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tengu-firm

by io.github.Hlobo-dev

tengu_v3_workforce_layoffs

WARN-Act LAYOFF FILINGS for one company — the public notices an employer must file WEEKS BEFORE a cut, so they lead the press release and the next earnings call. Returns each filing (notice date, effective date, employees affected, site city/state, layoff type) newest first, plus TRUE window totals, a month-by-month series and the largest single filing; with_workforce also sizes the total against estimated headcount and names the headcount month used. Call it as a downside early-warning, or to confirm the scale of an announced restructuring — filings are SITE-level, so one restructuring appears as many rows. Coverage is US WARN notices from 1989 forward including forward-dated notices; only employers matched to a listed symbol are reachable by ticker, so an empty result is not proof there were no layoffs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
monthsNo
tickerYesPath parameter 'ticker' (required).
employer_idNo
with_workforceNo

TDQS

A4.1/5.0
Behavior5/5

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

With no annotations, the description carries full burden and excels: it discloses site-level granularity (one restructuring appears as many rows), coverage specifics (US WARN notices from 1989 forward, forward-dated notices), the ticker-matching limitation, and the behavior of with_workforce (sizes total against estimated headcount, names headcount month). These are exactly the non-obvious behavioral traits an agent needs.

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 longer than the calibration's 'high' example, but every sentence earns its place: purpose, return contents, use cases, and caveats. It is front-loaded and logically structured. Slightly verbose in the middle, but not wasteful.

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 no annotations, the description covers return fields, use cases, coverage limitations, and parameter hints for with_workforce. It misses detailed semantics for limit and employer_id, which leaves it a step below fully complete, but for a single-company lookup it is substantially informative.

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

Parameters2/5

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

Schema coverage is only 20% (only ticker has a description). The description adds meaning for with_workforce ('also sizes the total against estimated headcount') and hints at months ('month-by-month series'), but leaves limit and employer_id entirely unexplained. Given the low schema coverage, the description fails to compensate for these parameters.

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 opens with a specific verb and resource: 'WARN-Act LAYOFF FILINGS for one company'. It clearly states what the tool returns (filings with notice date, effective date, employees affected, site city/state, layoff type) and distinguishes it from siblings like tengu_v3_workforce_layoff_screen by emphasizing 'for one company' and 'site-level' granularity.

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

Usage Guidelines4/5

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

Provides clear usage context: 'Call it as a downside early-warning, or to confirm the scale of an announced restructuring'. Also includes practical caveats (empty result not proof of no layoffs, site-level rows). However, it does not explicitly name alternatives or state when-not-to-use, so it falls just short of a 5.

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.

Resources