io.github.khglynn/spotify-bulk-actions-mcp
Allows batch playlist creation, library exports, and large-scale library management with confidence scoring for track matching and human-in-the-loop review.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@io.github.khglynn/spotify-bulk-actions-mcpimport CSV of podcast songs and create playlist"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Spotify Bulk Actions MCP
A Model Context Protocol (MCP) server for bulk Spotify operations - batch playlist creation, library exports, and large-scale library management.
What makes this different from other Spotify MCPs?
Confidence scoring - Batch searches return HIGH/MEDIUM/LOW confidence for each match
Human-in-the-loop - Uncertain matches are exported for review, then re-imported
Bulk operations - Handle 500+ songs efficiently with rate limiting built-in
Library exports - Export your complete library data
Podcast playlist focused - Built specifically for importing song lists from podcast show notes
Support This Project
Made cause I can't not have headphones on, support my 80k+ pocast subscriptions.
Related MCP server: Tempo
Listed On
Directory | Link |
PyPI | |
mcp.so | |
awesome-mcp-servers | PR #1541 (pending) |
Projects I've Built With This
Project | Description | Links |
recordOS | Which albums do you love most? A visual album collection app | |
Festival Navigator | Navigate multi-day festivals with friends |
Playlists Maintained With This MCP
Coming soon: Switched On Pop, This American Life, and more podcast playlists
What This Does
Library Analysis:
Get all your followed artists
Get all saved/liked songs (handles libraries up to 10k songs)
Find unique artists from your library ranked by song count
Find albums where you have 6+ saved songs (great for vinyl shopping!)
Export your complete library summary
Listening Insights:
Your top artists and tracks (short/medium/long term)
Recently played history
Bulk Playlist Creation:
Import song lists from CSV files (for podcast playlists, etc.)
Batch search with confidence scoring (HIGH/MEDIUM/LOW)
Automatic handling of uncertain matches for human review
Create playlists from search results
Playlist Maintenance:
Find and remove duplicate tracks
Compare two playlists (shared vs unique tracks)
Bulk remove and reorder tracks, update playlist details
Export any playlist to CSV
Bulk Library Actions:
Follow/unfollow artists in bulk
Save/unsave tracks in bulk
Quick Start
1. Prerequisites
Python 3.10+
A Spotify account
Spotify Developer credentials (get them here)
2. Clone & Setup
# Clone the repo
git clone https://github.com/khglynn/spotify-bulk-actions-mcp.git
cd spotify-bulk-actions-mcp
# Create and activate virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install the package
pip install -e .
# Copy env example and add your credentials
cp .env.example .env
# Edit .env with your SPOTIFY_CLIENT_ID and SPOTIFY_CLIENT_SECRETAlso on PyPI:
pip install spotify-bulk-actions-mcp- but you'll still need local.envand auth setup.
3. Authenticate with Spotify (One-Time)
This opens a browser for you to log in:
python setup_auth.pyAfter login, your token is saved locally in .spotify_cache/.
4. Test It Works
source venv/bin/activate
python -c "from spotify_bulk_actions_mcp.utils.auth import is_authenticated; print('Auth OK!' if is_authenticated() else 'Not authenticated')"Option B: Hosted (claude.ai custom connector)
This server also runs as a remote MCP over streamable HTTP (MCP_TRANSPORT=http),
fronted by OAuth 2.1 (WorkOS AuthKit) with a fail-closed user allowlist. That's how
the author runs it: Cloud Run + Secret Manager for the Spotify refresh token, added
to claude.ai as a custom connector. Tools carry readOnlyHint/destructiveHint
annotations so clients can group read vs write actions. See Dockerfile and the
deploy notes in the parent collection repo.
5. Connect to Claude Code
Add this to your Claude Code settings (~/.claude/settings.local.json):
{
"mcpServers": {
"spotify": {
"command": "/path/to/spotify-bulk-actions-mcp/venv/bin/spotify-bulk-actions-mcp"
}
}
}Restart Claude Code after adding this.
Available Tools (33)
Library Analysis
Tool | Description |
| Verify Spotify auth is working |
| Get all artists you follow |
| Get all your liked songs |
| Artists from saved songs, ranked by count |
| Albums with N+ saved songs |
| Complete library export |
Listening Insights
Tool | Description |
| Your top artists (short/medium/long term) |
| Your top tracks (short/medium/long term) |
| Recently played tracks |
Bulk Library Actions
Tool | Description |
| Follow artists in bulk |
| Unfollow artists in bulk |
| Like/save tracks in bulk |
| Un-like tracks in bulk |
Search
Tool | Description |
| Search for a single track |
| Broader search when exact fails |
| Search many tracks with confidence scores |
| Get 30-second preview URL |
Playlist Creation
Tool | Description |
| Create a new playlist |
| Add tracks to existing playlist |
| Full CSV → playlist workflow |
| Create from batch search |
| Add reviewed/corrected tracks |
Playlist Management
Tool | Description |
| Get playlist details |
| Update name, description, public status |
| Get all tracks in a playlist |
| Export a playlist to CSV |
| Shared vs unique tracks between two playlists |
| Find duplicates in a playlist |
| Remove duplicates, keeping first occurrence |
| Bulk remove specific tracks |
| Move tracks within a playlist |
Utilities
Tool | Description |
| Validate a song CSV |
| Export uncertain matches for review |
How This Differs From the Official Spotify Connector
Claude has an official Spotify connector (built by Spotify, April 2026). It's excellent at what it does — but its tool surface is small, and this MCP exists for everything it doesn't cover. As of August 2026 the official connector exposes 8 tools: Search Spotify, Create Playlist, Get Currently Playing, Add to Library, Remove from Library, Fetch Playlist Tracks, and two auth utilities.
Capability | Official connector | This MCP |
Search, playback context, mood playlists | ✅ | Search only |
Create a playlist | ✅ | ✅ (plus CSV import w/ confidence scoring) |
Add/remove Liked Songs | ✅ (one at a time) | ✅ bulk |
Read your full library (saved tracks, followed artists) | ❌ | ✅ |
Listening insights (top artists/tracks, recently played) | ❌ | ✅ |
Edit existing playlists (bulk remove, reorder, update details) | ❌ | ✅ |
Dedupe / compare / export playlists to CSV | ❌ | ✅ |
Bulk follow/unfollow artists | ❌ | ✅ |
One more difference: the official connector runs on Spotify's partner-gated MCP gateway (no dynamic client registration; tokens from ordinary developer apps are rejected), so it's only usable inside partnered AI surfaces. This MCP runs under your own Spotify developer app — Development Mode limits apply (5 allowlisted users per Client ID as of February 2026), but you control it end to end.
Example Workflows
Get Your Library Stats
Ask Claude:
"What artists do I have the most saved songs from?"
Claude will use get_library_artists and show you.
Find Albums for Vinyl
Ask Claude:
"Find albums where I have 6 or more saved songs"
Claude will use get_albums_by_song_count with min_songs=6.
Create Playlist from Song List
Create a CSV file:
title,artist
Bohemian Rhapsody,Queen
Hotel California,Eagles
Billie Jean,Michael JacksonAsk Claude:
"Create a playlist called 'My Mix' from this CSV: [paste CSV]"
Claude will:
Parse the CSV
Search each song with confidence scoring
Create the playlist with high-confidence matches
Show you uncertain matches to review
Bulk Podcast Playlist
For large lists (500+ songs):
Ask Claude to use
batch_search_trackswith your song listReview the results (HIGH goes in automatically)
Use
export_review_csvto get uncertain matchesReview/correct in a spreadsheet
Use
add_reviewed_tracksto add your corrections
Rate Limits
The server handles Spotify's rate limits automatically:
Small delays between API calls
Automatic retry on 429 errors
Caching to reduce repeat calls
For 10k songs, expect the initial library fetch to take 2-3 minutes.
Files & Data
Location | Purpose |
| Your Spotify credentials (gitignored) |
| Auth tokens and cached data (gitignored) |
| Main MCP server |
| Tool implementations |
Troubleshooting
"Not authenticated" error:
python setup_auth.pyRate limit errors: Wait a few minutes and try again. The server will auto-retry.
Token expired:
The server auto-refreshes tokens. If issues persist, re-run setup_auth.py.
Security Notes
Your credentials are in
.env(gitignored, never committed)Auth tokens are stored locally in
.spotify_cache/Never share your
.envor token filesIf credentials are exposed, rotate them in Spotify Dashboard
License
MIT
Made cause I can't not have headphones on. If this helps you, buy me a coffee!
Available Tools
33 toolsadd_reviewed_tracksA
Add tracks from a reviewed CSV to an existing playlist.
Use this after reviewing uncertain matches from a batch search.
The CSV should have an 'action' column:
'approve': Add the matched track
'reject': Skip this track
spotify:track:xxx: Use this specific URI instead
| Name | Required | Description | Default |
|---|---|---|---|
| playlist_id | Yes | Existing playlist ID | |
| reviewed_csv | Yes | Reviewed CSV content with 'action' column |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes the CSV format and action column, but does not disclose side effects (e.g., duplicate handling), authentication needs, or rate limits. Since no annotations exist, the description carries full burden but is only partially transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, each essential. First sentence states purpose, second gives usage context, third explains CSV format. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists, description doesn't need to explain return values. Provides enough context for usage, though could mention error handling or confirmation of addition.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and description adds significant value by explaining the CSV format and action column values ('approve', 'reject', specific URI). Goes beyond the basic schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Add', resource 'tracks from a reviewed CSV to an existing playlist', and context 'after reviewing uncertain matches from a batch search'. Distinguishes from sibling tools like add_tracks_to_playlist and batch_search_tracks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use: 'after reviewing uncertain matches from a batch search'. Does not directly state when not to use, but context implies alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
add_tracks_to_playlistA
Add tracks to an existing playlist.
Handles batching automatically (Spotify max 100 per request).
| Name | Required | Description | Default |
|---|---|---|---|
| playlist_id | Yes | Playlist ID (not URI) | |
| track_uris | Yes | List of Spotify track URIs |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses automatic batching with a limit of 100 per request, which is useful. However, it does not mention authorization requirements, error handling, or whether duplicates are handled.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The main purpose is front-loaded, and the batching behavior is concisely stated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, return values are not needed. The tool has only two required parameters. The description covers the batching limit. However, it does not differentiate from add_reviewed_tracks or mention prerequisites like authentication.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so baseline is 3. The description adds extra clarity by specifying that playlist_id should not be a URI, and confirms track_uris are Spotify track URIs, which is slightly beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Add', the object 'tracks', and the context 'to an existing playlist'. It also mentions automatic batching, which distinguishes it from sibling tools like remove_tracks_from_playlist.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for adding tracks to a playlist but does not provide explicit guidance on when to use this tool versus alternatives like add_reviewed_tracks or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
batch_search_tracksA
Search for multiple tracks with confidence scoring.
Categorizes results:
HIGH (>= 90%): Safe to auto-add
MEDIUM (70-89%): Should review
LOW (< 70%): Needs attention
NOT FOUND: No results
| Name | Required | Description | Default |
|---|---|---|---|
| songs | Yes | List of {"title": "...", "artist": "..."} dicts | |
| delay_seconds | No | Delay between API calls (default 0.2s for rate limiting) |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses confidence scoring categories but does not mention other behaviors like rate limiting, error handling, or API call frequency. The delay_seconds parameter is described in schema but not in the main description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences and a clear list. It front-loads the main action and uses efficient structure. Every sentence provides value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and the tool's complexity, the description is fairly complete: it explains the main purpose and categorization. However, it could mention handling of failures or partial results for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add new semantics to parameters; the schema already describes songs as dicts with title/artist and delay_seconds. The confidence categories relate to output, not input parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches for multiple tracks with confidence scoring, which is a specific verb-resource combination. It distinguishes from sibling tools like search_track or search_track_fuzzy by focusing on batch search and categorization, though explicit differentiation is missing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for batch search with confidence-based categorization, but does not provide explicit guidance on when to use this tool over alternatives or when not to use it. The categorization hints at post-search actions but lacks direct usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_auth_statusA
Check if Spotify authentication is set up and working.
Returns current user info if authenticated.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description adequately discloses the tool returns user info only if authenticated, which is sufficient for a simple read-only operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the purpose and result, with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters, an existing output schema (not shown), and no annotations, the description covers the essential purpose and result, though it could mention error behavior when unauthenticated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so description adds no param info; baseline 4 applies as schema coverage is 100%.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks Spotify authentication status and returns user info, distinguishing it from all sibling tools that deal with tracks, playlists, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives guidance, but the standalone role of checking auth before other operations is implied by the sibling set.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compare_playlistsB
Compare two playlists to find shared and unique tracks.
| Name | Required | Description | Default |
|---|---|---|---|
| playlist_id_1 | Yes | First playlist ID | |
| playlist_id_2 | Yes | Second playlist ID |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states the basic function (comparison) without indicating whether the tool is read-only, whether it modifies playlists, or any authentication or rate limit requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, complete sentence with no wasted words. It is front-loaded with the action and outcome.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two string parameters and an output schema, the description covers the basic function. However, behavioral transparency gaps and lack of usage guidance reduce completeness for an agent deciding between sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters as playlist IDs with 100% coverage. The description adds no additional meaning about parameter format, source, or constraints beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ("Compare") and resource ("playlists") and clearly states the output ("shared and unique tracks"). It clearly distinguishes from siblings like 'find_duplicate_tracks' and 'get_playlist_tracks' by focusing on comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'find_duplicate_tracks' or manual track comparison. The description does not provide context for its best use or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_playlistC
Create a new Spotify playlist.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Playlist name | |
| description | No | Playlist description | |
| public | No | Whether playlist is public (default False) |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden of behavioral disclosure. It only states 'Create a new Spotify playlist' without revealing any behavioral traits like authorization requirements, rate limits, or consequences of duplicate names.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. However, it is under-informative and could include more context without becoming verbose. Every sentence should earn its place; this one barely does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema (which reduces the need to explain return values), the description lacks context about usage scenarios and behavioral nuances. For a simple creation tool, it is minimally adequate but incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with parameter descriptions. The description adds no additional meaning beyond what the schema already provides, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates a new Spotify playlist, using a specific verb and resource. However, it does not distinguish from sibling tools like 'create_playlist_from_search_results' or 'import_and_create_playlist', which also involve playlist creation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'create_playlist_from_search_results' or 'import_and_create_playlist'. There are no explicit when-to-use or when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_playlist_from_search_resultsB
Create a playlist from batch search results.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Playlist name | |
| batch_results | Yes | Results from batch_search_tracks | |
| include_confidence | No | Which confidence levels to include: - "high": Only >= 90% matches (safest) - "high_medium": >= 70% matches - "all": All matches (use with caution) | high |
| description | No | Playlist description | |
| public | No | Whether playlist is public |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It only indicates creation but does not mention side effects, idempotency, or requirements (e.g., authentication, rate limits). Insufficient for a creation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, efficient and front-loaded. However, it sacrifices necessary detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite an output schema existing, the description does not explain return values or processing of 'batch_results' and 'include_confidence'. For a tool with 5 parameters and nested objects, the description is too sparse.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema covers all parameters with descriptions. The description adds minimal value beyond the schema, only clarifying 'batch_results' as results from 'batch_search_tracks'. Baseline score of 3 is appropriate given 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'create' and the resource 'playlist from batch search results', distinguishing it from siblings like 'create_playlist' (empty playlist) and 'import_and_create_playlist' (CSV import).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after a batch search but lacks explicit when-to-use or alternatives. Siblings provide contrast, but no direct guidance on when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
export_library_summaryA
Export a complete summary of your Spotify library.
Includes:
Followed artists
Top artists by saved song count
Albums with most saved songs
| Name | Required | Description | Default |
|---|---|---|---|
| use_cache | No | Use cached data if available |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the tool as 'export' but does not clarify if it is read-only, destructive, or requires specific permissions. It mentions caching via a parameter but provides no behavioral details like side effects or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, using a single sentence and bullet points. It is front-loaded with the core action and efficiently lists included items. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, which explains return values. However, the description lacks context on what 'export' entails (e.g., file generation vs. data object) and how it differs from similar tools. With many siblings, more contextual guidance would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter (use_cache) is fully documented in the schema with description and default. The tool description adds no additional meaning beyond what the schema provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool exports a complete summary of the Spotify library, listing specific content (followed artists, top artists by song count, albums with most saved songs). This distinguishes it from sibling tools that focus on single data types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for an overview of library stats but does not explicitly state when to use this tool over siblings like get_followed_artists or get_top_artists. No when-not or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
export_playlist_to_csvA
Export a playlist to CSV format.
Great for backing up playlists or sharing song lists.
| Name | Required | Description | Default |
|---|---|---|---|
| playlist_id | Yes | Playlist ID |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It does not disclose whether the tool is read-only, any authentication requirements, rate limits, or limitations on playlist size. For an export tool, such details are important.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loads the purpose, and each sentence adds value: the first defines the action, the second suggests use cases. No redundant or unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one required parameter and an output schema (though not detailed). The description is mostly complete given the simplicity, but could mention the CSV output structure or any limits. However, it adequately covers the main use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'playlist_id' has a schema description of 'Playlist ID', and the tool description does not add additional meaning. Since schema coverage is 100%, this score is appropriate at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Export' and resource 'a playlist to CSV format', clearly distinguishing it from sibling tools like 'get_playlist_tracks' (which returns tracks in a non-CSV format) or 'create_playlist'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear use cases: 'Great for backing up playlists or sharing song lists.' However, it does not explicitly mention when not to use this tool or compare with alternatives like 'export_review_csv'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
export_review_csvA
Export medium/low confidence matches to a CSV for human review.
| Name | Required | Description | Default |
|---|---|---|---|
| batch_results | Yes | Results from batch_search_tracks |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It states the output (CSV for human review) but does not mention whether the operation is read-only, if it modifies any data, or any authentication or rate limit considerations. The description is minimal and lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It efficiently conveys the tool's purpose and context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one parameter (referencing batch_search_tracks) and an output schema, the description is reasonably complete. It explains the input source and output format (CSV for human review). However, it could mention where the CSV is saved or how it is delivered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with the parameter description in the schema being 'Results from batch_search_tracks'. The tool description does not add any additional meaning beyond what the schema already provides, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool exports medium/low confidence matches to CSV for human review. It specifies the exact resource (matches) and action (export to CSV), distinguishing it from sibling export tools like export_library_summary and export_playlist_to_csv.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used after batch_search_tracks, as the input is batch_results. However, it does not explicitly mention when to use it over alternatives or provide any exclusion criteria. The purpose is clear but lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_duplicate_tracksB
Find duplicate tracks in a playlist.
| Name | Required | Description | Default |
|---|---|---|---|
| playlist_id | Yes | Playlist ID |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose whether the tool is read-only, what constitutes a duplicate, or any side effects. Minimal behavioral info.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words, directly states the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, description need not detail return format, but could still benefit from explaining duplicate criteria or scope. Adequate but minimal.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter 'playlist_id' with schema description 'Playlist ID'. Description adds no additional meaning beyond schema. Baseline 3 due to 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb 'find' and the resource 'duplicate tracks in a playlist', distinguishing it from sibling 'remove_duplicate_tracks' which performs a different action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., remove_duplicate_tracks). No mention of prerequisites or conditions for finding duplicates.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
follow_artistsB
Follow artists on Spotify.
| Name | Required | Description | Default |
|---|---|---|---|
| artist_ids | Yes | List of Spotify artist IDs to follow |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavioral traits such as idempotency, side effects, or authentication requirements. The description carries full burden but provides minimal information beyond the action itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise and front-loaded. No fluff, but it is very brief and could benefit from additional context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description is minimally complete for a simple tool with good schema and output schema. However, it lacks context about usage limits, authentication, or output nature.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for the single parameter 'artist_ids'. The tool description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool follows artists on Spotify, using the specific verb 'Follow' and resource 'artists on Spotify'. It distinguishes from siblings like unfollow_artists and get_followed_artists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. No prerequisites or context provided. Agents must infer usage from the name and parameter.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_albums_by_song_countA
Find albums where you have N or more saved songs.
Great for finding albums worth buying on vinyl!
| Name | Required | Description | Default |
|---|---|---|---|
| min_songs | No | Minimum saved songs to include album (default 6) | |
| use_cache | No | Use cached data if available |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for disclosing behavioral traits. It does not mention read-only status, performance, or authentication needs, leaving the agent without important context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first states the action, second provides a use case. No extraneous information, front-loaded effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 non-required params, output schema exists), the description adequately covers purpose and context. Minor omissions like pagination or caching details are not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers both parameters with descriptions and defaults. The description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description specifies a clear action: 'Find albums where you have N or more saved songs.' This distinguishes it from sibling tools that deal with tracks, playlists, and artists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a specific use case ('Great for finding albums worth buying on vinyl'), implying when to use. However, it does not explicitly state when not to use or compare with alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_followed_artistsB
Get all artists you follow on Spotify.
| Name | Required | Description | Default |
|---|---|---|---|
| use_cache | No | Use cached data if available (faster, default True) |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose behavioral traits beyond the basic purpose. With no annotations, it should have mentioned caching behavior, auth requirements, or data format, but it only reiterates the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It is front-loaded and immediately conveys the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with output schema, the description is minimally adequate but lacks usage guidelines and behavioral context needed for full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the only parameter 'use_cache' has a description). The tool description adds no additional meaning to parameters, so baseline score applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Get) and resource (all artists you follow on Spotify), distinguishing it from sibling tools like follow_artists, unfollow_artists, and get_library_artists which have different scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as get_library_artists or get_top_artists. The description lacks context for selection among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_library_artistsA
Get unique artists from your saved songs, sorted by song count.
This shows artists you have saved songs from (even if not followed), ranked by how many songs you've saved.
| Name | Required | Description | Default |
|---|---|---|---|
| use_cache | No | Use cached data if available |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. It explains output (unique artists sorted by song count) and scope (saved songs, including unfollowed). However, it does not mention permissions, caching behavior, or potential limitations. With no annotations, a score of 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no unnecessary words. Front-loads the main action and then clarifies scope. Excellent structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with an output schema, the description adequately explains what it does and its scope. It could mention pagination or caching, but overall it is reasonably complete given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter (use_cache) and includes its description. The description does not add further meaning, so baseline 3 is correct.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it gets unique artists from saved songs, sorted by song count. It differentiates from siblings like get_followed_artists (followed only) and get_top_artists (likely based on listening history) by emphasizing 'even if not followed'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (when you want artists from saved songs) and contrasts with 'not followed'. It lacks explicit 'when not to use' or alternatives, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_playlist_infoC
Get information about a playlist.
| Name | Required | Description | Default |
|---|---|---|---|
| playlist_id | Yes | Playlist ID |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. 'Get information' is vague—it doesn't specify whether it returns metadata, owner, followers, or restrictions. The agent cannot infer usage constraints or side effects (e.g., read-only).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, no redundant information. It is appropriately concise for a simple tool. Slightly reduced because it could be more informative without adding length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (not shown), the description should clarify what information is returned. With 15+ sibling tools, more context is needed to differentiate behavior. The single sentence leaves the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description of playlist_id as 'Playlist ID' is adequate but adds no extra meaning. The description does not elaborate on how the parameter is used. A 3 is baseline for high coverage with minimal additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a clear verb ('Get') and resource ('information about a playlist'), which is specific enough. However, it does not distinguish from siblings like get_playlist_tracks, which also retrieves playlist data but focuses on tracks. A 4 reflects good clarity but missing differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs. alternatives like get_playlist_tracks or compare_playlists. The description lacks context for selection, making it difficult for an AI agent to choose correctly among many siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_playlist_tracksA
Get all tracks from a playlist.
| Name | Required | Description | Default |
|---|---|---|---|
| playlist_id | Yes | Playlist ID |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Given no annotations, the description bears full burden for behavioral disclosure. It only states it retrieves tracks but doesn't mention important traits like pagination, limit, ordering, or read-only nature. The simple statement doesn't contradict any annotations since none exist, but it is minimally informative.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, clear sentence with no wasted words. It is front-loaded and appropriately brief for a simple retrieval tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (for return values) and only one required parameter, the description is nearly complete. It could mention pagination if applicable, but for a simple list retrieval of all tracks, it is adequate. The description covers the essential purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (one parameter described as 'Playlist ID'). The description adds no extra meaning beyond the schema; it just restates what the parameter is. Baseline 3 is appropriate since the parameter is adequately documented in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get all tracks from a playlist' is a specific verb+resource combination that clearly states the tool's function. It implicitly distinguishes from siblings like 'get_playlist_info' which likely retrieves metadata, not the track list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a playlist's track list is needed, but it lacks explicit guidance on when to use this tool versus alternatives (e.g., search_track) or any prerequisites (e.g., ownership, authentication). No when-not-to-use or alternative naming is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_recently_playedC
Get your recently played tracks.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of results (max 50) |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not mention any behavioral traits, such as whether the operation is read-only, what data is returned, or any side effects. This is insufficient for an agent to predict behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with one sentence. It is front-loaded but may be too brief to provide sufficient guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and 30 sibling tools, the description lacks context about what 'recently played' means, time window, or how it differs from similar tools like 'get_saved_tracks'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'limit' is fully described in the input schema with default and max values. The description adds no additional meaning, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get your recently played tracks' clearly states it retrieves recently played tracks, distinguishing it from siblings like 'get_saved_tracks' or 'get_top_tracks'. However, it does not further differentiate from similar tools like 'get_recently_played' itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites, limitations, or specific scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_saved_tracksA
Get all your liked/saved songs on Spotify.
Note: This may take 1-2 minutes for large libraries (10k songs).
| Name | Required | Description | Default |
|---|---|---|---|
| use_cache | No | Use cached data if available (faster, default True) |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that retrieval may take 1-2 minutes for large libraries, which is a useful behavioral trait. However, it does not mention that it is read-only or any other side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose, followed by a concise note. No superfluous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one optional parameter) and presence of an output schema, the description is mostly complete. It could add a note about pagination or result format, but the output schema compensates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter (use_cache) well-described in the schema. The description adds context by explaining the latency implication, which helps understand when to use cache.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the exact resource 'all your liked/saved songs on Spotify'. This distinguishes it from sibling tools like get_playlist_tracks which operate on specific playlists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. The note about latency for large libraries implies a consideration but does not give alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_top_artistsA
Get your top artists based on listening history.
Great for understanding your music taste and finding festival lineups.
| Name | Required | Description | Default |
|---|---|---|---|
| time_range | No | Time period: - "short_term": Last 4 weeks - "medium_term": Last 6 months (default) - "long_term": All time | medium_term |
| limit | No | Number of results (max 50) |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description lacks behavioral details such as authentication needs, rate limits, or data format expectations. The existence of an output schema partially mitigates this, but the description itself offers little beyond purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences, each adding value: the first defines the action and the second provides use cases.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high schema coverage and presence of an output schema, the description is adequate but lacks usage guidelines and behavioral transparency, making it only somewhat complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions for both parameters. The description adds no additional meaning beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'your top artists based on listening history,' distinguishing it from sibling tools like get_top_tracks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for understanding taste and festival lineups but provides no explicit guidance on when to use this tool versus siblings or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_top_tracksA
Get your top tracks based on listening history.
| Name | Required | Description | Default |
|---|---|---|---|
| time_range | No | Time period: - "short_term": Last 4 weeks - "medium_term": Last 6 months (default) - "long_term": All time | medium_term |
| limit | No | Number of results (max 50) |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description is minimal. For a simple read operation, it's adequate but doesn't disclose authentication requirements or output behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise one-sentence description with no filler; front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With output schema present and clear parameter schema, the description is sufficient for this simple tool; minor omission is explanation of return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with clear parameter descriptions; description adds no extra meaning beyond 'get your top tracks'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool retrieves top tracks based on listening history, which is specific and distinct from siblings like get_top_artists or get_recently_played.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Could mention it's for personal listening history as opposed to curated playlists or artist data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_track_preview_urlA
Get the 30-second preview URL for a track.
| Name | Required | Description | Default |
|---|---|---|---|
| track_uri | Yes | Spotify track URI (e.g., "spotify:track:xxx") |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose more. It specifies the preview is 30 seconds and returns a URL, but doesn't mention authentication requirements, potential null responses for tracks without previews, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no wasted words. The key information is front-loaded: what it does and what it returns.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and output schema, the description is adequate. It could note that the preview might not exist for all tracks, but overall it is complete for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description. The tool description adds no extra parameter meaning beyond what's in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the specific resource '30-second preview URL for a track', distinguishing it from sibling tools like search or modify operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives; it is implied that it is used when a preview URL is needed, but no when-not-to or alternative mentions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
import_and_create_playlistA
Full workflow: Parse song list CSV, search all tracks, create playlist.
This is the main tool for bulk playlist creation from a list of songs.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Playlist name | |
| csv_content | Yes | CSV content with columns: title, artist | |
| include_confidence | No | "high", "high_medium", or "all" | high |
| description | No | Playlist description | |
| public | No | Whether playlist is public |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full transparency burden. It outlines the workflow (parse, search, create) but does not disclose potential issues like missing tracks, authentication requirements, or rate limits. The high-level steps are clear but lack detail on side effects or failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no redundant information. The first sentence efficiently lists the three steps, and the second reinforces the tool's primary use case. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking annotations, the description covers the main workflow and purpose. An output schema exists to document return values, so that gap is mitigated. However, it could mention input validation or performance implications for a multi-step tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds limited value beyond the schema. It contextualizes parameters (e.g., `csv_content` is for parsing, `name` for playlist), but does not elaborate on formats or constraints. Baseline score of 3 is appropriate given full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the tool's action: 'Parse song list CSV, search all tracks, create playlist.' It distinguishes itself from siblings like `create_playlist` (which only creates an empty playlist) and `parse_song_list_csv` (which only parses). The phrase 'main tool for bulk playlist creation' reinforces its specific role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states this is 'the main tool for bulk playlist creation from a list of songs,' providing clear context for when to use it. However, it does not explicitly mention when to avoid it or list alternatives, though the sibling set implies options for other scenarios (e.g., adding tracks individually).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
parse_song_list_csvA
Parse a CSV of songs into a structured list.
Use this to validate your CSV before batch searching.
| Name | Required | Description | Default |
|---|---|---|---|
| csv_content | Yes | CSV content as string |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It states parsing into a structured list but doesn't explicitly confirm it's a read-only operation or describe error handling. Adequate for a simple parsing tool, but not highly transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first explains the action, second adds usage context. No wasted words, perfectly front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (one parameter, output schema exists), the description covers the core purpose and usage. It could optionally mention the output format, but the output schema handles that. Complete enough for the complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter described as 'CSV content as string'. The description adds no extra semantic detail beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'parse' and resource 'CSV of songs', and it distinctly differs from sibling tools which perform actions like searching, adding, or updating.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this to validate your CSV before batch searching', providing clear guidance on when to use it. It implies a precondition but doesn't mention alternatives or when not to use, though the context makes it obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
remove_duplicate_tracksA
Remove duplicate tracks from a playlist, keeping the first occurrence.
For safety, returns a preview unless confirm=True.
| Name | Required | Description | Default |
|---|---|---|---|
| playlist_id | Yes | Playlist ID | |
| confirm | No | Set to True to actually remove duplicates |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations were provided, so the description must disclose behavioral traits. It reveals the safety preview behavior and that confirm=True triggers actual removal. It could mention permissions or irreversibility, but the key safety mechanism is well explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences that convey the core functionality and safety behavior. Every word is necessary, with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, straightforward action) and the presence of an output schema, the description adequately covers the essential information. It could be slightly more thorough about edge cases, but it is sufficient for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides parameter descriptions (playlist_id: 'Playlist ID', confirm: 'Set to True to actually remove duplicates'). The description adds value by noting that duplicates are removed keeping the first occurrence and that a preview is returned unless confirm=True, which clarifies the parameter's effect.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool removes duplicate tracks from a playlist while keeping the first occurrence, which is a specific verb+resource. It distinguishes itself from siblings like 'find_duplicate_tracks' (which likely only finds duplicates) and 'remove_tracks_from_playlist' (which removes specific tracks).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that a preview is returned by default and that setting confirm=True actually removes duplicates, guiding when to use the confirm parameter. It does not explicitly mention when not to use this tool, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
remove_tracks_from_playlistA
Remove specific tracks from a playlist.
For safety, returns a preview unless confirm=True.
| Name | Required | Description | Default |
|---|---|---|---|
| playlist_id | Yes | Playlist ID | |
| track_uris | Yes | List of Spotify track URIs to remove | |
| confirm | No | Set to True to actually remove |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description effectively discloses the default preview behavior (safe) and the condition to actually remove (confirm=True), which is critical for an agent to use correctly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no unnecessary words; the key information (action, safety preview, confirm requirement) is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description sufficiently covers the tool's core behavior and safety semantics without requiring elaboration on return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters are described in the schema; the description adds value by explaining the safety logic (preview unless confirm), which goes beyond individual parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Remove' and the resource 'specific tracks from a playlist', distinguishing it from siblings like add_tracks_to_playlist or reorder_playlist_tracks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear guidance on the preview behavior and the confirm parameter, but does not explicitly contrast with alternative removal tools like remove_duplicate_tracks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
reorder_playlist_tracksC
Move tracks within a playlist.
| Name | Required | Description | Default |
|---|---|---|---|
| playlist_id | Yes | Playlist ID | |
| range_start | Yes | Position of first track to move (0-indexed) | |
| insert_before | Yes | Position to insert before (0-indexed) | |
| range_length | No | Number of tracks to move (default 1) |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist. Description does not disclose behavioral traits such as atomicity, persistence, authorization needs, or whether tracks are physically moved. Very minimal for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single short sentence is concise but under-specifies the operation. Could be considered too terse for a tool with 4 parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the mutation nature requires more context (e.g., side effects, permissions). Description fails to provide necessary behavioral context beyond the obvious.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter descriptions in the schema. The tool description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Move' and resource 'tracks within a playlist'. Distinguishes from sibling tools like add/remove tracks, but could be ambiguous if moving between playlists; schema clarifies within.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. Siblings like add_tracks_to_playlist, remove_tracks_from_playlist, update_playlist are available but no differentiation provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
save_tracksA
Save tracks to your Spotify library (like/heart them).
| Name | Required | Description | Default |
|---|---|---|---|
| track_ids | Yes | List of Spotify track IDs to save |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It states the action but omits details such as whether saving duplicates has an effect, authentication requirements, rate limits, or idempotency. This leaves significant gaps for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with parenthetical clarification is extremely concise and front-loaded. Every word adds value, and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, straightforward action), the description is minimally adequate. However, it lacks behavioral transparency and usage guidelines, which reduces completeness. The presence of an output schema helps slightly but is not fully leveraged.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides a clear description for the only parameter ('List of Spotify track IDs to save'), and coverage is 100%. The tool description adds no additional semantic information beyond the schema, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'Save tracks' and resource 'Spotify library' with parenthetical 'like/heart them', making the action unambiguous. It distinguishes from siblings like 'add_tracks_to_playlist' (saves to playlist) and 'unsave_tracks' (removes).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies usage for saving tracks to library but provides no explicit guidance on when to use this tool versus alternatives like 'add_tracks_to_playlist' or 'unsave_tracks'. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_trackC
Search for a single track and get matches with confidence scores.
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | Track title | |
| artist | Yes | Artist name | |
| limit | No | Max results to return (default 5) |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Only mentions confidence scores, but omits behavioral traits like search algorithm (exact/partial), whether combining title and artist is AND/OR, read-only nature, rate limits, or error conditions. Minimal disclosure beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence efficiently conveys core purpose and output. Front-loaded with verb. Not overly long, but could include a tiny bit more detail without losing conciseness. Earns high marks for lack of fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the search tool's complexity and multiple siblings, the description is incomplete. It does not explain how search parameters are combined, whether matching is fuzzy or exact, or what confidence scores represent. Output schema exists but description should still provide high-level context. Significant gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 3 parameters. Description adds no extra meaning beyond schema (e.g., does not specify how title/artist interact). Baseline 3 is appropriate as schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear statement of action ('Search for a single track') and output ('matches with confidence scores'). Implicitly differentiates from batch_search_tracks and search_track_fuzzy by mentioning 'single track', but doesn't explicitly contrast. Loses 1 point for lack of explicit sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., search_track_fuzzy, batch_search_tracks). No context on prerequisites or when not to use. A strong description would clarify exact vs fuzzy matching or batch searching.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_track_fuzzyA
Broader fuzzy search when exact match fails.
Tries multiple strategies:
Exact title + artist
Title only
Simplified title (removing parentheses, etc.)
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | Track title | |
| artist | Yes | Artist name | |
| limit | No | Max results per strategy |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes the multiple strategies attempted and implies fallback behavior. Lacks details on rate limits or authentication, but the core behavior is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise: three short, front-loaded sentences that convey the main purpose, then details. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Has output schema, so return values are covered. Description addresses when to use and strategies, but lacks mention of pagination or empty results behavior. Still quite complete given tool complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage, baseline 3. Description adds meaning by explaining how title and artist are used across strategies (exact match, title-only, simplified). This gives the agent a better understanding of parameter roles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it performs a broader fuzzy search when exact match fails, and lists specific strategies. This distinguishes it from sibling tool 'search_track' which presumably does exact search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'when exact match fails', implying usage context. Lists strategies but does not explicitly state when not to use or provide alternatives. However, the context and sibling names give enough guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
unfollow_artistsA
Unfollow artists on Spotify.
For safety, returns a preview unless confirm=True.
| Name | Required | Description | Default |
|---|---|---|---|
| artist_ids | Yes | List of Spotify artist IDs to unfollow | |
| confirm | No | Set to True to actually unfollow (default False for preview) |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the preview behavior, which is a key safety trait. However, it does not mention potential side effects (e.g., irreversibility) or rate limits, but the preview mitigates risk.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, highly concise. Every word adds value. No fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the purpose and safety preview behavior. With an output schema present, the lack of detailed return value explanation is acceptable. It could mention that unfollowing is immediate, but overall it is sufficiently complete for a simple operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add new information beyond what the schema already provides for the parameters. The safety note about 'confirm' is already in the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Unfollow artists on Spotify', which is a specific verb and resource. This distinguishes it from the sibling tool 'follow_artists'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear usage guideline: 'For safety, returns a preview unless confirm=True.' This tells the agent to first preview before actually unfollowing, which is good safety practice. However, it does not explicitly mention when to use this tool versus alternatives like follow_artists.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
unsave_tracksA
Remove tracks from your Spotify library.
For safety, returns a preview unless confirm=True.
| Name | Required | Description | Default |
|---|---|---|---|
| track_ids | Yes | List of Spotify track IDs to remove | |
| confirm | No | Set to True to actually remove (default False for preview) |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the preview behavior and confirm flag for safety, which is crucial for a mutation tool. No annotations exist, so description carries burden well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no redundant text. Purpose is front-loaded, safety note is clear and brief.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose and key behavior. Output schema exists for return details. Lacks mention of prerequisites like authentication, but minor given simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters. Description adds value by explaining the safety mechanism (preview unless confirm=True), which goes beyond schema defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Remove' and resource 'tracks from your Spotify library'. Distinguishes from sibling tools like 'save_tracks' and 'remove_tracks_from_playlist'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides guidance on the confirm parameter for safety, but does not explicitly contrast with alternatives like 'remove_tracks_from_playlist'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_playlistB
Update playlist details (name, description, public status).
Only provide the fields you want to change.
| Name | Required | Description | Default |
|---|---|---|---|
| playlist_id | Yes | Playlist ID | |
| name | No | New playlist name (optional) | |
| description | No | New playlist description (optional) | |
| public | No | New public status (optional) |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It states 'update' which implies mutation, but does not disclose any side effects, prerequisites (e.g., authentication, ownership), error behavior, or irreversibility. This is insufficient for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences with no wasted words. It front-loads the core action and then provides an essential usage hint, making it efficient for quick parsing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (covering return values) and the parameter schema is fully documented, the description captures the core functionality and the partial update nuance. However, it lacks behavioral transparency (e.g., requirements, errors), which lowers completeness for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters, but the description adds valuable usage semantics beyond the schema: emphasizing that all fields except 'playlist_id' are optional and only those to be changed should be provided. This helps the agent understand the partial update pattern.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'update' and the resource 'playlist details' with specific fields (name, description, public status). It distinguishes from sibling tools like 'create_playlist' and 'add_tracks_to_playlist' by focusing on metadata changes, but could be more explicit about not adding or removing tracks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a partial update hint ('Only provide the fields you want to change'), but provides no guidance on when to use this tool versus alternatives like 'create_playlist' or 'get_playlist_info'. It lacks context for appropriate usage scenarios and excludes when-not-to-use information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
33 tool updates
v0.1.1- First observed
add_reviewed_tracks - First observed
add_tracks_to_playlist - First observed
batch_search_tracks - First observed
check_auth_status - First observed
compare_playlists - First observed
create_playlist - First observed
create_playlist_from_search_results - First observed
export_library_summary - First observed
export_playlist_to_csv - First observed
export_review_csv - First observed
find_duplicate_tracks - First observed
follow_artists - First observed
get_albums_by_song_count - First observed
get_followed_artists - First observed
get_library_artists - First observed
get_playlist_info - First observed
get_playlist_tracks - First observed
get_recently_played - First observed
get_saved_tracks - First observed
get_top_artists - First observed
get_top_tracks - First observed
get_track_preview_url - First observed
import_and_create_playlist - First observed
parse_song_list_csv - First observed
remove_duplicate_tracks - First observed
remove_tracks_from_playlist - First observed
reorder_playlist_tracks - First observed
save_tracks - First observed
search_track - First observed
search_track_fuzzy - First observed
unfollow_artists - First observed
unsave_tracks - First observed
update_playlist
TDQS
Scored across 33 tools
Each tool has a clearly defined purpose, with distinct boundaries between batch search, single search, fuzzy search, and playlist operations. The descriptions provide clear differentiation, even for similar tools like batch_search_tracks and search_track.
All tool names follow a consistent verb_noun pattern, using underscores and descriptive verbs. There are no mixed conventions or vague names, making the toolset predictable for an agent.
With 33 tools, the count is high but justified by the comprehensive scope of bulk Spotify operations, including search, playlist management, library actions, and CSV workflows. It is slightly above the typical range but each tool serves a distinct purpose.
The tool set covers the full lifecycle of bulk actions: authentication, search with confidence scoring, playlist creation and modification, duplicate management, library operations, and CSV import/export. No obvious gaps are present for the stated purpose.
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