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HSH Data-on-Demand

by io.github.hshintelligence

hsh-esg-events

Authoritative company-attributed ESG material-event intel for US-listed companies. Sourced from SEC EDGAR 8-K + SD filings (companies disclosing their own material events): governance changes, restatements, auditor changes, bankruptcy/debt triggers, material impairments, litigation/other-material-events, conflict-minerals disclosures. Each event is mapped to ESG pillar (E/S/G), severity-graded (1-5), and links to the actual SEC filing. Optional ticker or pillar filter. Pay per call via x402 (USDC on Base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLookback window in days.
limitNoMax events to return.
pillarNoFilter by pillar: E, S, or G.
tickerNoFilter to one company e.g. AAPL, XOM.

TDQS

A4/5.0
Behavior4/5

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

No annotations provided, so description bears full burden. Discloses data source (SEC filings), event mapping, severity grading, and links. Mentions payment per call. Does not discuss rate limits or idempotency, but these are less critical for a read-only tool.

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?

Single paragraph with dense, relevant information. Every sentence adds value. Could be slightly more structured with bullet points, but no redundancy.

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?

No output schema but description explains return structure: events mapped to pillar, severity-graded, with links to SEC filings. Covers source, event types, filtering options. Complete for a data retrieval 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?

Schema covers all parameters (100% coverage) with clear descriptions. Tool description adds no additional detail for parameters beyond what schema provides. Baseline 3 is appropriate.

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?

Clearly states it provides authoritative company-attributed ESG material-event intel for US-listed companies from SEC filings. Specific verb ('provide'), resource ('ESG events'), and source (SEC EDGAR). Differentiates from siblings like hsh-esg-news by specifying the source and nature.

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

Usage Guidelines3/5

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

Describes filtering options (ticker, pillar) and payment model but does not explicitly state when to use this tool over alternatives like hsh-esg-news or other data tools. Lacks guidance on when not to use it.

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

B3.3/5.0
Disambiguation4/5

Most tools have distinct purposes, but some closely related tools (e.g., hsh-b2b-*, hsh-esg-* variants) could cause confusion. Descriptions help differentiate, but an agent might still misselect similar products.

Naming Consistency3/5

Naming convention is mixed: some tools use hyphens (hsh-b2b-contact), others use underscores (hsh_broker_data_request). While mostly readable, the inconsistency could be confusing for agents expecting a uniform pattern.

Tool Count3/5

32 tools is on the high side for a single server, but given its purpose as a data marketplace, the large number reflects a wide catalog. However, it may be overwhelming for agents to navigate.

Completeness3/5

Covers many data domains but has obvious gaps (e.g., weather, social media). The inclusion of custom data request tools (hsh_describe_data_need, hsh_broker_data_request) mitigates these gaps, allowing agents to request missing data.

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