotion Preservation?

Call Cross Lingual Emotion Preservation fits situations like: tasks that involve Translation.

How do I install Call Cross Lingual Emotion Preservation in Claude Code?

Run `npx skills add CALLE-AI/awesome-phone-call-agents --skill call-cross-lingual-emotion-preservation -a claude-code`. Or copy the skill folder (skills/call-cross-lingual-emotion-preservation in CALLE-AI/awesome-phone-call-agents) into .claude/skills/call-cross-lingual-emotion-preservation in your project. Claude Code loads it when a task matches its description.

How do I install Call Cross Lingual Emotion Preservation in Codex?

Run `npx skills add CALLE-AI/awesome-phone-call-agents --skill call-cross-lingual-emotion-preservation -a codex`. Or copy the skill folder (skills/call-cross-lingual-emotion-preservation in CALLE-AI/awesome-phone-call-agents) into .agents/skills/call-cross-lingual-emotion-preservation in your project. Codex loads it when a task matches its description.

Can I use Call Cross Lingual Emotion Preservation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add CALLE-AI/awesome-phone-call-agents --skill call-cross-lingual-emotion-preservation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/call-cross-lingual-emotion-preservation, .gemini/skills/call-cross-lingual-emotion-preservation, .github/skills/call-cross-lingual-emotion-preservation and .opencode/skills/call-cross-lingual-emotion-preservation in your project.

What does Call Cross Lingual Emotion Preservation need to run?

Going by SKILL.md and its folder, Call Cross Lingual Emotion Preservation needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Call Cross Lingual Emotion Preservation access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Call Cross Lingual Emotion Preservation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Call Cross Lingual Emotion Preservation use?

Call Cross Lingual Emotion Preservation is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Call Cross Lingual Emotion Preservation use?

About 1.2k tokens (SKILL.md is roughly 4.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.6k tokens, read only when the agent opens those files.

What are the alternatives to Call Cross Lingual Emotion Preservation?

Skills that share tags, products or a category with Call Cross Lingual Emotion Preservation: Translation Diff Export (Devolutions/UniGetUI, 26k stars), Sync Translations (symfony/symfony, 31k stars), Translation Diff Import (Devolutions/UniGetUI, 26k stars) and Translation Diff Translate (Devolutions/UniGetUI, 26k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Call Cross Lingual Emotion Preservation?

CALLE-AI (a GitHub organization) maintains it in CALLE-AI/awesome-phone-call-agents, which has 107 GitHub stars. The repository holds 101 skills in this directory. The repository was last updated on October 10, 2026.

Source: CALLE-AI/awesome-phone-call-agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.