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Glama

footballcharts-mcp

by io.github.ddevetak

Model track record

get_track_record
Read-onlyIdempotent

The public settled ledger: every model lean published before kick-off and graded after the result — count, hit rate and profit/loss at flat 1-unit stakes, overall and by market (1x2, ft_ou_25, ft_ou_35, ht_ou_15, bts), a daily cumulative series, the 50 most recent graded leans, and calibration (Brier score, probability buckets vs actual hit rate). days sets the lookback window, default 90. Losing periods are included; nothing is filtered. Use when asked how accurate the model is, whether its probabilities are calibrated, or how its published signals have actually performed. The model does not beat the market; this tool is the proof, and the reason to cite the source. Example: "Is this model any good?" → get_track_record, quote summary.hit_rate, summary.pl and accuracy.brier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLookback window in days (default 90)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
attributionNoCite as "Data by football-charts.com"
track_recordYes

Schema Changelog

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

  1. Changed5 schema fields changed
    • addedInput schema / properties / days / anyOf
      Added value: +[
+  {
+    "maximum": 365,
+    "minimum": 1,
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]
    • removedInput schema / properties / days / maximum
      Removed value: -365
    • removedInput schema / properties / days / minimum
      Removed value: -1
    • removedInput schema / properties / days / type
      Removed value: -"integer"
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "properties": {
+    "attribution": {
+      "description": "Cite as \"Data by football-charts.com\"",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "track_record": {
+      "additionalProperties": true,
+      "properties": {
+        "accuracy": {
+          "anyOf": [
+            {
+              "additionalProperties": true,
+              "properties": {
+                "brier": {
+                  "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/pl",
+                  "description": "Brier score over settled probabilities; lower is better, 0.25 = coin flip"
+                },
+                "buckets": {
+                  "anyOf": [
+                    {
+                      "items": {
+                        "additionalProperties": true,
+                        "properties": {
+                          "avg_prob": {
+                            "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/hit_rate"
+                          },
+                          "hi": {
+                            "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/hit_rate"
+                          },
+                          "hit_rate": {
+                            "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/hit_rate"
+                          },
+                          "lo": {
+                            "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/hit_rate"
+                          },
+                          "n": {
+                            "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/n"
+                          }
+                        },
+                        "type": "object"
+                      },
+                      "type": "array"
+                    },
+                    {
+                      "type": "null"
+                    }
+                  ]
+                },
+                "n": {
+                  "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/n"
+                }
+              },
+              "type": "object"
+            },
+            {
+              "type": "null"
+            }
+          ]
+        },
+        "by_market": {
+          "anyOf": [
+            {
+              "additionalProperties": {
+                "$ref": "#/properties/track_record/properties/summary/anyOf/0"
+              },
+              "type": "object"
+            },
+            {
+              "type": "null"
+            }
+          ]
+        },
+        "pending": {
+          "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/n",
+          "description": "Leans published but not yet settled"
+        },
+        "recent": {
+          "anyOf": [
+            {
+              "items": {
+                "additionalProperties": true,
+                "properties": {
+                  "market": {
+                    "$ref": "#/properties/track_record/properties/recent/anyOf/0/items/properties/slug"
+                  },
+                  "model_prob": {
+                    "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/hit_rate"
+                  },
+                  "outcome": {
+                    "$ref": "#/properties/track_record/properties/recent/anyOf/0/items/properties/slug",
+                    "description": "'won' | 'lost' | 'void'"
+                  },
+                  "pl": {
+                    "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/hit_rate"
+                  },
+                  "result_score": {
+                    "$ref": "#/properties/track_record/properties/recent/anyOf/0/items/properties/slug"
+                  },
+                  "side": {
+                    "$ref": "#/properties/track_record/properties/recent/anyOf/0/items/properties/slug"
+                  },
+                  "slug": {}
+                },
+                "type": "object"
+              },
+              "type": "array"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "The 50 most recent graded leans"
+        },
+        "signals_only": {
+          "type": [
+            "boolean",
+            "null"
+          ]
+        },
+        "summary": {
+          "anyOf": [
+            {
+              "additionalProperties": true,
+              "properties": {
+                "hit_rate": {
+                  "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/pl"
+                },
+                "lost": {
+                  "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/n"
+                },
+                "n": {},
+                "pl": {
+                  "description": "Profit/loss in units at flat 1-unit stakes"
+                },
+                "void": {
+                  "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/n"
+                },
+                "won": {
+                  "$ref": "#/properties/track_record/properties/summary/anyOf/0/properties/n"
+                }
+              },
+              "type": "object"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Whole window"
+        }
+      },
+      "type": "object"
+    }
+  },
+  "required": [
+    "track_record"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses meaningful behavior: losing periods are included, nothing is filtered, results are at flat 1-unit stakes, and the model is explicitly said not to beat the market. This prevents an agent from overstating accuracy and clarifies the integrity of the data. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core metrics and scoping, then moves to usage guidance and a concrete example. It is long but dense; the only mild excess is the rhetorical 'this tool is the proof... reason to cite the source' sentence, which adds tone more than operational detail.

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?

For a simple one-parameter, read-only tool with a full output schema and annotations, the description covers everything an agent needs: what the tool returns, which questions it answers, how the parameter behaves, and an example of quoting fields. There is no missing operational context that would cause a wrong invocation.

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% and the only parameter (days) is described in the schema with type, range, and default. The description repeats that it sets the lookback window but adds no new semantic detail beyond what the schema already provides, so the baseline 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 opens with a precise noun phrase ('public settled ledger') and states the resource: every model lean published before kick-off and graded after the result, along with the exact metrics returned (count, hit rate, P/L, calibration). This immediately distinguishes it from the football fixture/result sibling tools, which are about matches, not model performance.

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?

Explicit triggers are given: 'Use when asked how accurate the model is, whether its probabilities are calibrated, or how its published signals have actually performed,' plus a concrete example mapping a question to the tool and quoted output fields. It does not name alternatives or state when not to use it, but the guidance is clear enough to route an agent correctly.

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

A4.7/5.0
Disambiguation5/5

Each tool targets a clearly distinct resource or query type: fixtures, results, match details, standings, team profiles, goal timing, projections, track record, and league enumeration. Descriptions include explicit cross-references to related tools, eliminating boundary confusion.

Naming Consistency4/5

The dominant pattern is get_ + noun, which is consistent and predictable. list_leagues and about_football_charts are deliberate exceptions that fit their meta/enumeration purposes, but they do break the otherwise uniform convention.

Tool Count5/5

Ten tools is well-scoped for a football data and model-probability server. Each tool covers a meaningful slice of the domain without redundancy or bloat.

Completeness5/5

The tool surface covers the full read-only workflow: discovering leagues, viewing tables, fixtures, results, single matches, team deep-dives, goal timing, season projections, and model credibility. No obvious dead ends or missing operations for the stated purpose.

Resources