Skip to main content
Glama

tengu-firm

by io.github.Hlobo-dev

tengu_v3_skills_apex_equity

Apex Equity Intelligence — single-call omnibus brief for 'what do you think about $TICKER'. Fuses 12 vendor calls in parallel (daily + hourly charts, company facts, income/balance statements, snapshot, insider, congress, lobbying, gov-contracts, WSB, patents, off-exchange). Returns: 'fundamentals' (12 scalar fields — name, sector, market_cap, last_price, day_change_pct, latest_revenue, latest_net_income, latest_eps, total_assets/liabilities/equity, filing_date), 'intel' (8 scalar fields — insider/congress 30d buy-sell counts, ttm_lobbying_usd, ttm_gov_contract_usd, wsb_7d_mentions+sentiment, patent_filings_recent, avg_dark_pool_pct_30d), 'flags' (notable patterns: insider_cluster_buy/sell, elevated_dark_pool, retail_attention_spike, etc.), 'chart' (primary daily 120-bar candlestick PNG with RSI/MACD/BB indicators, palette-quantized to keep the tool result under 32KB), and 'charts' (a list of ADDITIONAL charts beyond the primary — currently just the hourly intraday chart; do NOT expect the daily here, it's only in 'chart'). 'components' carries raw counts of items behind each digest. 'vendor_errors' is non-empty when one of the parallel fetches failed; the rest of the payload is still usable. For full per-section detail (complete insider trade list, full income statements, etc.) call the dedicated tools tengu_v3_fundamentals_*/tengu_v3_intel_* — apex_equity is the digest, not the firehose.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesPath parameter 'ticker' (required).

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries full burden. It discloses parallel vendor calls, the vendor_errors field for failed fetches (rest usable), palette-quantization for size limits, and the structure of charts vs charts. It also explains that 'components' carries raw counts, giving transparent insight into behavior beyond a simple return value.

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?

The description is long but information-dense, with clear section names ('fundamentals', 'intel', 'flags', etc.) and examples. Every sentence provides value, though the lengthy enumeration of fields could be seen as slightly over-detailed for a tool description.

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

Completeness5/5

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

Without an output schema, the description thoroughly explains the return structure, listing all major fields and their contents, including vendor_errors and flags. It also points to detailed tools, making the description fully adequate for a complex multi-section tool.

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

Parameters3/5

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

The only parameter 'ticker' has schema description 'Path parameter ticker (required)' with 100% coverage, so baseline is 3. The description does not add extra semantic detail (e.g., format, exchange suffixes), only using '$TICKER' as a placeholder, which does not meaningfully enrich 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?

The description clearly states the tool's purpose as a 'single-call omnibus brief for what do you think about $TICKER' and explains it fuses 12 vendor calls into a digest. It explicitly distinguishes itself from the detailed sibling tools by calling itself 'the digest, not the firehose', which aids selection.

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

Usage Guidelines5/5

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

The description gives explicit guidance on when to use this tool ('what do you think about $TICKER') and when to use alternatives: 'For full per-section detail... call the dedicated tools tengu_v3_fundamentals_*/tengu_v3_intel_*'. It also warns about chart placement ('do NOT expect the daily here, it's only in chart') and vendor_errors, providing practical usage context.

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

All tengu-firm toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

C2.9/5.0
Disambiguation2/5

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.

Naming Consistency2/5

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.

Tool Count1/5

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.

Completeness4/5

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.

Resources