★ SEC 8-K — recent MATERIAL EVENTS (earnings, exec changes, M&A, restatements).
Catalysts that should move or confirm an analyst's thesis, point-in-time by filing date. Item codes are mapped to plain language (2.02=earnings, 5.02=exec change, 4.02=restatement red flag, 7.01=guidance…). Free, keyless. Not advice.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | ||
| since_days | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that the tool is free, keyless, and not advice, and explains item code mappings. However, it lacks details on rate limits, data refresh frequency, or whether historical data beyond since_days is available, leaving some behavioral gaps.
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, using bullet-style formatting with a star symbol to draw attention. Every sentence adds value, but it could be better structured with explicit sections.
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 but is not described in the input. The description adequately covers the tool's purpose and basic behavior, but given the lack of behavioral transparency and parameter semantics, it is not fully complete for an agent to invoke correctly without additional inference.
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 0%, so the description must compensate. It does not explicitly describe the 'ticker' or 'since_days' parameters, though the context implies ticker is a stock symbol and since_days relates to recency. This is insufficient given the zero 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 tool retrieves SEC 8-K filings for recent material events like earnings, exec changes, M&A, and restatements. It specifies the verb 'get' implicitly and distinguishes from sibling tools (e.g., insider_activity, fundamentals) by focusing on a specific SEC filing type.
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 context for when to use the tool (e.g., to get catalysts that move an analyst's thesis, by filing date). However, it does not explicitly state when not to use it or compare to alternatives, though the context is clear enough.
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.
Most tools have clearly distinct purposes (e.g., analyst_views fetches views, analyst_debate compares them, analyst_track_record scores accuracy). Some overlap exists between sentiment tools (stocktwits_symbol, ticker_social_sentiment) but descriptions clarify boundaries. Overall, an agent can differentiate them.
Naming is mostly lowercase with underscores, but conventions vary: some use prefixes (analyst_, direction_review_), some are single words (quote, leaderboard), and others are verb_noun (score_ticker, screen_stocks). This inconsistency makes patterns less predictable, though prefixes help group related tools.
With 24 tools, the server is slightly above the ideal range of 3-15 for coherence. While each tool seems justified for the financial analysis domain, the volume could be overwhelming. Some tools (e.g., tweet_store_stats, direction_review_batch) are operator-only, reducing the surface for typical agents.
The tool set covers core workflows: fetching analyst views, tracking accuracy, SEC fundamentals, insider activity, material events, live quotes, social sentiment, and screening. Gaps like earnings calendar or portfolio management are minor given the focus on analyst-driven analysis. The operator tools for direction review add internal completeness.