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LiveDataLink

by io.github.blackboxfoundry

caselaw_opinion_text

Read-onlyIdempotent

Fetch the full opinion text of a case on demand by its CAP id. Text is retrieved live from the public-domain CAP static mirror (not stored), and includes each opinion (majority, dissent, concurrence) with its author. Use max_chars to bound the response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesCAP case id (from caselaw_search / caselaw_citation_lookup).
max_charsNoMaximum total characters of opinion text (default 50000, max 500000).

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the bar is lower. The description adds meaningful behavior beyond annotations: text is retrieved live from the public-domain CAP static mirror, is not stored, and includes each opinion with its author. No contradiction with 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?

Three concise sentences with zero filler. The core purpose is front-loaded, followed by useful behavioral context and a practical parameter hint. Every sentence earns its place.

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 non-destructive, idempotent fetch tool, the description plus schema cover the required input, the live source, the bounded-response control, and the content of the returned text. There is no output schema, but 'includes each opinion with its author' gives sufficient expectation of the result. Minor omissions like error behavior or exact response format are acceptable given the simplicity.

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 both id and max_chars with default/max bounds and id provenance. The description restates 'CAP id' and 'max_chars to bound the response,' which is consistent but adds little new semantic value 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 states a specific verb ('Fetch'), a precise resource ('full opinion text of a case'), and an identifier ('CAP id'). It also clarifies that the result includes majority, dissent, and concurrence opinions with authors, making it easy to distinguish from caselaw_search or caselaw_case_details.

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 usage scenario is clear: you need a CAP id (obtained via caselaw_search / caselaw_citation_lookup in the schema) and want the raw opinion text. The description adds 'on demand' and directs use of max_chars to bound the response. It does not explicitly name sibling alternatives or exclusion criteria, so it stops 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

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.

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