Post-outcome summary over the last N days: totals, published/partial/failed counts, per-platform volume, and recent platform errors.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Window in days (1-90, default 30) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses what information is returned (totals, counts, per-platform volume, errors) but does not explicitly state that this is a read-only operation, nor does it mention any rate limits or data-gathering side effects. The behavior is inferable but not fully transparent.
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, tightly packed sentence that leads with the core purpose and lists the key output components. Every word earns its place; there is no fluff or redundancy.
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?
Given the tool's simplicity (one optional parameter, no output schema), the description adequately specifies what the summary includes. It could mention the time window's timezone or inclusiveness, but for a lightweight analytics tool, this is sufficient. The absence of an output schema is mitigated by listing the result components.
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% for the single 'days' parameter. The description merely echoes 'over the last N days' without adding new semantic detail beyond the schema's 'Window in days (1-90, default 30)'. Baseline of 3 applies as no additional parameter insight is provided.
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 opens with a specific verb+resource ('Post-outcome summary') and enumerates the exact metrics included: totals, published/partial/failed counts, per-platform volume, and recent platform errors. This clearly differentiates it from sibling tools like get_queue_info or list_published_posts, which focus on operational lists rather than aggregated analytics.
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 the tool is for viewing aggregated post results over a time window, but it does not explicitly state when to use this versus alternatives, nor does it provide exclusions or prerequisites. The context is clear enough, but there is no comparative guidance.
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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Each tool targets a unique resource and action: drafts, scheduled posts, published posts, accounts, analytics, quota, and queue info are all clearly separated. No two tools overlap in purpose; even similar-sounding ones like list_scheduled_posts and list_published_posts are distinct.
All tool names follow a consistent verb_noun pattern with snake_case (e.g., create_post, list_drafts, get_posting_quota). The use of 'list_' for collections and 'get_' for single items/summaries is predictable and logical.
14 tools is well within the ideal 3-15 range and appropriately covers the domain of social media post management, scheduling, drafts, analytics, and account inspection. Each tool serves a distinct function without redundancy.
The surface covers the full lifecycle of posts and drafts: create, read, update, delete, schedule, cancel, and reschedule. Minor gaps exist, such as no direct way to convert a draft into a post, but this can be worked around by copying content.