Analyst rating actions and price-target changes from the newswire: analyst_firm, analyst_name, action_company (Maintains/Initiates), action_pt (Raises/Lowers), pt_current, pt_prior, pt_pct_change, rating_current/prior. Call this when the user asks about upgrades, downgrades, or price-target moves on a ticker.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| action | No | ||
| date_to | No | ||
| tickers | No | ||
| date_from | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description must fully explain behavior. It only states the data source (newswire) and lists output fields, but says nothing about whether the operation is read-only, how results are sorted/paginated, date-range handling, or any side effects. This leaves significant ambiguity for an agent.
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 a single sentence followed by a comma-separated field list. It is reasonably concise but the field list makes it a bit dense. The primary purpose and usage hint are front-loaded, so it loses little time for readers.
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 annotations, no output schema, and 5 unannotated parameters, the description needs to fill many gaps. It provides clear purpose and usage context, but lacks parameter explanations, behavior details, and return-format guidance. It is sufficient only for a high-level understanding, not for reliable invocation.
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 5 parameters with 0% coverage from the description. The description mentions 'ticker' and upgrades/downgrades, hinting at the `tickers` and `action` parameters, but does not map these to actual parameter names or clarify formatting (e.g., date formats, comma-separated tickers, enum values). The field list in the description pertains to output, not input parameters, adding limited semantic value.
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 reports 'Analyst rating actions and price-target changes from the newswire', which is specific about the resource and verb. It also enumerates key output fields, distinguishing it from related tools like consensus or news ratings. The phrase 'upgrades, downgrades, or price-target moves' directly addresses typical user intents.
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 an explicit 'when to use' directive: 'Call this when the user asks about upgrades, downgrades, or price-target moves on a ticker.' However, it does not mention when not to use it or point to alternatives, so it lacks the fuller guidance expected for a top score.
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.
