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flevy

by com.flevy

Get Content Details

get_content_details
Read-only

Full metadata for one Flevy item, by content_id from search_content (e.g. "doc-1234" or "case-567"). Documents return the author with their credentials (headline, bio, LinkedIn, profile URL; pass the author name to search_content's author filter to list more of their documents), full description, editor summary, AI summary, and editorial review when available, page/slide count, price, FlevyPro inclusion, management topics, ranking badge, and the number of slide deep dives available. Case studies return the client situation, TL;DR, and summary. Call this before recommending an item so you can describe it accurately and cite the author's credentials, and share the returned flevy.com URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
content_idYesThe content_id from search_content: "doc-<n>" for documents, "case-<n>" for case studies.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds substantial behavioral detail by enumerating exactly what fields are returned for documents vs. case studies, including author credentials, summaries, pricing, and the flevy.com URL. This goes beyond annotations to set expectations.

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, well-organized sentence that front-loads the core purpose, then breaks down details by content type. It packs much information without redundancy, earning its length.

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?

With no output schema, the description carries the full burden of explaining return values. It covers both document and case study metadata, mentions the returned URL, and provides usage context, making it highly complete for the tool's complexity.

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 coverage is 100% and the schema description already explains the content_id format ('doc-<n>' or 'case-<n>'). The description only repeats the example, adding no extra semantic meaning beyond what the schema provides, so the baseline score of 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 it retrieves full metadata for one Flevy item by content_id, distinguishing it from sibling tools like search_content (search) and get_slide_deep_dive (deep dives). It specifies the resource and the verb 'get' with a clear scope.

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

Usage Guidelines5/5

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

Explicitly instructs to call this before recommending an item and explains how to use the returned author name with search_content. This provides clear when-to-use guidance and differentiates from alternatives.

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

A4.7/5.0
Disambiguation5/5

Each tool targets a distinct action: searching the catalog, retrieving item metadata, previewing slides, listing topics, and deep-diving into a single topic. No two tools serve the same purpose; even list_topics and get_topic_details are clearly differentiated by scope (all topics vs one topic).

Naming Consistency5/5

All tools follow a verb_noun pattern with snake_case: get_content_details, get_slide_deep_dive, get_topic_details, list_topics, search_content. The verbs (get, list, search) are appropriate for their actions and consistent throughout.

Tool Count5/5

With 5 tools, the set is well-scoped for a content marketplace, covering search, retrieval, preview, and topic exploration without redundancy. It fits comfortably within the ideal 3-15 range and each tool earns its place.

Completeness5/5

The tools cover the full discovery journey: browse topics, search content, get detailed metadata, and preview slides. There are no critical gaps for the marketplace's purpose; even author and related topic information are accessible through existing tools, so the workflow has no dead ends.

Resources