koalcheck

insider_activity

★ SEC Form 4 — are company INSIDERS buying or selling this ticker?

Open-market purchases/sales by officers, directors, and 10% owners (Section 16), point-in-time and KEYLESS from SEC EDGAR. Corroborates an analyst's view: "analyst bullish AND insiders buying" = high conviction; "analyst bullish BUT insiders dumping" = a contradiction worth flagging. Free. Analytics, not advice.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`ticker`	Yes
`since_days`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

B3.4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, description mentions 'point-in-time and KEYLESS' and 'Free. Analytics, not advice.' but does not fully disclose behavioral traits like mutation, idempotency, or rate limits. Adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Reasonably concise and front-loaded with key purpose, though contains some marketing language (★, 'Free. Analytics, not advice.') that could be trimmed without loss of clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has output schema so return values are covered, but input parameters are undocumented in description. Lacks behavioral details like error handling or pagination, leaving gaps despite low complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Description does not explain the 'since_days' parameter at all; only implicitly references 'ticker'. With 0% schema coverage, the description fails to add meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool provides SEC Form 4 insider transactions for a given ticker, distinguishing it from analyst and other sibling tools. The purpose is specific and well-defined.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance on when to use in conjunction with analyst views, e.g., corroborating bullish/bearish signals. Lacks explicit contraindications but offers clear context for combined use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.5/5.0

Disambiguation4/5

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 Consistency3/5

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.

Tool Count3/5

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.

Completeness4/5

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.

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