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Glama

Ai Briefing

by io.github.pipeworx-io

Get Model Landscape

get_model_landscape
Read-onlyIdempotent

List AI model releases from the last N days (default 30). Returns model names, provider companies, release dates, feature summaries, and source URLs grouped by importance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLook back N days (default 30)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelsYesModel release developments
periodYesTime period description
model_releasesYesNumber of model releases found

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": {
+    "model_releases": {
+      "description": "Number of model releases found",
+      "type": "number"
+    },
+    "models": {
+      "description": "Model release developments",
+      "items": {
+        "properties": {
+          "importance": {
+            "description": "Importance level",
+            "type": "string"
+          },
+          "published_at": {
+            "description": "Publication timestamp",
+            "type": "string"
+          },
+          "source": {
+            "description": "Source identifier",
+            "type": "string"
+          },
+          "summary": {
+            "description": "Model description and capabilities",
+            "type": "string"
+          },
+          "tags": {
+            "description": "Associated tags",
+            "type": "array"
+          },
+          "title": {
+            "description": "Model name or release title",
+            "type": "string"
+          },
+          "url": {
+            "description": "Source URL",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "period": {
+      "description": "Time period description",
+      "type": "string"
+    }
+  },
+  "required": [
+    "period",
+    "model_releases",
+    "models"
+  ],
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "days": 30
+  },
+  {
+    "days": 14
+  }
+]
  3. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, openWorld, idempotent, non-destructive. The description adds value by detailing the return structure (grouped by importance, fields returned). No contradictions. The description could mention pagination or limits, but given annotations, it is sufficient.

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 concise sentences: purpose first, then specifics. No wasted words. Front-loaded with action and scope.

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?

Given a simple tool with one optional parameter, comprehensive annotations, and an output schema (not shown but exists), the description fully covers the tool's functionality and return values. No gaps.

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% with one parameter ('days') well described. The description repeats the default but adds no further semantic detail. Baseline 3 applies as schema does the heavy lifting.

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 uses a specific verb ('List') and identifies a clear resource ('AI model releases from the last N days') with a default. It distinguishes from siblings like get_ai_news by specifying the focus on model releases and return fields.

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 recent model releases but does not explicitly state when to use versus alternatives (e.g., get_ai_news for general news) or provide exclusions. The context is clear but lacks comparative guidance.

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

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