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Glama

Islam West Africa Collection (IWAC)

Search audiovisual materials

search_audiovisual
Read-onlyIdempotent

Search audiovisual materials by keyword and metadata: francophone web video from Burkina Faso, Togo and Benin (TV reports, association and campus recordings), plus deposited Nigerian Hausa/Arabic recordings. Keyword matches title, creator, publisher, subject, spatial, language, source, the item's own description (the richest text most of these items have) and its transcription where one exists. Each row says which population it is from (source_type) and carries either external_url (a video to watch) or media_url (a file), never both.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoDefault 20, max 50
mediumNoExact carrier medium: Vidéo sur le web | DVD | CD (validated, accents optional)
offsetNo
countryNoExact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional). Burkina Faso, Togo, Benin and Nigeria only — no Niger or Ivorian items
keywordNoSubstring match across audiovisual title/metadata fields
subjectNoExact subject tag — only ~27 rows carry one, so prefer publisher/keyword
languageNoExact language value, e.g. Français | Haoussa | Arabe | Anglais | Mooré
publisherNoSubstring on the publishing channel/broadcaster, e.g. RTB | AEEM | CERFI
source_typeNoyoutube (harvested web video, the large majority) | deposited (recordings with a file, 47)

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already provide readOnlyHint=true and idempotentHint=true, so the description does not repeat safety. It adds behavioral value by explaining that each result row includes source_type and either external_url or media_url (never both), and that keyword does substring matching across multiple fields. This goes beyond the annotations to clarify output shape and search behavior.

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 a single, dense paragraph of about five sentences. It is front-loaded with the core action and immediately provides the geographic and material scope. Every sentence adds specific, non-redundant information. No fluff or repetition.

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?

Given the tool has 9 parameters and no output schema, the description covers the main search behavior, field matching, and the key output distinction (external_url vs media_url). It does not explain pagination behavior beyond schema defaults, nor does it list all response fields (though it implies them via the matched fields). For a search tool, this is reasonably complete but could mention sorting or offset behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 89% schema coverage, the schema already documents parameters well. The tool description adds context for keyword (explaining which fields it matches), source_type (defining 'youtube' vs 'deposited'), and country (specifying exactly which countries are present and excluding Niger and Ivory Coast). These clarifications are valuable beyond the schema's concise descriptions.

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 'Search audiovisual materials by keyword and metadata' and enumerates the specific content: francophone web video from three countries plus deposited Nigerian recordings. It explains what fields are matched, which distinguishes it from sibling tools like list_audiovisual (which likely just lists) and get_audiovisual (which retrieves a single item). The verb+resource is specific and unambiguous.

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 description implies usage context by naming the content scope and search fields, but it does not explicitly state when to use this tool versus alternatives like search (general), search_documents, or list_audiovisual. No 'when not to use' or comparative guidance is provided. The purpose is clear but the tool lacks explicit decision support.

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

A4/5.0
Disambiguation5/5

Each tool targets a distinct resource or analytical dimension: get_* tools are specific to item categories (article, audiovisual, document, image, publication, reference) or specific analyses (cooccurrence, field distribution, lexical metrics, semantic map, sentiment distribution, similar items, temporal distribution, topic distribution). Search tools are clearly separated by subset, with generic 'search' for cross-category discovery and search_* for filtered queries. The only potential overlap between 'fetch' and get_* is resolved by 'fetch' returning a standard format while get_* tools provide category-specific extra metadata.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern: fetch, get_*, list_*, search_*. The verbs are clear and the nouns precisely indicate the resource or action. There are no mixed conventions (e.g., no camelCase or inconsistent verb styles), making the naming predictable and easy to navigate.

Tool Count2/5

At 34 tools, the count is well above the 25+ threshold that the rubric flags as too many. While the server's comprehensive scope for a digital archive with multiple subsets and analytical features explains the high count, the sheer number may overwhelm agents and makes the toolset feel heavy rather than well-scoped. Some grouping or consolidation (e.g., merging distribution tools or providing a single fetch with optional detail levels) could reduce the load without losing functionality.

Completeness5/5

The tool surface provides complete coverage for the domain: every content type (articles, publications, references, documents, audiovisual, images, index) has both search and get/retrieve tools, plus listing tools for key vocabularies. Analytical tools for statistics, distributions, sentiment, topics, and similarity are fully realized. There are no obvious dead ends—users can discover, retrieve, and analyze all parts of the collection, and even gaps in the underlying data (e.g., limited OCR coverage) are explicitly surfaced via tools like get_collection_stats.