Delivery receipt for a post: per-platform outcome (published/failed/retrying/pending), platform post ids, and the platform's real error text. Use this to VERIFY a post actually went live instead of assuming. Accepts the id from create_post or from list_published_posts.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Post id (scheduled or published) |
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 the type of output (per-platform outcome, platform post ids, real error text) and indicates the verification behavior. It does not explicitly state side-effects, but 'get' and 'receipt' imply a non-mutating read, and the described statuses add transparency beyond a generic 'get by id'.
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 compact and front-loaded: the first sentence immediately states what the tool returns, the second sentence states its purpose, and the last sentence clarifies parameter provenance. No wasted words or filler.
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?
For a simple one-parameter read tool with no output schema, the description fully covers what it does, why to use it, what to expect, and how to obtain the required id. It leaves no major gaps for an agent to understand invocation and outcome.
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%, describing the id as 'Post id (scheduled or published)'. The description adds source-of-truth context ('Accepts the id from create_post or from list_published_posts'), which is a meaningful semantic enrichment beyond the schema's basic definition.
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 defines the tool's purpose: obtaining a delivery receipt showing per-platform outcome, platform post IDs, and real error text. It uses specific verbs and resource scope ('Delivery receipt for a post') and distinguishes from siblings like get_analytics_summary by emphasizing verification of whether a post went live.
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 gives explicit guidance on when to use this tool ('Use this to VERIFY a post actually went live instead of assuming') and notes the id can come from create_post or list_published_posts. It does not explicitly mention exclusions or alternatives, but the context is clear enough for an agent to select it over other read/list tools.
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.