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Glama

l0g.fr Risk Intelligence

by io.github.bluetouff

Get Changefeed

get_changefeed
Read-onlyIdempotent

Renvoie les dernières publications, révisions et politiques avec objectId, version/hash courant, statut de diff et changement sémantique. À utiliser pour surveiller le corpus sans tout rescanner.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNombre maximum d'entrées.
contentTypeNoType de contenu optionnel.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
errorNo
entriesNo
versionNo
generatedNo
feedPolicyNo

Schema Changelog

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

  1. Added
  2. Removed
  3. Changed2 schema fields changed
    • addedOutput schema / properties / entries / items / properties / language
      Added value: +{
+  "enum": [
+    "fr",
+    "en"
+  ],
+  "type": "string"
+}
    • changedOutput schema / properties / entries / items / required
      Previous value: -[
-  "id",
-  "objectId",
-  "date",
-  "type",
-  "contentType",
-  "slug",
-  "title",
-  "url",
-  "changedFields",
-  "summary",
-  "previousVersion",
-  "currentVersion",
-  "previousHash",
-  "currentHash",
-  "replaces",
-  "semanticChange",
-  "correctionReason",
-  "diffStatus"
-]New value: +[
+  "id",
+  "objectId",
+  "date",
+  "type",
+  "contentType",
+  "language",
+  "slug",
+  "title",
+  "url",
+  "changedFields",
+  "summary",
+  "previousVersion",
+  "currentVersion",
+  "previousHash",
+  "currentHash",
+  "replaces",
+  "semanticChange",
+  "correctionReason",
+  "diffStatus"
+]
  4. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful behavioral context about what the feed contains and its diff-related output, but does not disclose details like ordering, time-window, or pagination behavior beyond the limit parameter.

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: the first fronts the returned data, and the second gives the intended use case. There is no filler, repetition, or unnecessary 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, read-only, zero-required-parameter tool with a full input schema and an output schema, the description is complete enough. It names the returned artifact types and fields, and states the intended monitoring scenario, so an agent can decide whether to call it without additional context.

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%, so the schema already documents both parameters (limit and contentType) adequately. The description adds no extra parameter-level meaning beyond its mention of content types, which aligns with the schema's enum. 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 clearly states a specific verb ('Renvoie') and the resource (latest publications, revisions, policies), and lists key returned fields (objectId, current version/hash, diff status, semantic change). It also conveys a distinct monitoring purpose, which separates it from sibling tools like get_ndjson_feed or get_changes.

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 explicitly says to use it for monitoring the corpus without rescanning everything ('À utiliser pour surveiller le corpus sans tout rescanner'), providing a clear context. It does not mention when not to use it or name alternative tools, so it misses the full exclusionary 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

A3.9/5.0
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