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Ai Incident Db

by io.github.pipeworx-io
OverviewDiscussionsAdmin

Search Incidents

search_incidents
Read-onlyIdempotent

Search the AI Incident Database. Combines free-text with date range filters. Returns incident IDs, titles, dates, and a short blurb.

Input Schema

NameRequiredDescriptionDefault
limitNo1-200 (default 25)
queryNoFree-text. Every word must appear somewhere in the incident title or description, in any order — "facial recognition bias" finds records mentioning all three, not that exact phrase. Fewer words match more.
offsetNo0-based offset
end_dateNoYYYY-MM-DD upper bound
start_dateNoYYYY-MM-DD lower bound on incident date

Output Schema

NameRequiredDescriptionDefault
offsetNoThe offset this page started at, echoed back.
has_moreNoTrue if more incidents exist past this page. AIID exposes no total count, so this is the only way to distinguish "end of results" from an empty response.
returnedNoHow many incidents are in this page (<= the requested limit).
incidentsNoList of matching incidents

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedOutput schema / properties / has_more
      Added value: +{
+  "description": "True if more incidents exist past this page. AIID exposes no total count, so this is the only way to distinguish \"end of results\" from an empty response.",
+  "type": "boolean"
+}
    • addedOutput schema / properties / offset
      Added value: +{
+  "description": "The offset this page started at, echoed back.",
+  "type": "number"
+}
    • addedOutput schema / properties / returned
      Added value: +{
+  "description": "How many incidents are in this page (<= the requested limit).",
+  "type": "number"
+}
  2. Changed2 schema fields changed
    • changedInput schema / examples
      Previous value: -[
-  {
-    "query": "facial recognition bias"
-  },
-  {
-    "end_date": "2024-01-01",
-    "limit": 50,
-    "query": "chatbot misinformation",
-    "start_date": "2023-01-01"
-  }
-]New value: +[
+  {
+    "query": "facial recognition bias"
+  },
+  {
+    "end_date": "2025-01-01",
+    "limit": 50,
+    "query": "chatbot misinformation",
+    "start_date": "2024-01-01"
+  }
+]
    • changedInput schema / properties / query / description
      Previous value: -"Free-text — title / description"New value: +"Free-text. Every word must appear somewhere in the incident title or description, in any order — \"facial recognition bias\" finds records mentioning all three, not that exact phrase. Fewer words match more."
  3. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "query": "facial recognition bias"
+  },
+  {
+    "end_date": "2024-01-01",
+    "limit": 50,
+    "query": "chatbot misinformation",
+    "start_date": "2023-01-01"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "incidents": {
+      "description": "List of matching incidents",
+      "items": {
+        "properties": {
+          "date": {
+            "description": "Incident date in YYYY-MM-DD format",
+            "type": "string"
+          },
+          "description": {
+            "description": "Short description of the incident",
+            "type": "string"
+          },
+          "editors_notes": {
+            "description": "Editorial notes on the incident",
+            "type": "string"
+          },
+          "incident_id": {
+            "description": "Unique incident identifier",
+            "type": "number"
+          },
+          "title": {
+            "description": "Incident title",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "type": "object"
+}
  4. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, fully covering the safety profile. The description adds the return-shape note (IDs, titles, dates, blurb) which complements and does not contradict the annotations. It doesn't describe pagination mechanics or rate limits, but annotations carry the bulk safely.

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 sentences, zero waste. States the database, the filter combination, and the return shape concisely. Every clause carries information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present and 100% parameter coverage plus rich annotations (read-only, idempotent, non-destructive), the description covers what a search tool needs: what it searches, what filters, and what it returns. A short mention of result ordering or the blurb source would push it to 5, but this is complete for the structured context provided.

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 parameters are fully documented in the schema itself (limit range, query semantics, offset type, date formats). The description adds the return shape but not parameter-specific detail beyond schema. Baseline 3 applies appropriately.

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+resource ('Search the AI Incident Database') and clearly states what it returns ('incident IDs, titles, dates, and a short blurb'). It distinguishes from siblings like get_incident (single record) and list_recent (recent items), establishing this as the free-text/criteria search tool.

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 names the two combining filters (free-text + date range) which provides clear context for when to use this vs list_recent or search_within. It doesn't explicitly name alternatives or give when-not guidance, but the sibling context makes the distinct search role clear.

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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