Skip to content
cccskills
FreePublished on GitHub

language-injection

Guides developers in making agent replies and interface messages follow each user's language settings. It covers language instructions in prompts, frontend translation keys, and adding languages through the application's existing shared modules.

OriginalShow the original description

LLM Agent 多语言注入规范。在修改 Agent 提示词、添加新的 Agent 端点、处理用户可见的后端消息(message_code)时使用。

See how to install

Good for

  • Making agent replies follow the user's language
  • Translating backend messages for the interface
  • Adding support for another language
  • Reviewing language handling in new agent endpoints

Files included (1)

  • SKILL.md5.1 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Language Injection for Agent Prompts

Authoritative developer guide: docs/dev-guides/6-i18n-language-injection.md.

Prerequisites: Read docs/dev-guides/6-i18n-language-injection.md before changing Agent prompts, Agent routes, backend user-visible messages, or frontend i18n strings. If your work introduces new language injection patterns or conventions, update this file and related dev-guides accordingly.

Architecture

Frontend i18n.language  →  Accept-Language header  →  get_language_instruction()
                                                           │
                                                   build_language_instruction()
                                                   (agents/agent_language.py)
                                                           │
                                              ┌────────────┴────────────┐
                                              ▼                         ▼
                                        mode="full"               mode="compact"
                                    (text-heavy agents)        (code-gen agents)

Core Modules

ModuleRole
agents/agent_language.pybuild_language_instruction(lang, mode) — generates prompt fragments; inject_language_instruction() — injects into system prompts; supports 20 languages; returns "" for English
routes/agents.py → get_language_instruction()Reads Accept-Language header, delegates to build_language_instruction
routes/agents.py → _get_ui_lang()Extracts primary language code from Accept-Language header
src/app/utils.tsx → fetchWithIdentity()Sets Accept-Language header on every API request from i18n.language
src/app/utils.tsx → translateBackend()Translates backend message_code / content_code using frontend i18n

Code Examples

Route handler — inject language

# In a Flask route handler:
lang_instruction = get_language_instruction(mode="compact")
lang_suffix = f"\n\n{lang_instruction}" if lang_instruction else ""

messages = [
    {"role": "system", "content": "You are a helpful assistant." + lang_suffix},
    {"role": "user", "content": user_input},
]

Agent constructor — use inject_language_instruction()

from data_formulator.agents.agent_language import inject_language_instruction

# Simple append (most agents)
system_prompt = inject_language_instruction(system_prompt, language_instruction)

# Insert before a marker (complex prompts)
system_prompt = inject_language_instruction(
    system_prompt, language_instruction,
    marker="**About the execution environment:**"
)

Python-side user-visible messages — message_code pattern

For fixed strings in Python that appear in the UI, do NOT translate in Python. Return a message_code and let the frontend translate:

# In an Agent or route handler:
yield {
    "type": "error",
    "message": "Output DataFrame is empty (0 rows).",  # English fallback
    "message_code": "agent.emptyDataframe",             # frontend i18n key
}

# With parameters:
result = {
    "status": "error",
    "content": f"Fields not found: {missing}",
    "content_code": "agent.fieldsNotFound",
    "content_params": {"missing": missing, "available": available},
}

Frontend consumption:

import { translateBackend } from '../app/utils';
const msg = translateBackend(event.message, event.message_code, event.message_params);

Translation keys go in src/i18n/locales/{en,zh}/messages.json under messages.agent.*.

Anti-Patterns (with explanations)

PatternWhy it's wrong
os.environ.get("DF_DEFAULT_LANGUAGE")Process-level — all users get same language; breaks multi-user
Global LLM client interceptorHidden behavior; can't distinguish full/compact mode; fragile string detection
New MessageBuilder classDuplicates agent_language.py; creates parallel conflicting abstractions
Hardcoded "回答请使用中文" in promptsNot configurable; skips the mode system; breaks for other languages
Backend-side translation dict (agent_messages.py)Forces adding every new language to Python; translations should all live in src/i18n/locales/
Hardcoded English UI strings in .tsx without t()Not translatable; use useTranslation + t('key')

Adding a New Language

  1. Add language code + display name to LANGUAGE_DISPLAY_NAMES in agents/agent_language.py.
  2. Optionally add extra rules to LANGUAGE_EXTRA_RULES (e.g. simplified vs traditional Chinese).
  3. Add frontend translations in src/i18n/locales/<lang>/ — copy an existing locale folder as template.
  4. No Agent code changes needed — the existing flow picks up new languages automatically.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

core

FreeSummary

Supports analysis of tables already in the workspace through data inspection, Python calculations, and charts chosen for the question. It also explains how to ask users for clarification and label results with meaningful units and names.

  • Inspecting table columns, statistics, and sample rows
  • Comparing categories or tracking changes over time
  • Exploring distributions and relationships
microsoft/data-formulator17.6KUpdated Oct 17, 2026

data-loading

FreeSummary

Find missing data in connected sources, inspect table structure, and suggest loading options for analysis. It also helps prepare a connection form for a new source, leaving connection and loading choices to the user.

  • Find external tables needed for an analysis
  • Browse available connected data sources
  • Check table columns before choosing data
microsoft/data-formulator17.6KUpdated Oct 17, 2026

error-handling

FreeSummary

Guides developers in handling API failures consistently from backend responses to frontend messages. It covers ordinary and streaming requests, translated error codes, retry and authentication handling, request identifiers, and removing credentials from server logs.

  • Adding an API endpoint with consistent error responses
  • Displaying errors during streaming responses
  • Adding error codes and translated messages
microsoft/data-formulator17.6KUpdated Oct 17, 2026

path-safety

FreeSummary

Guides developers in restricting server file access to approved directories. It covers validated download paths, agent file tools, local data connectors, and sandbox settings to address path traversal, where supplied paths escape their allowed location.

  • Reviewing file download routes
  • Restricting agent file access to a workspace
  • Checking local file connectors for cloud deployment
microsoft/data-formulator17.6KUpdated Oct 17, 2026

report

FreeSummary

Turn data exploration findings into one Markdown report with embedded charts and tables. Adapt the structure for a short summary, blog post, executive briefing, KPI overview, or detailed analysis while checking supporting data.

  • Summarize analysis findings for management
  • Write a blog post with supporting charts
  • Compile a KPI overview with commentary
microsoft/data-formulator17.6KUpdated Oct 17, 2026

See all skills by microsoft

Report a problem with this skill