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Glama

Ai Briefing

by io.github.pipeworx-io

Get Ai News

get_ai_news
Read-onlyIdempotent

Get AI industry news — model releases, funding, acquisitions, policy changes, benchmarks. Returns news events with dates and summaries for industry context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLook back N days (default 7)
limitNoMax results (default 15)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
feedYesFeed name
itemsYesAI industry news items
totalYesNumber of news items found
periodYesTime period description
descriptionYesFeed description

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "description": {
+      "description": "Feed description",
+      "type": "string"
+    },
+    "feed": {
+      "description": "Feed name",
+      "enum": [
+        "ai_news"
+      ],
+      "type": "string"
+    },
+    "items": {
+      "description": "AI industry news items",
+      "items": {
+        "properties": {
+          "category": {
+            "description": "News category",
+            "type": "string"
+          },
+          "importance": {
+            "description": "Importance level",
+            "type": "string"
+          },
+          "published_at": {
+            "description": "Publication timestamp",
+            "type": "string"
+          },
+          "source": {
+            "description": "Source identifier",
+            "type": "string"
+          },
+          "summary": {
+            "description": "News summary",
+            "type": "string"
+          },
+          "title": {
+            "description": "News title",
+            "type": "string"
+          },
+          "url": {
+            "description": "Source URL",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "period": {
+      "description": "Time period description",
+      "type": "string"
+    },
+    "total": {
+      "description": "Number of news items found",
+      "type": "number"
+    }
+  },
+  "required": [
+    "feed",
+    "period",
+    "description",
+    "total",
+    "items"
+  ],
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "days": 7
+  },
+  {
+    "days": 30,
+    "limit": 20
+  }
+]
  3. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering safety and behavior. The description adds that the tool returns events with dates and summaries, which is consistent but does not elaborate on rate limits, authentication needs, or data freshness. With high annotation coverage, this is adequate but not exceptional.

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 extremely concise: one sentence defining the purpose and one sentence on return format. Every part is necessary and front-loaded. No filler or redundancy.

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 read-only tool with two optional parameters and an output schema, the description covers the core function and output. It could mention default parameter values (though schema examples do), but overall it provides sufficient context for an agent to invoke the tool correctly.

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%, with both 'days' and 'limit' already documented. The tool description does not add any additional meaning about these parameters, so it neither improves nor degrades the semantic clarity. Baseline score of 3 is appropriate.

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 clearly states the tool retrieves AI industry news and lists specific content types (model releases, funding, etc.). It uses a specific verb and resource combination, making the purpose unambiguous. While it does not explicitly distinguish from siblings like get_recent, the scope is well-defined enough for an agent.

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 broad AI news but provides no explicit guidance on when to use this tool versus alternatives (e.g., get_recent or entity_profile). No when-not conditions or references to sibling tools are given, leaving the agent to infer the appropriate context.

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

All Ai Briefing toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as multiple tools for querying Pipeworx data (ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim) and numerous tools for AI news/tools (get_ai_news, get_ai_toolbelt, get_briefing, get_model_landscape, etc.). This will cause an agent to frequently misselect the appropriate tool.

Naming Consistency4/5

Most tools follow a verb_noun pattern in snake_case (e.g., compare_entities, discover_tools, get_briefing). However, a few deviate like 'bet_research' (noun_verb) and 'what_happened' (phrase), but overall the pattern is largely consistent.

Tool Count2/5

38 tools is excessive for a server called 'Ai Briefing', which suggests a focused purpose. The tool count spans multiple domains (AI visibility, Pipeworx queries, Polymarket betting, memory, subscriptions) making it feel overstuffed and unfocused.

Completeness3/5

The tool set covers many aspects of its broad domain (querying, comparing, subscribing, memory), but there are notable gaps: no tool for modifying subscriptions, no user profile management, and the AI news tools overlap rather than cover distinct needs.

Resources