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Court-reported negative history for one case

treatment
Read-onlyIdempotent

Later courts, in their own words, reporting that one case was overruled, abrogated, superseded, reversed or vacated. Takes a cluster id (the case-record id), not an opinion id. Every row carries the citing court’s own sentence, cut from its stored text; the label is a filter over those sentences, not a verdict, and 68.7% of findings are expressly partial ("overruled on other grounds"). Not a validity verdict and not Shepardizing: an automated, unverified reading with no positive signal, so zero rows is not evidence that a case remains good law. Rows include known false positives; a read guard (version 2) withholds ten known false shapes and counts them in declined_by_read_guard with read_guard_note. Precision, hand-read after version 2: 0.9862 (95% interval 0.9511-0.9962, 145 of 150 kept rows); 1.0000 (0.9124-1.0000, 40 of 40) for cases cited 10,000+ times. Recall for this collection is unknown; the only figure, 0.6477 (0.5780-0.7116, n=193), is an upper bound on the Supreme Court stratum. The overruling opinion itself is usually not among the rows (Roe carries no row from Dobbs). Five labels only; "followed" and "distinguished" are not loaded. Counts are for this record alone; also_carried_by names sibling records. unrelayable_in_window counts rows dropped because no sentence could be cut; capped=true marks a slice; order is citing-opinion date. Case law in this mirror ends 2026-09-30 (exact scan of all 10,174,547 case records): a thin or empty result for recent authority means the collection ends there, not that no such case exists. Every response carries a "note" and a coverage_note. The sources tool returns this tool’s full coverage statement.

Input Schema

NameRequiredDescriptionDefault
labelNofilter rows to one label. A filter over sentences, never a verdict; by_label on the response reports all five regardless
limitNomax rows returned, 1-25 (default 10)
offsetNoskip this many, for paging further down the date order; capped at 5000
cluster_idYesthe CASE RECORD (cluster) id of the case you are checking — from a search/citation/fts result (id or cluster_id), not an opinion id

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already cover read-only/idempotent safety, and the description adds substantial behavior beyond them: known false positives, a read guard (version 2) that withholds ten false shapes and reports them in declined_by_read_guard/read_guard_note, hand-read precision with confidence intervals, unknown recall, and the fact that only five labels are loaded. It also discloses that the overruling opinion itself is usually absent (Roe has no Dobbs row), which is exactly the kind of non-obvious behavior an agent needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the essential definition and the id caveat, but the block is extremely dense and carries precision/recall confidence intervals and stratum-specific figures that matter more for trust calibration than for invoking the tool. Several clauses (sample sizes, intervals) could be moved to the referenced coverage statement without losing invocation-critical information.

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?

There is no output schema, yet the description documents the return shape in detail: every row carries the citing court's sentence, by_label reports all five labels regardless of filter, also_carried_by, unrelayable_in_window, capped, plus the mandatory 'note' and coverage_note, and ordering by citing-opinion date. Given the tool's complexity and high false-positive risk, nothing an agent needs to interpret results 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 coverage is 100%, so the schema already documents all four parameters, including the label enum note 'A filter over sentences, never a verdict'. The description reinforces the label-as-filter framing and the cluster-id-not-opinion-id distinction, but largely restates schema content rather than adding new parameter syntax or semantics; baseline 3 applies.

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?

Opens with a specific verb+resource (later courts reporting a case was overruled/abrogated/etc.) and immediately disambiguates the identifier: 'Takes a cluster id (the case-record id), not an opinion id.' It also distinguishes itself from the sibling concept citation/Shepardizing, so an agent can place it against citation, citations and brief_check without opening a schema.

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?

Explicit exclusions are given ('Not a validity verdict and not Shepardizing', 'zero rows is not evidence that a case remains good law', and the caveat that ~68.7% of findings are expressly partial), plus a temporal boundary explaining thin recent results. It stops short of naming a specific sibling to use instead when you want a positive/validity signal — it only delegates that to 'sources' for coverage.

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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