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ContentIn — LinkedIn Ghostwriter

List ContentIn posts

list_posts
Read-onlyIdempotent

List the posts on this ContentIn profile — drafts, scheduled, published and ideas. Use this to find a post's id before scheduling, publishing, repurposing or pulling analytics for it, and to answer questions about what the user has written or has queued up. Returns a 280-character excerpt of each post, never the full body.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoISO-8601 date. Only posts created on or before this.
fromNoISO-8601 date. Only posts created on or after this.
limitNoHow many posts to return (1-50, default 20).
searchNoFree-text match against the post body and title.
statusNoFilter by post status. Omit for all statuses. 'draft' = written but not queued, 'scheduled' = queued for automatic publishing, 'posted' = already live on LinkedIn.

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by disclosing that it returns a 280-character excerpt (never the full body), which is crucial for the agent to know. However, it does not mention ordering, pagination behavior beyond the limit parameter, or rate limits. The added detail is helpful but not exhaustive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with the core purpose, followed by usage context and a key behavioral constraint. Every sentence adds necessary information without redundancy or fluff. It is well-structured for quick scanning by an AI agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that there is no output schema, the description should ideally explain the return structure beyond '280-character excerpt'. It mentions that IDs can be found (implied) but does not explicitly state that IDs, status, title, etc. are returned. For a listing tool with 5 parameters and no output schema, the description could more fully describe the output fields to help the agent understand what it will receive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description does not add extra meaning to the parameters (to, from, limit, search, status) beyond what the schema already provides. It mentions categories like 'drafts, scheduled, published and ideas' which partially map to the status enum but are not parameter documentation. No additional value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'List' and the resource 'posts on this ContentIn profile', and enumerates the categories (drafts, scheduled, published, ideas). It distinguishes from sibling tools like write_post, publish_post, schedule_post, repurpose_post, and get_post_analytics by focusing on listing vs. creating, editing, or analytics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly specifies when to use this tool: to find a post's id before scheduling, publishing, repurposing, or pulling analytics, and to answer questions about posts the user has written or queued. This provides clear context and implies it is the appropriate choice for listing posts, not for mutations or detailed analytics.

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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TDQS

A4.6/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: capturing user substance, generating ideas from scratch, writing posts from user material, repurposing posts, scheduling, publishing, listing, and analytics. There is no ambiguity or overlap, as even similar actions like publishing and scheduling are differentiated by timing and require separate confirmation flows.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., capture_substance, generate_ideas, write_post_in_my_voice). The verbs are descriptive and the nouns clearly indicate the resource or action, making the naming predictable and easy to understand.

Tool Count5/5

With 8 tools, the server is well-scoped for a LinkedIn ghostwriting assistant. Each tool covers a necessary step in the content lifecycle: capturing input, generating ideas, writing, repurposing, scheduling, publishing, listing, and analytics. The number is neither excessive nor insufficient for the domain.

Completeness4/5

The tool set covers the core workflow of content creation, scheduling, publishing, and analytics. Minor gaps exist, such as no direct post editing (beyond repurposing), no explicit pillar management, and no deletion tool. However, these are edge cases and do not hinder the primary ghostwriting purpose.

Resources