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tengu-firm

by io.github.Hlobo-dev

tengu_v3_funds_mutual_fund_ownership

Which mutual funds hold a stock — each fund's percent_tna, shares and market value, largest first, plus report_dt and n_funds, from the survivor-bias-free holdings archive (coverage 2002-2021; no date = latest lagged quarter-end). Call it for mutual-fund demand base or holder concentration; for 13F institutional holders use /intel/sec13f.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNo
dateNo
tickerYesPath parameter 'ticker' (required).
min_market_valNo

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses the data source (survivor-bias-free archive), coverage window (2002-2021), and default date behavior (no date = latest lagged quarter-end). This adds meaningful context beyond the schema, though it omits potential nuances like pagination or error behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single dense sentence followed by a short usage directive. Every clause adds value, with no filler or redundancy, and the key purpose is front-loaded.

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

Completeness4/5

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

Given no output schema and four parameters, the description covers the core purpose, output fields, data provenance, and default date behavior. It falls slightly short of full completeness by not explaining all parameters, but the tool's behavior is reasonably inferable.

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?

Schema coverage is low (25%, only ticker described). The description explains the 'date' parameter's default behavior and the output ordering, but it does not clarify the 'top' or 'min_market_val' parameters, leaving agents to infer their semantics from names and schema constraints.

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 identifies mutual fund holdings for a given stock, specifying output fields (percent_tna, shares, market value, report_dt, n_funds) and ordering (largest first). It distinguishes from the 13F tool, making the purpose unambiguous.

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?

Explicitly says to use for 'mutual-fund demand base or holder concentration' and directs the agent to '/intel/sec13f' for 13F institutional holders, providing clear when-to-use and alternative guidance.

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

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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.

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