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LiveDataLink

by io.github.blackboxfoundry

edgar_recent_filings

Read-onlyIdempotent

List recent SEC filings for a company. Filter by form type (10-K, 10-Q, 8-K, 4, DEF 14A, etc.) and start date. Use ticker or CIK as identifier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum rows to return (default 25, max 100).
form_typeNoOptional form type filter (e.g. '10-K', '10-Q', '8-K', '4').
identifierYesTicker symbol or CIK. Examples: 'AAPL', '0000320193'.
start_dateNoOptional ISO date lower bound (YYYY-MM-DD).

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety and idempotency. The description adds that results are recent company-specific filings and filterable, but discloses no additional behavioral details such as pagination, time-window semantics, 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?

Three short sentences, no filler, with the most important information (what it returns) first and filters/identification details stated efficiently.

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?

For a read-only listing tool with annotations covering safety and four fully documented parameters, the description is nearly sufficient. The only minor gap is that 'recent' is not defined precisely (no default lookback window), though this is unlikely to block correct invocation.

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 100%, with all four parameters already described including examples for identifier and defaults for limit. The description's mention of form-type filtering and ticker/CIK identification merely restates schema information, adding no new meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('List') and a specific resource ('recent SEC filings for a company') with examples of filter options, making its core function clear. It does not explicitly contrast itself with the overlapping sibling edgar_filings_by_form_type, so it cannot receive full marks for differentiation.

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?

The description implies the tool is for fetching recent SEC filings for a specific company and states the identifier requirement and available filters, giving a clear context for when it applies. It never explicitly names an alternative tool or a when-not-to-use condition, so the guidance is implied rather than explicit.

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

B3.2/5.0
Disambiguation2/5

Many tools overlap heavily across domains: caselaw_search vs court_case_search vs court_opinion_search, caselaw_citation_lookup vs court_citation_resolver, and a cluster of company due-diligence tools (company_trust_check, counterparty_risk_score, entity_dossier, issuer_diligence_dossier, kyb_aml_evidence_case_file) that all screen a company for sanctions/risk/standing. With 290 tools, an agent will frequently face multiple equally plausible choices for the same user intent.

Naming Consistency3/5

The vast majority of tools follow a clean domain-prefix + snake_case pattern (census_, eia_, fmcsa_, npi_, cfpb_, etc.), but there are notable exceptions: entity_resolve and resolve_entity are reversed duplicates, reg_search (Federal Register) sits next to reg_cfr_search (CFR) with confusingly similar names, and carrier_monitor_recheck deviates from the carrier_vetting_* family.

Tool Count1/5

290 tools is an extreme count under any rubric, far exceeding even the 50+ threshold for the lowest score. While the group-filtering mechanism and meta-tools like list_tool_groups and search_available_datasets mitigate the practical burden, the raw surface is still massively oversized for an agent to select from accurately and efficiently.

Completeness4/5

For a read-only data-aggregation server, coverage is remarkably comprehensive across 59 domains, and generic fallbacks like cdc_dataset_query, eia_series_lookup, fred_observations, and bls_series prevent most dead ends. Minor gaps exist (a single GitHub tool, demo-only property_lookup coverage, no write/update operations anywhere), but the stated data-access purpose is well served.

Resources