# Advise Skills

> Query the skill registry to find relevant architectural skills matching what the user wants to build. Searches across configured registries with graceful fallback to local sources.

- **Type:** Skill
- **Install:** `agentstack add skill-prosusai-prism-advise-skills`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [ProsusAI](https://agentstack.voostack.com/s/prosusai)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** Apache-2.0
- **Upstream author:** [ProsusAI](https://github.com/ProsusAI)
- **Source:** https://github.com/ProsusAI/prism/tree/main/skills/advise-skills

## Install

```sh
agentstack add skill-prosusai-prism-advise-skills
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

## When to use this skill

Use when the user wants to find skills relevant to a task or architectural decision. Invoked as `/advise-skills ` (Claude Code) or `@advise-skills ` (Cursor).

## Configuration

- **Primary source:** All configured registries in `~/.prism/registries.json` (with per-registry caching and source tagging)
- **Fallback 1:** Local `skill-registry.json` in the current project directory
- **Fallback 2:** Local `_analysis/extracted_skills_codebase/` skill directories
- **Authentication:** `REGISTRY_TOKEN` environment variable (global override) or per-registry token from `registries.json`

> Skills from multiple registries are merged and each result is tagged with `[registry-name]` (e.g., `[team]`, `[community]`) to identify the source.

## Instructions

### Step 1 -- Resolve skill registry source

Read `~/.prism/skills/_shared/registry-fetch.md` and follow its instructions. It resolves all configured registries with ETag caching and local fallbacks, returning a skills array where each entry is tagged with `_registry`.

Outcomes:
- Valid JSON array → use as the skills list, proceed to Step 2
- `REGISTRY_EMPTY` → registry reached but empty, proceed to Step 2
- `NO_REGISTRIES` → no registry reachable, stop (the shared file handles the user message)

### Step 2 -- Check for empty registry

If the `skills` array from the resolved source is empty, respond with: "No skills have been published to the registry yet." and stop.

### Step 3 -- Extract trigger clauses

For each entry in the `skills` array, extract the `TRIGGER when` clause from its `description` field. This clause defines the scenarios where the skill is relevant.

### Step 4 -- Match and rank

Compare the user's query against each trigger clause semantically. A skill matches if the user's intent aligns with at least one trigger scenario. Require genuine semantic alignment -- do not match on superficial keyword overlap.

Rank matches by relevance to the user's query.

### Step 5 -- Respond with match table

Respond with a table using only registry metadata (no fetching yet). If the skill has a `_registry` field, prefix the skill name with `[registry-name]` to show the source:

| Skill Name | Repository | Why it matches |
|---|---|---|
| [registry-name] {name} | {repository} | {why it matches this query} |

If no skills match the query, state that clearly and list all available skill names with their one-line descriptions so the user can see what is available and refine their query. Stop here.

Then ask:

> "Fetch full skill details for all N match(es), or would you like to adjust the list first?"

Wait for the user's response. If they want to adjust, accept a revised list of skill names and proceed with those. If they confirm all, proceed with the full matched set.

### Step 6 -- Load confirmed skills' SKILL.md

For each confirmed skill, try to load its full SKILL.md content.

**If the skill was loaded from a remote registry:** Fetch the individual skill's SKILL.md using the `path` field from the registry entry:

```python
python3 /dev/null | sed 's/.*\///;s/\.git$//'
date +%d-%m-%Y
```

```markdown
# /advise-skills (Claude Code) or @advise-skills (Cursor) Results
# {repository} -- {DD-MM-YYYY}

> Query: {the user's original query}

| Skill Name | Repository | Why it matches |
|---|---|---|
| {name} | {repository} | {why it matches this query} |
```

If no skills were successfully loaded, do not write the file.

## Output rules

- Only respond with a table. Do not render the full SKILL.md files below the table.
- Do not add commentary or analysis beyond what is in the SKILL.md.
- Do not suggest skills that do not have a clear trigger match.
- Order results by relevance, strongest match first.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [ProsusAI](https://github.com/ProsusAI)
- **Source:** [ProsusAI/prism](https://github.com/ProsusAI/prism)
- **License:** Apache-2.0

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** yes
- **Filesystem access:** yes
- **Shell / process execution:** no
- **Environment & secrets:** yes
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-prosusai-prism-advise-skills
- Seller: https://agentstack.voostack.com/s/prosusai
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.