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Glama

l0g.fr Risk Intelligence

by io.github.bluetouff

Get Freshness

get_freshness
Read-onlyIdempotent

Renvoie la fraîcheur du corpus l0g : derniers contenus, compteurs, endpoints disponibles et politique de fraîcheur. À appeler avant de présenter un snapshot comme actuel.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNombre de derniers contenus à renvoyer.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
corpusNo
latestNo
versionNo
endpointsNo
generatedNo
freshnessPolicyNo
signalFreshnessNo

Schema Changelog

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

  1. Added
  2. Removed
  3. Changed12 schema fields changed
    • addedOutput schema / properties / signalFreshness / items / properties / coverage / properties / lastAttemptAt
      Added value: +{
+  "type": "boolean"
+}
    • addedOutput schema / properties / signalFreshness / items / properties / coverage / properties / lastSuccessAt
      Added value: +{
+  "type": "boolean"
+}
    • changedOutput schema / properties / signalFreshness / items / properties / coverage / required
      Previous value: -[
-  "signalPresent",
-  "observedAt",
-  "sourcePublishedAt",
-  "retrievedAt",
-  "computedAt",
-  "staleAfter"
-]New value: +[
+  "signalPresent",
+  "observedAt",
+  "sourcePublishedAt",
+  "retrievedAt",
+  "lastAttemptAt",
+  "lastSuccessAt",
+  "computedAt",
+  "staleAfter"
+]
    • addedOutput schema / properties / signalFreshness / items / properties / fallbackReason
      Added value: +{
+  "type": [
+    "string",
+    "null"
+  ]
+}
    • addedOutput schema / properties / signalFreshness / items / properties / fallbackUsed
      Added value: +{
+  "type": "boolean"
+}
    • addedOutput schema / properties / signalFreshness / items / properties / lastAttemptAt
      Added value: +{
+  "anyOf": [
+    {
+      "format": "date-time",
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ]
+}
    • addedOutput schema / properties / signalFreshness / items / properties / lastSuccessAt
      Added value: +{
+  "anyOf": [
+    {
+      "format": "date-time",
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ]
+}
    • changedOutput schema / properties / signalFreshness / items / properties / missing / items / enum
      Previous value: -[
-  "signalPresent",
-  "observedAt",
-  "sourcePublishedAt",
-  "retrievedAt",
-  "computedAt",
-  "staleAfter"
-]New value: +[
+  "signalPresent",
+  "observedAt",
+  "sourcePublishedAt",
+  "retrievedAt",
+  "lastAttemptAt",
+  "lastSuccessAt",
+  "computedAt",
+  "staleAfter"
+]
    • addedOutput schema / properties / signalFreshness / items / properties / qualityStatus
      Added value: +{
+  "enum": [
+    "nominal",
+    "degraded",
+    "official-delayed",
+    "unknown",
+    "missing"
+  ],
+  "type": "string"
+}
    • addedOutput schema / properties / signalFreshness / items / properties / sourceStatus
      Added value: +{
+  "enum": [
+    "ok",
+    "fallback",
+    "missing"
+  ],
+  "type": "string"
+}
    • addedOutput schema / properties / signalFreshness / items / properties / warnings
      Added value: +{
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
    • changedOutput schema / properties / signalFreshness / items / required
      Previous value: -[
-  "key",
-  "label",
-  "source",
-  "methodology",
-  "observedAt",
-  "sourcePublishedAt",
-  "retrievedAt",
-  "computedAt",
-  "staleAfter",
-  "expiresAt",
-  "timelinessStatus",
-  "coverageStatus",
-  "coverage",
-  "missing",
-  "note"
-]New value: +[
+  "key",
+  "label",
+  "source",
+  "methodology",
+  "observedAt",
+  "sourcePublishedAt",
+  "retrievedAt",
+  "lastAttemptAt",
+  "lastSuccessAt",
+  "computedAt",
+  "staleAfter",
+  "expiresAt",
+  "timelinessStatus",
+  "sourceStatus",
+  "qualityStatus",
+  "fallbackUsed",
+  "fallbackReason",
+  "warnings",
+  "coverageStatus",
+  "coverage",
+  "missing",
+  "note"
+]
  4. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare the operation read-only, idempotent, and non-destructive. The description adds valuable behavioral context by explaining that the tool reports freshness state, including counters and policy, and frames it as a pre-check before asserting currency. No contradiction with annotations exists.

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 two sentences with no filler. The main purpose is front-loaded, and the usage note is compact and relevant. Every word earns its place.

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?

The tool is simple: one optional parameter and no required inputs. The description states what the tool returns, and an output schema exists to provide structured return details. Nothing necessary for calling the tool correctly is missing.

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 input schema fully documents the single optional limit parameter with default, minimum, and maximum, so schema coverage is 100%. The description does not mention limit, but the schema carries the full semantic burden and the description does not need to compensate.

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 ('Renvoie') and resource ('fraîcheur du corpus l0g'), then enumerates what the tool returns: latest contents, counters, available endpoints, and freshness policy. This clearly separates it from siblings like get_changes or get_changefeed, which focus on content changes rather than corpus freshness metadata.

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?

The description gives explicit guidance: call this tool before presenting a snapshot as current. This is a clear, actionable usage context. It does not enumerate when not to use the tool or name alternatives, but the stated use case is sufficient for most decision-making.

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

A3.9/5.0
Disambiguation4/5

Most tools target clearly distinct resources (articles, claims, sources, indices, signal history, integrity), and the descriptions are detailed. The two real ambiguities are get_changefeed vs get_changes, which are near-identical except for filtering, and the Agent Surface metadata cluster (manifest, openapi, integrity, verify, ndjson feed) where an agent could misselect. These are minor enough not to undermine the set.

Naming Consistency5/5

All 21 tools follow a consistent verb-first snake_case pattern with clear semantic verbs: get_ for retrieval, list_ for enumeration, search_ for querying, plus build_research_pack and verify_artifact as lone but clearly communicative composites. There is no mixing of conventions or vague verbs like process or run, making tool selection predictable.

Tool Count4/5

21 tools is above the ideal 3-15 range, but the server covers a broad domain: content retrieval, claims and evidence graphs, risk signals, change monitoring, and integrity verification. A few tools could be consolidated (the changefeed pair and the metadata cluster), but none is pure filler, so the count feels justified though slightly heavy.

Completeness4/5

For a read-only intelligence platform, the coverage is comprehensive: content listing and full-text retrieval, claims and evidence graphs, source auditing, risk indices with history, freshness and risk-diff monitoring, and artifact verification. Minor gaps include no per-source detail endpoint and no push or subscription mechanism, but agents can work around these using list_sources and the changefeed.

Resources