Max-pain price per options expiration for one ticker from the options-flow feed. Call this when the user asks where a stock is likely to pin into expiry or what the max-pain level is; pair with tengu_v3_intel_gex for aggregate gamma/delta exposure.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | Path parameter 'ticker' (required). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the data source ('from the options-flow feed'), the output granularity ('per options expiration'), and the scope constraint ('one ticker'). While it doesn't explicitly state read-only nature or return format, these are implied strongly, and the added context about the feed and pairing adds meaningful behavioral insight beyond the name and schema.
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 usage guidance without any fluff. Every sentence earns its place, and the structure is highly efficient.
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?
Given no output schema and no annotations, the description covers the essential context: what it returns (max-pain price per expiration), the source (options-flow feed), when to use it, and how it relates to a specific sibling. It doesn't detail the response structure or limitations, but for a one-parameter lookup, the context is largely sufficient.
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?
The schema has one parameter 'ticker' with minimal description ('Path parameter (required)'). Schema coverage is 100%, so baseline is 3. The description does slightly enrich the parameter by specifying 'one ticker' and referring to a stock, but it doesn't add format or examples. It provides marginal added meaning beyond the schema.
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 defines the tool as returning max-pain price per options expiration for a single ticker from the options-flow feed. It uses a specific resource ('max-pain price') and scope ('one ticker', 'per options expiration'), and distinguishes it from the sibling tool tengu_v3_intel_gex by noting the latter provides aggregate gamma/delta exposure.
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?
Explicit usage instructions are provided: 'Call this when the user asks where a stock is likely to pin into expiry or what the max-pain level is' and it recommends pairing with tengu_v3_intel_gex for aggregate gamma/delta exposure. This clearly indicates when to use this tool versus 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 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.
