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ca-rate-filings

by ai.serff

List Regulatory Caseload by Email

list_email_workload
Read-onlyIdempotent

Use this to size up a person's REGULATORY caseload — how many filings a reviewer, actuary, or contact appears on, split by filing status. NOT for content or rating questions about the filings themselves.

Wrong tool for reading filing content, answering "what does this filing do", or seeing the objection text itself. For those, chain from a caseload result: this tool gives you the emails and volumes; search_correspondence_embeds({email}) or get_filing_correspondence({serff}) returns the actual paperwork.

Right questions this answers directly:

  • "Which CDI reviewer has the heaviest live caseload?" → email_domain='insurance.ca.gov' + year=2026 — top rows show pending vs closed split

  • "How many filings has actuary jane@wps-inc.com been on this year, and how many are still Pending?" → email='jane@wps-inc.com', year=2026

  • "Top carrier-side filers across the whole corpus" → no filter, topK=50

  • "Which of Pan Wong's recent Farmers filings are still under CDI review" → email='pan.wong@farmersinsurance.com', then search_correspondence_embeds({email, filing_status:'Pending'}) for the specific filings

Cost: one indexed aggregate + one join against filings. No LLM.

Each row: {email, filings_total, filings_closed, filings_pending, filings_other, earliest_filing, latest_filing}. filings_closed matches serff_filing_status ILIKE 'Closed%' (Approved, Withdrawn, Disapproved, Acknowledged); filings_pending matches ILIKE 'Pending%'; filings_other catches everything else (Filed, Draft, N/A, etc.). Sorted by filings_total descending, top topK returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topKNoMax rows to return. Defaults to 20; capped at 200.
yearNoExact filing year. Mutually exclusive with year_from/year_to.
emailNoOptional exact email to scope the aggregate to a single address (case-insensitive).
year_toNoUpper bound on filing year, inclusive.
year_fromNoLower bound on filing year, inclusive.
email_domainNoOptional exact domain to scope the aggregate (e.g. "insurance.ca.gov"). Case-insensitive.

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, and the description adds valuable behavioral context: it is a single indexed aggregate with one join, no LLM, sorted by filings_total descending, and it precisely defines how filings_closed, filings_pending, and filings_other are computed from serff_filing_status. This goes well beyond the 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?

The description is long but tightly organized: purpose, exclusions, example questions, cost, and output semantics each earn their place. The most important scoping information is front-loaded, and the examples are concrete and directly actionable.

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?

With no output schema, the description fully explains the return row shape, status classification logic, sorting order, and topK behavior. It also covers cost and the absence of LLM processing, leaving no critical gap for an agent deciding whether and how to invoke this tool.

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

Parameters4/5

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 all six parameters. The description adds extra value by showing realistic parameter combinations (e.g., email_domain='insurance.ca.gov' + year=2026, email='jane@wps-inc.com', topK=50) and explaining what each row means, which helps an agent construct correct calls.

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 and resource: 'size up a person's REGULATORY caseload' with counts split by filing status. It explicitly distinguishes itself from content/rating tools and names sibling tools it is not, so an agent can select it correctly without opening schemas.

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

Usage Guidelines5/5

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

The description gives explicit when-to-use guidance with concrete example questions and parameter mappings. It also states when NOT to use it and names the correct alternatives (`search_correspondence_embeds`, `get_filing_correspondence`), including how to chain from caseload results to actual filings.

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

A4.5/5.0
Disambiguation4/5

The get_filing_* family has distinct purposes, though get_filing_lineage and get_filing_references could be confused without the detailed descriptions. The search_* tools are clearly separated by embedding surface, and dossier/composite vs single-filing retrievals are explicitly differentiated.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern with clear prefixes: get_filing_*, search_*, list_*, and mcp_*. No style mixing or vague generic verbs.

Tool Count4/5

At 16 tools, this sits at the upper edge of the ideal range. Each tool earns its place, though get_filing_dossier could have been a client-side composition of the other get_filing_* calls rather than a separate tool.

Completeness5/5

The domain (retrieving CA rate filings) is covered end to end: structured and semantic search across multiple granularities, filing summaries, correspondence threads, actuarial numerics, lineage, source file listing/download, and reviewer caseload. The read-only nature of the domain means no create/update operations are needed, and every retrieval path leads to a terminal artifact.

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