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.
npx skills add CALLE-AI/awesome-phone-call-agents --skill call-multilingual-code-switching-alignergit clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agentsWrote 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.
[](https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/call-multilingual-code-switching-aligner)<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/call-multilingual-code-switching-aligner"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/call-multilingual-code-switching-aligner/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/call-multilingual-code-switching-aligner"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/call-multilingual-code-switching-aligner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.00652 |
| Opus 5.5 | $0.00018 | $0.00261 |
| Sonnet 5.5 | $0.00009 | $0.00130 |
| Haiku 4.5 | $0.00005 | $0.00065 |
Grade A, and why
call-multilingual-code-switching-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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multilingual Code-Switching Aligner
This offline prototype counts a small Spanish vocabulary in supplied text and suggests an English/Spanish mixing style. It does not identify arbitrary matrix languages, support Hinglish, or establish improvements in inclusivity, trust, or cognitive load.
The helper returns a style label only. A separate host could use it as a suggestion, subject to the caller's stated language preference; rapport or cognitive-load benefits are not established.
Scientific Foundation
| Paper / Framework | Relevance |
|---|---|
| Output Language Alignment for CSW | Demonstrates that AI mirroring code-switching frequencies increases user trust and reduces linguistic anxiety. |
| Matrix Language Frame (MLF) model | Myers-Scotton framework for distinguishing embedded words vs the matrix language. |
| FCA Consumer Duty (Vulnerability) | Reduces cognitive load for non-native speakers by allowing them to use their natural hybrid dialects. |
How it works
- Supply a transcript string. An optional host ASR component is outside this contribution.
- It strips punctuation and detects embedded vocabularies to calculate a Code-Mixing Index (CMI).
- The system returns a structured
CodeSwitchingReportcontaining the CMI and the suggestedPromptStyle. - A host may review the suggested style before updating a prompt; the helper performs no prompt or speech mutation.
Decision Matrix
| Code-Mixing Index (CMI) | Derived Prompt Style | Expected LLM Output Behavior |
|---|---|---|
CMI == 0.0 |
monolingual_english |
Strict monolingual English (standard). |
0.0 < CMI < 0.30 |
low_code_switching |
Occasional embedded loan words (e.g., "gracias", "pero"). |
CMI >= 0.30 |
high_code_switching |
Fluid Spanglish; alternating sentence clauses. |
Expected Outcomes & Metrics
Latency is a design target, not a measured integration benchmark.
| Metric | Target | Notes |
|---|---|---|
| CMI Computation Latency | < 5ms | Runs via ultra-fast lexicon matching. |
| Rapport / Trust Score | Not measured | No A/B evaluation of this helper is supplied. |
What ships with it
5 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.
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.
- 1mo ago First seen · 52 lines · 45 tokens per session scan A 24fcbe1d8b80
call-multilingual-code-switching-aligner is a skill published in the GitHub repository CALLE-AI/awesome-phone-call-agents (109 stars, last pushed yesterday), licensed MIT. It adds 45 tokens to every session and 652 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-19.
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