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LiveDataLink

by io.github.blackboxfoundry

edgar_filing_content

Read-onlyIdempotent

Fetch the text content of a specific SEC filing. Returns the primary document (10-K, 10-Q, etc.) stripped of HTML, suitable for LLM consumption. Use edgar_recent_filings first to get the accession number.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cikYesFiler CIK (with or without leading zeros).
max_charsNoMaximum characters of text to return (default 20000, max 200000).
accession_numberYesAccession number (e.g. '0000320193-25-000006' or '000032019325000006').

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already mark the tool as readOnly, idempotent, and non-destructive. The description adds behavioral value by disclosing that the output is the primary document text, HTML-stripped, and formatted for LLM consumption. It does not overpromise or contradict annotations.

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?

Two compact sentences, with the core action first, followed by expected output and a direct usage prerequisite. No wasted words; every sentence earns its place.

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?

For a focused retrieval tool with well-documented parameters and read-only annotations, the description is sufficient. It identifies how to obtain the required accession_number, explains what content will be returned, and notes the HTML-stripped format. No critical operational detail is missing.

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 description coverage is 100%, so the schema already documents CIK, accession_number, and max_chars. The description adds useful workflow context by naming edgar_recent_filings as the source for accession_number, but it does not add significant semantic detail beyond 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 a specific action ('Fetch the text content of a specific SEC filing') and specifies the output ('primary document... stripped of HTML, suitable for LLM consumption'). It is readily distinguishable from sibling tools like edgar_recent_filings or edgar_full_text_search because it targets a single known filing's text.

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?

The description gives a concrete prerequisite and sequencing instruction: 'Use edgar_recent_filings first to get the accession number.' This is clear context for when to use the tool, though it does not explicitly mention when not to use it or contrast with alternatives other than the prerequisite.

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