postsFetch specific Tenor GIFs/stickers by their post IDs (ids, comma-separated) — use to re-resolve media URLs and metadata for results returned earlier by search or featured.
| Name | Required | Description | Default |
|---|---|---|---|
| ids | Yes | ||
| client_key | No | ||
| media_filter | No |
| Name | Required | Description | Default |
|---|---|---|---|
| results | No | Posts by ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive nature. The description adds behavioral context by specifying the comma-separated IDs format and the return purpose (re-resolving media URLs and metadata). It does not introduce contradictions or undisclosed destructive behaviors, and the added context is valuable beyond annotations.
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?
The description is a single, well-structured sentence that front-loads the primary action. It is concise with no redundant wording, and every piece of information (resource, scope, use case) contributes to understanding.
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 tool has a simple 3-parameter schema, a comprehensive annotation set (read-only, idempotent, non-destructive), and an output schema. The description covers the main purpose and usage context, and it adds the comma-separated detail. It does not need to explain return values due to output schema; the only minor gap is no mention of optional parameters, but their names are self-explanatory.
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 description coverage is 0%, so the description must compensate. It provides the comma-separated format for the 'ids' parameter, which is not in the schema. However, it does not explain 'client_key' or 'media_filter', leaving these parameters without additional semantics. Partial compensation, hence a 3.
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 uses a specific verb 'Fetch' and clearly states the target resource (Tenor GIFs/stickers) and scope (by post IDs). It explicitly distinguishes from sibling tools like search and featured by noting it re-resolves results from those tools, indicating a unique purpose.
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?
It explicitly states when to use the tool: 're-resolve media URLs and metadata for results returned earlier by search or featured.' This gives clear context for usage, though it does not explicitly list when-not-to-use or alternative tools; however, the mention of search/featured as the source of IDs implies this is not for discovery.
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.
Several tools have nearly identical purposes: autocomplete and search_suggestions both return query completions, ask_pipeworx and ask_pipeworx_beta are currently identical, and ai_visibility_check overlaps with scan_competitor_ai_presence. The detailed descriptions help for some, but the overlapping clusters create real confusion for an agent selecting a tool.
Naming is a mix of single-word nouns (search, featured, posts, categories) and snake_case verb phrases (resolve_entity, compare_entities, ask_pipeworx), with modifier suffixes like _beta and _grounded. While the snake_case is consistent where used, the overall pattern is not uniform across the server.
38 tools is far too many for a server named 'Tenor' whose core GIF API needs only a handful. Much of the surface belongs to Pipeworx data, polymarket analytics, memory, and subscriptions—scope that belongs in a different server or a clearly separated package.
The Pipeworx side is remarkably complete: query (ask_pipeworx), grounded answers, deep research, entity profiles, comparisons, validation, discovery, memory, subscriptions, and specialized polymarket tools all cover their domain thoroughly. The Tenor side has search, browse, categories, trending, suggestions, and post retrieval—no critical dead ends.