search_threadsOrganic Threads keyword search (/v1/threads/search) — short-form text/social posts for trend + voice research. Returns compact JSON {desc, author, handle, likes, link, cover} per post. Spends about a credit.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | max posts returned (1–25, default 8) | |
| query | Yes | keyword to search Threads for |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false), lowering the bar. The description adds genuinely useful non-annotation behavior: 'Spends about a credit' discloses cost, and the compact JSON field list documents the return shape. No contradiction with 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?
Three compact, purposeful pieces: purpose sentence, return format, and credit cost. Purpose is front-loaded, and every clause earns its place with no filler or repetition of the title.
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?
With no output schema, the description correctly documents the return structure. Two simple parameters at full schema coverage plus read-only annotations make this nearly complete. Minor omissions — no mention of sorting, pagination, or empty-result behavior — keep it just short of a 5.
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 100% — both query and limit are documented with meaning in the input schema. The description adds the return-field context ({desc, author, handle, likes, link, cover}) but does not materially enrich parameter-level semantics beyond what the schema already states, so the baseline 3 applies.
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?
States a specific verb plus resource ('Threads keyword search'), names the exact endpoint (/v1/threads/search), and scopes the purpose to 'short-form text/social posts for trend + voice research.' The return format is specified, so an agent knows exactly what comes back.
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?
Provides clear context that this is a keyword search on organic Threads posts intended for trend and voice research. It does not, however, name alternatives like search_threads_keyword, search_threads_locations, or list_threads_posts, so an agent facing those near-identically named siblings gets no explicit routing guidance.
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.
With 293 tools, the surface is enormous and many tools have overlapping purposes—multiple posting tools (post_to_meta, post_to_linkedin, schedule_post, etc.), multiple analytics tools per channel, and several search tools (search_meta_ads, search_instagram, search_reddit...). While each description is detailed, the volume makes it difficult for an agent to reliably distinguish between similar tools without careful reading, leading to frequent misselection.
The naming is largely consistent with a verb_noun pattern (post_to_*, list_*, create_*, delete_*, update_*, manage_*). There are clear families for major operations. A few outliers like 'google_business_account', 'hermoso_capabilities', and 'store_get' break the pattern, but the overwhelming majority follow a predictable structure, making navigation somewhat easier.
293 tools is far beyond any reasonable scope for a single MCP server, even for a comprehensive marketing platform. The calibration guide flags 50+ as an extreme mismatch, and this is nearly six times that threshold. Such a large surface overwhelms context windows, increases the probability of misselection, and makes it impractical for agents to learn or use effectively.
The tool set covers a vast domain: ad creation and rendering, posting across nine+ social channels, analytics and reporting, file management (Drive/OneDrive), competitor research, brand management, and more. It appears to provide CRUD and lifecycle coverage for most resources. While there may be minor gaps given the immense scope, the overall coverage is impressively comprehensive.