agent-platform-skill-registry

Name: agent-platform-skill-registry
Author: google

AI Community

Repo stars 10,425
Author repo skills

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: > This skill provides instructions for interacting with the Skill Registry on the Gemini Enterprise Agent Platform. specific ski…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “Core Capabilities”, “Core Directives”, “Prerequisites & Authentication”, “Library & Authentication”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name agent-platform-skill-registry directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “Core Capabilities / Core Directives / Prerequisites & Authentication” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / write / shell-exec / env-read; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

Skill Registry

This skill provides instructions for interacting with the Skill Registry on the Gemini Enterprise Agent Platform.

Core Capabilities

Skill Discovery - Query the registry to easily search, list, get specific skills, and inspect revision histories.
Skill Lifecycle Management - Upload, update, or permanently delete skills.
Operation Monitoring - Utility to check the completion status of long-running state changes (LROs).
Generate Skill - Automate the initial scaffolding of new agent skills locally.

Core Directives

Mandatory Validation: ALWAYS execute the environment validation check before performing any operations.

Before any operation, you must validate the core environment.
```
# Execute the validation script
python3 scripts/validate_env.py
```

Prerequisites & Authentication

Library & Authentication

Ensure you have the latest Google Cloud credentials and libraries installed.

# Install required libraries
pip install google-auth requests

# Authenticate with Google Cloud
gcloud auth application-default login

Environment Variables

The following variables are required for operations:

GCP_PROJECT_ID: Your Google Cloud Project ID.
GCP_LOCATION: The region (e.g., us-central1).

Quickstart

Quickly search for available skills in the registry:

python3 scripts/skill_registry_ops.py search \
  --query "test skill" \
  --top-k 5

Operations

Skill Discovery: query-skills.md
Skill Lifecycle: manage-skills.md
Monitor Operations: monitor-operations.md
Generate Skill: generate-skill.md

Fluxly profile Author and license come from source; runtime, permissions, and network are Fluxly detections or estimates

Fluxly category: AI
Author-declared agents: No explicit declaration found; this is not inferred or tested compatibility
Static check: 88 / 100 · heuristic scan, not runtime safety proof
Author / version / license: @google · no license declared
Fluxly token estimate: Lean
Fluxly setup estimate: Guided setup
External API key: No requirement detected
Detected OS requirements: Unspecified
Runtime requirements: Unspecified
Detected file/system behavior: Read-only
Write / modify
Shell exec
Env read
Detected network behavior: Local-only
Install commands: None (reference only)

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview agent-platform-skill-registry.preview

The current SKILL.md does not define a fixed output example.

SKILL.md SKILL.md

# Skill Registry

This skill provides instructions for interacting with the **Skill Registry** on
the Gemini Enterprise Agent Platform.

## Core Capabilities

-   **Skill Discovery** - Query the registry to easily search, list, get
    specific skills, and inspect revision histories.
-   **Skill Lifecycle Management** - Upload, update, or permanently delete
    skills.
-   **Operation Monitoring** - Utility to check the completion status of
    long-running state changes (LROs).
-   **Generate Skill** - Automate the initial scaffolding of new agent skills
    locally.

## Core Directives

-   **Mandatory Validation**: ALWAYS execute the environment validation check
    before performing any operations.

    Before any operation, you **must** validate the core environment.

    ```bash
    # Execute the validation script
    python3 scripts/validate_env.py
    ```

## Prerequisites & Authentication

### Library & Authentication

Ensure you have the latest Google Cloud credentials and libraries installed.

```bash
# Install required libraries
pip install google-auth requests

# Authenticate with Google Cloud
gcloud auth application-default login
```

### Environment Variables

The following variables are required for operations:

-   `GCP_PROJECT_ID`: Your Google Cloud Project ID.
-   `GCP_LOCATION`: The region (e.g., `us-central1`).

--------------------------------------------------------------------------------

## Quickstart

Quickly search for available skills in the registry:

```bash
python3 scripts/skill_registry_ops.py search \
  --query "test skill" \
  --top-k 5
```

--------------------------------------------------------------------------------

## Operations

-   **Skill Discovery**: [query-skills.md](references/query-skills.md)

…

Evidence boundary and execution chain

Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.

sections -> Core Capabilities → Core Directives → Prerequisites & Authentication → Library & Authentication → Environment Variables → Quickstart
terms    -> Skill Registry · Skill Discovery · Skill Lifecycle Management · Operation Monitoring · Generate Skill · Mandatory Validation · must · Skill Lifecycle
files/cmd -> GCPPROJECTID · GCPLOCATION · us-central1 · scripts/validateenv.py · scripts/skillregistryops.py · query-skills.md · references/query-skills.md · manage-skills.md
body sha256 -> 54582d4365ed