Open a community watchlist by its slug — see the full list of constituents (tickers, sector, industry, asset type) plus follower count. Use the slug returned by discover_community_watchlists.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Watchlist slug, e.g. 'ai-and-tech-infrastructure' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful behavioral context by detailing the return contents (constituents with tickers, sector, industry, asset type and follower count), which is not visible in the annotations or schema. This is valuable beyond the structured data.
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 filler. The purpose is front-loaded in the first sentence, and the second sentence adds a targeted usage hint. 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?
With only one parameter and no output schema, the description provides adequate context: what the tool does, what it returns, and how to obtain the input. It could mention potential limitations (e.g., no pagination or lack of access to private watchlists), but for a simple retrieval tool with strong annotations, the description is sufficiently 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% and the slug parameter already has a type and example. The description adds meaning by explaining where to obtain the slug ('returned by discover_community_watchlists'), which gives the agent practical guidance on parameter provenance, going beyond the schema's basic definition.
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 ('Open') and resource ('community watchlist by its slug'), and explicitly states what will be seen ('full list of constituents... plus follower count'). It distinguishes itself from sibling tools like discover_community_watchlists (which is for browsing) and get_my_watchlists (which is for personal watchlists) by emphasizing 'community watchlist'.
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 clear when-to-use directive: 'Use the slug returned by discover_community_watchlists.' This not only tells the user the prerequisite but also points to the correct preceding tool, making it obvious how this fits into a workflow and differentiating it from alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
With 57 tools, most have distinct purposes (market data, journaling, watchlists). A few related tools (get_price_alignment vs get_crypto_price_alignment, get_market_pulse vs get_market_movers) could cause miselection, but descriptions clarify asset types and scope.
Tools predominantly use get_/list_/create_/update_/delete_ verbs with clear noun suffixes. Minor deviations like start_here, whoami, add_to_watchlist, and remove_from_watchlist break the pure verb_noun pattern, but the style is consistent and readable.
At 57 tools, the server is far beyond the well-scoped range. While the domain is broad, this many tools will overwhelm an agent's capability to select accurately, and many could be consolidated (e.g., separate financial statements).
The server covers watchlist CRUD, trading journaling, market data (fundamentals, statements, news, transcripts), analysis tools, and community features. No obvious dead ends; lifecycle coverage is thorough for the described domain.
