Source-linked research on U.S. judges, courts, cases, and judicial analytics.
Find court decisions involving AI-generated legal errors. Returns at most 10 source-linked cases with court, judges, response, summary, and a verified official decision URL when available. Empty and bulk searches are unavailable.
| Name | Required | Description | Default |
|---|---|---|---|
| court | No | Court name fragment | |
| judge | No | Judge name fragment | |
| limit | No | Maximum results, capped at 10 | |
| query | No | Case name, error type, ruling text, court, state, or judge search text | |
| state | No | US state name | |
| to_date | No | Inclusive latest decision date | |
| response | No | Court response, for example Warning or Sanctions | |
| from_date | No | Inclusive earliest decision date |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the maximum return count (10) and the fields included, but does not mention whether the tool is read-only, authentication requirements, rate limits, or error handling. For a search tool, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two sentences covering purpose, return fields, and constraints. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 optional parameters and no output schema, the description covers the core purpose and constraints but does not explain parameter interaction (e.g., AND/OR logic), sorting, or behavior when no results are found. It is functional but leaves gaps for complex queries.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-specific meaning beyond what the schema already provides; it only outlines return fields. No additional semantic value is offered.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds court decisions involving AI-generated legal errors, which is a specific verb and resource. It distinguishes from sibling tools that focus on judges, courtroom rules, and profiles, making its purpose unique.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states that empty and bulk searches are unavailable, providing clear constraints on usage. While it does not explicitly name alternative tools, the context and sibling list imply this tool is for AI-error cases, which is sufficient guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Find likely US judges by name, court, state, county, or jurisdiction. Use this before requesting a profile when the exact KnowJudges slug is unknown. Results are public, bounded, and link to canonical KnowJudges profiles.
| Name | Required | Description | Default |
|---|---|---|---|
| court | No | Court name fragment | |
| limit | No | Maximum results, capped at 10 | |
| query | Yes | Judge name or other identifying search text | |
| state | No | US state name or postal abbreviation, for example DC or California | |
| county | No | County name fragment |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that results are 'public, bounded, and link to canonical KnowJudges profiles,' implying safety and boundedness. It does not explicitly state read-only or idempotency, but the context of a search tool suggests it. The description adds value beyond the schema without contradicting any annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose. The first sentence states the action and criteria. The second sentence adds usage guidance and result traits. Every sentence is essential and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters (1 required), no output schema, and no annotations, the description adequately covers the purpose, usage context, and result characteristics. It could be improved by briefly describing the return format (e.g., 'returns a list of judge names, courts, and slugs'), but it is still sufficient for an agent to understand the tool's role.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add meaning beyond the parameter descriptions in the schema. It mentions searching by name, court, state, county, or jurisdiction, which maps to the parameters, but the schema already describes each parameter clearly (e.g., 'Court name fragment', 'Judge name or other identifying search text'). No additional semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Find' and resource 'US judges', lists search criteria (name, court, state, county, or jurisdiction), and explicitly distinguishes from siblings by noting 'Use this before requesting a profile when the exact KnowJudges slug is unknown.' This directly differentiates it from get_judge_profile.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool: 'Use this before requesting a profile when the exact KnowJudges slug is unknown.' It also provides context that results are public, bounded, and link to profiles, which helps the agent decide when to invoke this vs. a profile retrieval tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get source-linked courtroom technology and presentation rules for a judge. Optional topics can focus on PowerPoint, video, demonstratives, advance exchange, exhibits, or courtroom technology.
| Name | Required | Description | Default |
|---|---|---|---|
| topics | No | Optional presentation topics to filter | |
| judge_slug | Yes | Canonical slug returned by find_judges |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It discloses that the tool returns 'source-linked' rules and can be filtered by topics, but it does not state whether the operation is read-only, destructive, requires authentication, or has rate limits. The description is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that states the core purpose first, then adds an optional filtering note. Every word earns its place; no extraneous details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the input schema is fully covered and there is no output schema, the description should explain return format or structure. It mentions 'source-linked' but does not describe what the output contains (e.g., a list of rules, formatted text, structured data). Without output schema, this is a gap. Overall, the description is adequate for a simple retrieval tool but lacks completeness on return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning the schema already describes both parameters well. The description adds value by explaining the optional 'topics' parameter with concrete examples (PowerPoint, video, demonstratives), which clarifies permissible filter values beyond the schema's generic 'Optional presentation topics to filter'. The 'judge_slug' parameter is tied to the sibling tool find_judges, hinted by the description's mention of 'Canonical slug returned by find_judges' in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb 'Get' and the resource 'source-linked courtroom technology and presentation rules for a judge'. It also lists example topics, which distinguishes it from siblings like get_judge_biography or get_judge_profile. However, it does not explicitly differentiate from get_recent_rule_changes, which might overlap in scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (to get rules for a judge, optionally filtered by topics) but provides no guidance on when NOT to use it or explicit alternatives among siblings. For instance, it doesn't mention get_recent_rule_changes as an alternative for just checking recent updates.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return source-attributed public biographical facts for a judge, including birth details, computed age, education, professional and judicial careers, provenance, coverage gaps, and verification status. Demographic and political labels are excluded from this public tool.
| Name | Required | Description | Default |
|---|---|---|---|
| judge_slug | Yes | Canonical slug returned by find_judges |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is transparent about what is included (biographical facts with sources) and explicitly excludes demographic/political labels. With no annotations provided, it covers safety and scope adequately, but does not disclose potential pagination, rate limits, or data freshness beyond source attribution.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single focused sentence listing the tool's content and exclusions. It front-loads the main purpose and adds efficient detail without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool (one required parameter, no output schema, no nested objects), the description is fairly complete. It clarifies the tool's scope and exclusions. However, it does not describe the return value structure or format, which would be helpful for a factual biography tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (one parameter, described as canonical slug from find_judges). The description adds context that the slug is matched to a judge, but does not add meaning beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns source-attributed public biographical facts for a judge, and lists specific data categories (birth details, age, education, career, verification status). It distinguishes from siblings by stating it excludes demographic and political labels, and the sibling set includes get_judge_profile, which likely provides other judge info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining factual biography without demographics, and mentions a prerequisite (judge_slug from find_judges). However, it does not explicitly state when to use this versus get_judge_profile or how to decide between them, leaving room for confusion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return a public KYJ judge profile with scope-aware findings, official source links, evidence excerpts, and verification metadata. Do not present courtwide guidance as a judge's personal preference.
| Name | Required | Description | Default |
|---|---|---|---|
| judge_slug | Yes | Canonical slug returned by find_judges |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It clearly states the output includes 'scope-aware findings, official source links, evidence excerpts, and verification metadata', and includes a specific caveat: 'Do not present courtwide guidance as a judge's personal preference.' This is valuable behavioral guidance.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two sentences that pack significant value. The first sentence enumerates return contents; the second provides an important behavioral boundary. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has a single parameter with full schema coverage and no output schema, the description adequately covers return values and provides a specific behavioral caution. It is complete enough for an AI agent to understand what it returns and how to avoid misuse.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter (judge_slug) has 100% schema coverage with a description specifying it must be a 'Canonical slug returned by find_judges'. The tool description adds no additional semantics beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a 'public KYJ judge profile' with specific content types (scope-aware findings, source links, excerpts, verification metadata). It distinguishes itself from siblings like get_judge_biography by emphasizing the public and scope-aware nature of the profile.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates this is appropriate for retrieving a specific judge's profile via the required judge_slug. However, it lacks explicit guidance on when to prefer this over get_judge_biography or find_judges, and does not mention any prerequisites or fallbacks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return recorded KYJ profile or courtroom-rule changes since a date. Change tracking begins at the launch date, so an empty result does not prove that no earlier real-world rule changed.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| since | Yes | Inclusive date in YYYY-MM-DD format | |
| court_slug | No | Optional canonical court slug | |
| judge_slug | No | Optional canonical judge slug |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses a key behavioral trait: change tracking starts at launch date. This adds context beyond annotations (which are absent). However, it doesn't mention whether the tool supports pagination, how to handle large result sets, or what the return format looks like.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, one focused on purpose, the other on an important constraint. It is front-loaded and efficient, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description could explain what the result set contains (e.g., list of change objects with fields). The launch-date caveat is valuable, but the overall completeness is adequate rather than thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 75% with the `since` parameter described as 'Inclusive date in YYYY-MM-DD format'. The description adds no further parameter semantics beyond what the schema provides. Since coverage is high, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns recorded KYJ profile or courtroom-rule changes since a date. It distinguishes itself from siblings like get_judge_profile and get_courtroom_presentation_rules which retrieve static information, not recent changes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides the important caveat that change tracking starts at launch date, so empty results don't prove no earlier changes occurred. However, it does not explicitly state when to prefer this over other tools or mention alternatives for before-tracking-use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
find_ai_abuse_casesfind_judgesget_courtroom_presentation_rulesget_judge_biographyget_judge_profileget_recent_rule_changesClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
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Each tool has a clearly distinct purpose: finding judges, retrieving biography, profile, presentation rules, AI abuse cases, or recent changes. There is no overlap or ambiguity; descriptions further clarify boundaries.
All tools follow a consistent verb_noun pattern with snake_case (find_*, get_*). The naming is predictable and easy to interpret, aiding agent selection.
With 6 tools, the set is well-scoped for a judge and courtroom information server. Each tool addresses a distinct need without bloat or triviality.
Core workflows (finding judges, retrieving bio/profile, presentation rules, tracking changes) are covered. A potential minor gap is a tool for historical courtroom rules or direct case lookups, but the current set supports common use cases adequately.