list_faqsList published Flamel FAQ entries: platform capabilities, pricing model, onboarding, integrations, and security. Good for direct factual questions about the product.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many entries to return (1-100). Defaults to 50. | |
| category | No | Optional FAQ category filter. |
| Name | Required | Description | Default |
|---|---|---|---|
| faqs | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover readOnly, idempotent, non-destructive. The description adds that it lists published entries and what they cover, but doesn't clarify any unusual behavior like default pagination or error handling. Given annotations, it is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that are direct and informative, with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description plus schema and annotations sufficiently cover the tool's purpose and usage for a simple list operation. The output schema is separate, so return values are already defined. The tool is straightforward, and the description provides enough context for when to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with each parameter described. The description does not add additional semantics beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (List) and the specific resource (published Flamel FAQ entries), and enumerates the content categories (capabilities, pricing, integrations, security). It is immediately distinct from sibling tools like list_blog_posts or get_case_study.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says it's good for 'direct factual questions about the product,' which gives usage context. However, it doesn't explicitly mention when not to use it or contrast with search_flamel_content, which might be the alternative for broader queries. It implies the use case but doesn't exclude alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct content type and action: get_* fetches a single item by slug, list_* returns collections, and search_* does full-text search. There is no overlap that could cause misselection.
All tool names follow the same verb_noun pattern with snake_case: get_*, list_*, and search_*. The verbs and nouns are clear and consistent across the entire set.
With 9 tools, the server is well-scoped for a content-focused API. Each tool covers a necessary function (individual retrieval, collection listing, or search) without redundancy or bloat.
The tool surface fully covers the domain of public Flamel content: blog posts (get, list, categories), case studies (get, list), FAQs, testimonials, company overview, and a cross-content search. No obvious read operations are missing.