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Glama

Server Details

Free, no-auth AI industry briefings and a US/UK/EU AI regulation tracker for agents.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

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Tool DescriptionsA

Average 3.9/5 across 3 of 3 tools scored.

Server CoherenceA
Disambiguation5/5

Each tool has a clearly distinct purpose: daily briefing provides a summary, regulation updates focus on legislation, and search_news is for searching. No ambiguity.

Naming Consistency4/5

Tools mostly use snake_case with verb_noun pattern, but 'get_daily_briefing' and 'get_regulation_updates' use 'get' while 'search_news' uses 'search', a minor inconsistency.

Tool Count4/5

With 3 tools, the server is focused but not too thin for its purpose of providing AI news and regulation updates. It could benefit from additional tools like trend analysis, but the count is appropriate.

Completeness3/5

The tool set covers basic needs (daily summary, regulation updates, search), but the search is limited to teasers and full features require subscription. Lacks tools like topic filtering or historical data retrieval, leaving some gaps.

Available Tools

3 tools
get_daily_briefingAInspect

Today's aggregate AI industry briefing: top stories, emerging signals, new entrants, and regulation updates, distilled from HN/Reddit and official legislative sources. Optionally pass a date (YYYY-MM-DD, last 7 days).

ParametersJSON Schema
NameRequiredDescriptionDefault
dateNoOptional YYYY-MM-DD within the last 7 days; omit for the latest briefing.
Behavior3/5

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

The description discloses data sources (HN/Reddit, legislative) and date range (last 7 days), but does not mention any behavioral traits such as read-only nature, authentication, or rate limits. No annotations are present to require contradiction.

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 sentences with no wasted words. The purpose is front-loaded, and every sentence serves a clear function.

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 simple briefing tool with one optional parameter and no output schema, the description adequately explains what the briefing covers and the date constraint. It lacks details on return format, but is sufficiently complete.

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?

The description restates the schema's date parameter: 'Optionally pass a date (YYYY-MM-DD, last 7 days)'. With 100% schema coverage, this adds no new meaning, meeting the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it provides an aggregate AI industry briefing covering stories, signals, entrants, and regulation from specific sources. It distinguishes from siblings implicitly (AI industry briefing vs. regulation-only or general news), but lacks explicit differentiation.

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

Usage Guidelines3/5

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

The description implies usage for daily briefing retrieval with an optional date, but does not provide explicit guidance on when to use this tool versus siblings like get_regulation_updates or search_news.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_regulation_updatesAInspect

Current AI legislation headlines across the US Congress, UK Parliament, and EU, with their legislative stage (proposed / committee / floor action / passed / implementation).

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNoMax headlines (default 50, cap 100).
jurisdictionNoOptional filter to one jurisdiction.
Behavior3/5

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

No annotations provided, so description must fully disclose behavior. It states the output (headlines with stage) but omits details on data freshness, pagination, rate limits, or read-only nature.

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?

Single sentence that is compact, front-loaded with core functionality, and contains no redundant information.

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?

Given the simplicity (2 optional params, no output schema), the description explains purpose and data returned adequately. Lacks details on output format but sufficient for basic understanding.

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?

Input schema has 100% coverage with clear descriptions for limit and jurisdiction. The tool description adds no extra meaning 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?

Description clearly specifies the resource (AI legislation headlines), jurisdictions (US Congress, UK, EU), and the legislative stage information. It distinguishes from siblings like get_daily_briefing (broader) and search_news (generic).

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. Does not provide context for prerequisites, limitations, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_newsAInspect

Quick teaser search over recent AI news: returns the top 3 matching titles with links. Full-text search with bodies, filters, and history requires a Horizon subscription.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesSearch terms.
Behavior4/5

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

No annotations provided, so description carries full burden. Discloses that search is over 'recent AI news', returns top 3 titles with links, and that full-text search requires subscription. Does not mention rate limits or authentication needs, but covers key behavioral traits.

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 sentences, no wasted words. First sentence immediately states purpose and key behavior (returns top 3). Front-loaded and efficient.

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 simple tool with one parameter and no output schema, the description adequately covers return format, limitation to 3 results, and subscription requirement. Lacks specifics on time range for 'recent' and result ordering, but overall sufficient.

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 coverage is 100% with one 'query' parameter described as 'Search terms.' Description adds domain context ('recent AI news') to the parameter meaning, clarifying the scope 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?

Description clearly states 'Quick teaser search over recent AI news' with a specific verb (search) and resource (AI news). Distinguishes from sibling tools (get_daily_briefing, get_regulation_updates) by focusing on search rather than retrieval of specific items.

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?

Description indicates use for quick teaser searches returning top 3 titles with links, and contrasts with full-text search requiring a Horizon subscription. Provides context but does not explicitly state when not to use or specify alternative tools for different needs.

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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