tengu_logs
Recent service log lines. Call when the user asks whether the system/data pipeline is healthy or why data looks missing/stale and status alone doesn't explain it.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Recent service log lines. Call when the user asks whether the system/data pipeline is healthy or why data looks missing/stale and status alone doesn't explain it.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says logs are 'recent service log lines' and gives a call trigger; it does not disclose output format, verbosity, time window, or any limitations. Since the tool reads logs, it is likely read-only, but that is not stated.
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 with front-loaded substance: first what the tool returns, then when to use it. Every sentence earns its place, and there is no filler or repetition of schema information.
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?
The tool is simple—zero params and no output schema—but the description leaves operational details vague. It does not specify how 'recent' is defined, how many lines are returned, or whether output is raw text or structured. It provides enough to select the tool appropriately, but not full clarity on what the agent will receive.
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 input schema has zero properties, so there are no parameter semantics to add. With 0 params, the baseline is 4, and the description's 'recent' implies a default time window without needing to document parameters that don't 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 opens with 'Recent service log lines,' which clearly identifies the resource and what the tool provides. It also differentiates from sibling status/health tools by framing logs as the diagnostic next step when 'status alone doesn't explain it.'
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 explicitly states when to call: when the user asks about system/data pipeline health or missing/stale data and status alone is insufficient. It does not name sibling tools or list explicit when-not scenarios, but the condition 'status alone doesn't explain it' implies that status tools should be tried first.
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.