Recent news mentioning a ticker, with article-level sentiment. Mirrors what the website shows in /analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Up to 20 articles; default 10 | |
| ticker | Yes | Stock, ETF, or crypto ticker (e.g. AAPL, SPY, BTC-USD) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering safety expectations. The description adds the article-level sentiment detail and the 'mirrors /analysis' context, which provides some behavioral insight beyond annotations but does not disclose return format, pagination, 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 two sentences, front-loaded with the core purpose, and includes a useful website-mirroring note. Every word earns its place; 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?
For a tool with two parameters, clear annotations, and no output schema, the description provides sufficient context about the data source and sentiment feature. It does not explain return structure, but the 'mirrors /analysis' hint partially compensates for the lack of an output schema, making it reasonably complete though not exhaustive.
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%, with both 'ticker' and 'limit' fully described in the schema. The description mentions ticker and sentiment but adds no new parameter semantics beyond what the schema already provides, so the 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 retrieves recent news for a ticker with article-level sentiment, which is specific and distinguishes it from financial data or watchlist tools. The mention of mirroring the website's /analysis page adds clarity about the source and scope.
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 news lookup but does not explicitly state when to prefer it over alternatives like get_mood_for_ticker or get_market_pulse. The mirror note provides some context but no exclusions or alternative tool names, so usage guidance is implied rather than explicit.
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.
