standingsFetch the AFL ladder (standings) for a given year and optional round from Squiggle; returns wins, losses, points, and percentage for each team.
| Name | Required | Description | Default |
|---|---|---|---|
| year | No | ||
| round | No |
| Name | Required | Description | Default |
|---|---|---|---|
| standings | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / properties / countRemoved value: -{
- "description": "Number of items returned.",
- "type": "integer"
-}Output schema / properties / itemsRemoved value: -{
- "items": {
- "properties": {
- "losses": {
- "description": "Number of losses",
- "type": "number"
- },
- "points": {
- "description": "Competition points",
- "type": "number"
- },
- "position": {
- "description": "Ladder position",
- "type": "number"
- },
- "team": {
- "description": "Team name",
- "type": "string"
- },
- "wins": {
- "description": "Number of wins",
- "type": "number"
- }
- },
- "type": "object"
- },
- "type": "array"
-}Output schema / properties / standingsAdded value: +{
+ "items": {
+ "properties": {
+ "against": {
+ "type": "number"
+ },
+ "behinds_against": {
+ "type": "number"
+ },
+ "behinds_for": {
+ "type": "number"
+ },
+ "draws": {
+ "type": "number"
+ },
+ "for": {
+ "type": "number"
+ },
+ "goals_against": {
+ "type": "number"
+ },
+ "goals_for": {
+ "type": "number"
+ },
+ "id": {
+ "type": "number"
+ },
+ "losses": {
+ "type": "number"
+ },
+ "name": {
+ "type": "string"
+ },
+ "percentage": {
+ "type": "number"
+ },
+ "played": {
+ "type": "number"
+ },
+ "pts": {
+ "type": "number"
+ },
+ "rank": {
+ "type": "number"
+ },
+ "wins": {
+ "type": "number"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+}Output schema / requiredRemoved value: -[
- "items",
- "count"
-]Input schema / examplesAdded value: +[
+ {
+ "round": 10,
+ "year": 2024
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "count": {
+ "description": "Number of items returned.",
+ "type": "integer"
+ },
+ "items": {
+ "items": {
+ "properties": {
+ "losses": {
+ "description": "Number of losses",
+ "type": "number"
+ },
+ "points": {
+ "description": "Competition points",
+ "type": "number"
+ },
+ "position": {
+ "description": "Ladder position",
+ "type": "number"
+ },
+ "team": {
+ "description": "Team name",
+ "type": "string"
+ },
+ "wins": {
+ "description": "Number of wins",
+ "type": "number"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "items",
+ "count"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already convey read-only, idempotent, and non-destructive behavior. The description adds that the data comes from Squiggle and returns specific fields, but does not disclose edge-case behavior such as handling of missing data or default round when omitted. No contradiction with 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 a single, well-structured sentence that front-loads the main verb and resource, then efficiently adds parameter and output details. There is no redundant or unnecessary wording.
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?
For a simple read-only tool with rich annotations and an output schema, the description covers the core purpose and data source. The major gap is not addressing the overlapping sibling 'ladder' tool, which is essential for correct tool selection. Also, it doesn't mention default behavior for optional round.
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 input schema has no descriptions (0% coverage), so the description is the only source of parameter meaning. It explicitly states 'year' and 'optional round', clarifying that round is optional. However, it does not provide constraints or what happens when round is omitted, leaving gaps.
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 'Fetch the AFL ladder' with parameters 'year' and 'optional round', and lists return fields. This is specific and identifies the resource. However, it does not differentiate from the sibling tool 'ladder', which appears to cover similar functionality.
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 no guidance on when to use this tool versus alternatives. No alternatives are mentioned, and with a sibling named 'ladder' that likely overlaps, the agent has no criteria for selecting this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct roles, especially across the Pipeworx research, Polymarket, and subscription lifecycle groups. The main friction is ask_pipeworx_beta currently behaving identically to ask_pipeworx, and the bare Squiggle/AFL tools (games, ladder, tips, standings) could be confused without domain knowledge.
The set is overwhelmingly lower_snake_case with recognizable prefixes like ask_pipeworx, polymarket_, pipeworx_, and scan_. The Squiggle/AFL tools break the verb-led pattern with bare nouns (games, ladder, sources, standings, teams, tips), but the overall naming is still predictable and readable.
37 tools is well past the 25+ over-broad threshold, and several are near-duplicates or tightly coupled variants (three ask_pipeworx tools, five polymarket_* tools, two AI-visibility probes). The breadth of the Pipeworx platform partly justifies the count, but as an MCP surface it is heavy and hard to navigate efficiently.
The set covers the core workflows well: lookup, grounded answering, deep research, entity resolution, comparison, change feeds, claim validation, subscriptions, and memory. Minor gaps exist—no explicit update path for subscriptions, and the Squiggle/AFL side is thin relative to the Pipeworx platform—but there are no critical dead ends.