SEC EDGAR cash-flow statements for a ticker — operating, investing, and financing flows per period, quarterly or annual (default quarterly, last 8 periods). Call this when the user asks about cash generation, capex, buybacks, or how earnings convert to actual cash.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| period | No | quarterly | |
| ticker | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits. It only states the data content and defaults, but omits any mention of read-only nature, potential data latency or limitations (e.g., SEC EDGAR filing delays), or response format. An agent cannot infer side effects or edge cases from this 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 two sentences, each earning its place. The first sentence concisely defines the tool's purpose and defaults; the second gives actionable usage guidance. No redundant or vague wording.
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 no output schema and no annotations, the description should explain return structure and limitations. It covers the core content (operating/investing/financing flows) and usage scenarios, but lacks mention of the 'ttm' period option, potential data availability issues, or response format. Adequate for a simple data-retrieval tool, but with clear gaps.
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 mentions 'quarterly or annual' and 'last 8 periods,' which partially mirrors the schema defaults, but does not explain the 'ttm' enum option, nor does it define the meaning or constraints of 'limit' or 'ticker' beyond the obvious. The omission of 'ttm' could mislead the agent into thinking only two period values exist.
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 identifies the tool as retrieving SEC EDGAR cash-flow statements, listing the specific components (operating, investing, financing flows) and period options. This distinguishes it from sibling tools like balance sheets or income statements, and the verb 'cash-flow statements for a ticker' is precise.
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 explicit usage scenarios ('Call this when the user asks about cash generation, capex, buybacks, or how earnings convert to actual cash'). However, it does not provide any 'when not to use' guidance or mention alternative tools, which would push it to a 5.
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 336 tools, there is substantial overlap. Over a dozen health/status tools share nearly identical 'is the system healthy?' descriptions (e.g., tengu_status, tengu_ready, tengu_ml_health, tengu_v3_system_health, tengu_v3_stream_status), and multiple single-ticker analysis (tengu_ml_predict, tengu_copilot_score_ticker, tengu_v3_intel_ml_prediction) and top-picks (tengu_copilot_top_picks, tengu_ml_top_picks, tengu_v3_trade_setups) tools have poorly defined boundaries. Agents would frequently misselect.
The server mixes no-version (tengu_crypto), v2 (tengu_v2_drift), v3 (tengu_v3_intel_*), and copilot (tengu_copilot_*) families, and within families there is inconsistent verb/noun ordering (tengu_v3_research_fetch_url vs tengu_v3_news_summary). While subfamilies like tengu_v3_private_markets_* are internally consistent, the overall naming pattern is chaotic and unpredictable.
336 tools is far beyond any reasonable tool set size, even for an all-in-one financial data platform. This extreme count creates choice paralysis, high latency in tool selection, and makes the server effectively unusable for autonomous agents. The calibration guideline marks 50+ as extreme; this is nearly 7x that threshold.
The platform covers a vast domain: equity and crypto prices, fundamentals, insider trading, options, news (including crypto and FX), private markets, streaming data, risk metrics, and execution planning. There are minor gaps (no direct multi-ticker comparison tool, no order placement), but the surface is remarkably comprehensive for an analysis-focused server.
