get_post_refillShow the automatic posting refill for this brand: whether it is on, whether it is in dry-run (preview) mode, how many days ahead it fills, its render budget, when it next runs, and how many posts are queued right now. It also names the channels that CANNOT be posted to and why. Read-only, free.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and destructiveHint, so the safety profile is covered. The description adds value by detailing what the tool returns (dry-run mode, render budget, blocked channels and reasons) and by noting 'free' — a cost signal not in annotations. It also indicates scoping to 'this brand', implying reliance on brand context. No contradiction with annotations; the extra info improves transparency beyond the metadata.
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 sentence that front-loads the core purpose and then enumerates the returned fields efficiently. It packs substantial detail into about 70 words without redundancy. While it is a long sentence, it is well-structured and every clause adds distinct information. It could be slightly tighter, but it is appropriate for the complexity.
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 and no parameters, the description carries the full burden of explaining what the agent will receive. It lists all key return items: on/off status, dry-run mode, days ahead, render budget, next run time, queued posts, and blocked channels with reasons. It also notes 'read-only' and 'free'. This is thorough for a status-query tool, leaving no major gaps for an agent to call it correctly.
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?
The tool has zero parameters, so the schema covers them trivially. With no params, the baseline is 4, and the description does not need to add parameter details since there are none. The description correctly avoids mentioning nonexistent parameters, keeping it clean. No additional semantic burden exists.
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 ('Show') and resource ('automatic posting refill for this brand'), then enumerates the exact attributes returned (on/off, dry-run, days ahead, budget, next run, queued posts, blocked channels). This clearly distinguishes it from sibling tools like set_post_refill and run_post_refill, which modify or execute the refill rather than just displaying status.
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 implies its use for checking status via 'Show' and explicitly states 'Read-only, free', but it does not explicitly state when to use this over alternatives or when not to use it. There is no mention of comparing with set_post_refill or run_post_refill. The guidance is implicit rather than explicit, so it falls short of a higher score.
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.