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GoogleKnown publishergoogle/adk-samples/core/python/adk-voice-agent/sandbox/skills/recommendations/SKILL.md

recommendations

Skill11k starsChanged 44 days agoApache-2.0View on GitHub

How to suggest options that fit the user and don't repeat earlier ones (meals, restaurants, trips, activities, gifts, books). Use before any open-ended recommendation.

2 other projects use a version of this.

Trending

More talk lately.about the whole repository

Dec 2025: 1 mentionJan 2026: 1 mentionFeb 2026: 2 mentionsMar 2026: 0 mentionsApr 2026: 0 mentionsMay 2026: 1 mentionJun 2026: 1 mentionJul 2026: 2 mentionsAug 2026: 0 mentionsSep 2026: 4 mentionsOct 2026: 4 mentionsNov 2026: 0 mentions
Dec 2025Jun 2026Nov 2026
Mentions a month of the google/adk-samples repository that our weekly crawl found. There is no adoption data for this file yet.

Most recently taken up by

Who's talking about google/adk-samples

The biggest 5 of 32 mentions linking to the repository that our crawl found. Each line is their own headline.

See all 32

Talked about on GitHub, Bluesky, Hacker News and Stack Overflow (32 times).

On GitHub · 23

18 more on GitHub

On Bluesky · 4

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Treat all previously suggested options as an anti-repeat list unless the user asks to revisit one (say so if re-suggesting a past favorite …

    line 13
  2. Very specific:

    Verify live facts (hours, prices, availability) with search_web_grounded or search_maps_grounded and link sources.

    line 15

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Fresh recommendations

  1. Check prior context first:
    • <user_profile> in your thread prompt for preferences and hard constraints (diet, allergies, budget, dates, accessibility, companions).
    • Past threads and files: list_threads and read_thread on voice_agent, plus files in the project folder.
    • Earlier conversations: recall with the topic.
  2. Select options:
    • Treat all previously suggested options as an anti-repeat list unless the user asks to revisit one (say so if re-suggesting a past favorite on purpose).
    • Vary meaningful dimensions (cuisine, price, neighborhood, effort) rather than near-duplicates.
    • Verify live facts (hours, prices, availability) with search_web_grounded or search_maps_grounded and link sources.
  3. Record suggestions: In a project folder, update AGENTS.md (e.g., "Suggested so far") so future threads don't repeat them.

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Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.