Islam West Africa Collection (IWAC)

Search newspaper articles

search_articles

Read-onlyIdempotent

Search IWAC newspaper articles by keyword (title + OCR + AI abstracts, French and English), country, newspaper, subject, and date range. Use French concept keywords regardless of the user's report language. Matching is accent- and case-insensitive.

Input Schema

TableJSON Schema

Name	Required	Description
`exact`	No	AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>.
`limit`	No	Default 20, max 100 (10 and 25 with with_description)
`offset`	No
`country`	No	Exact country name: Benin \| Burkina Faso \| Côte d'Ivoire \| Niger \| Togo (accents optional)
`date_to`	No	YYYY-MM-DD (or YYYY)
`keyword`	No	Concept keyword; substring match on title, OCR text, and the French and English AI abstracts. Prefer French for the OCR; an English term still matches via the English abstract
`subject`	No
`date_from`	No	YYYY-MM-DD (or YYYY)
`newspaper`	No
`hijri_year`	No	Islamic (Umm al-Qura) year, e.g. 1445
`hijri_month`	No	Islamic lunar month: 1-12, or a name (Ramadan, Chaabane, Chawwal, Dhu al-Hijja). Pulls the articles behind an observance peak — matches only items with a full YYYY-MM-DD date.
`keyword_mode`	No
`keyword_aliases`	No
`with_description`	No	Include each article's ~500-char AI abstract (description_ai) for triage without get_article. Adds ~125 tokens/row, so `limit` defaults to 10 and caps at 25 while this is on.

Schema Changelog

Changes observed during successful MCP inspections.

Changed9 schema fields changedOct 6, 2026

addedInput schema / properties / exact

Added value: +{
+  "additionalProperties": {
+    "items": {
+      "type": "string"
+    },
+    "maxItems": 20,
+    "minItems": 1,
+    "type": "array"
+  },
+  "description": "AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>.",
+  "propertyNames": {
+    "type": "string"
+  },
+  "type": "object"
+}

removedInput schema / properties / hijri_year / maximum
```
Removed value: -9007199254740991
```
removedInput schema / properties / hijri_year / minimum
```
Removed value: --9007199254740991
```

addedInput schema / properties / keyword_aliases

Added value: +{
+  "items": {
+    "minLength": 1,
+    "type": "string"
+  },
+  "maxItems": 12,
+  "type": "array"
+}

addedInput schema / properties / keyword_mode

Added value: +{
+  "enum": [
+    "literal",
+    "all_terms"
+  ],
+  "type": "string"
+}

removedInput schema / properties / limit / maximum
```
Removed value: -9007199254740991
```
removedInput schema / properties / limit / minimum
```
Removed value: --9007199254740991
```
removedInput schema / properties / offset / maximum
```
Removed value: -9007199254740991
```
removedInput schema / properties / offset / minimum
```
Removed value: --9007199254740991
```

Changed1 schema field changedAug 7, 2026

changedInput schema / properties / keyword / description

Previous value: -"French concept keyword; substring match on title, OCR text, and AI abstract"New value: +"Concept keyword; substring match on title, OCR text, and the French and English AI abstracts. Prefer French for the OCR; an English term still matches via the English abstract"

Changed2 schema fields changedAug 4, 2026

changedInput schema / properties / limit / description

Previous value: -"Default 20, max 100"New value: +"Default 20, max 100 (10 and 25 with with_description)"

changedInput schema / properties / with_description / description

Previous value: -"Include each article's ~500-char AI abstract (description_ai) for triage without get_article. Adds ~125 tokens/row, so pass a smaller limit (≤10) when enabling it."New value: +"Include each article's ~500-char AI abstract (description_ai) for triage without get_article. Adds ~125 tokens/row, so `limit` defaults to 10 and caps at 25 while this is on."

Changed2 schema fields changedJul 31, 2026

addedInput schema / properties / hijri_month

Added value: +{
+  "description": "Islamic lunar month: 1-12, or a name (Ramadan, Chaabane, Chawwal, Dhu al-Hijja). Pulls the articles behind an observance peak — matches only items with a full YYYY-MM-DD date.",
+  "type": "string"
+}

addedInput schema / properties / hijri_year

Added value: +{
+  "description": "Islamic (Umm al-Qura) year, e.g. 1445",
+  "maximum": 9007199254740991,
+  "minimum": -9007199254740991,
+  "type": "integer"
+}

Changed1 schema field changedJul 29, 2026

changedInput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

Changed6 schema fields changedJul 6, 2026
- removedInput schema / additionalProperties
```
Removed value: -false
```
- changedInput schema / properties / keyword / description
```
Previous value: -"Substring match on title, OCR text, and AI abstract"New value: +"French concept keyword; substring match on title, OCR text, and AI abstract"
```
- addedInput schema / properties / limit / maximum
```
Added value: +9007199254740991
```
- addedInput schema / properties / limit / minimum
```
Added value: +-9007199254740991
```
- addedInput schema / properties / offset / maximum
```
Added value: +9007199254740991
```
- addedInput schema / properties / offset / minimum
```
Added value: +-9007199254740991
```
First observedJul 5, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description still adds real behavioral detail: matching is accent- and case-insensitive, and keyword scans title + OCR + both AI abstracts — semantics an agent could not derive from the annotations. It omits result ordering and pagination behavior.

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?

Two dense sentences with no filler, and the scope statement is front-loaded before the keyword-language rule. Slightly over-packed parentheticals, but 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?

For a complex, 14-parameter, nested-object tool with no output schema, the description delivers the essentials: what corpus is searched, which text fields the keyword hits, and the French-keyword rule. The many advanced parameters and the `exact` object are left entirely to the schema, which is acceptable given the schema does document them.

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?

With 14 parameters and only 64% schema description coverage, the description names roughly five facets (keyword, country, newspaper, subject, dates) but says nothing about exact, limit/offset, hijri_year/month, keyword_mode, keyword_aliases, or with_description. Its one added nuance — which fields the keyword matches and accent/case insensitivity — is useful but partial, so it neither compensates fully nor is purely redundant.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource ('Search IWAC newspaper articles') and enumerates the facets searched (keyword, country, newspaper, subject, date range), which cleanly separates it from get_article or the stats tools. It stops short of naming the neighboring search_* siblings (search_documents, search_index, search_publications), so the agent must still infer which corpus each covers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The line 'Use French concept keywords regardless of the user's report language' is a concrete, actionable usage rule and is genuinely helpful. However, it gives no guidance on when to prefer this tool over search_documents or search, and no prerequisites/exclusions are stated, leaving the selection decision to inference.

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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Search newspaper articles

Input Schema

Schema Changelog

TDQS

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