Full content of one post (returned under data.post). For comments use /posts/comments. (Costs 10 Zooq credits.)
| Name | Required | Description | Default |
|---|---|---|---|
| entityId | Yes | Activity id — bare numeric or urn:li:activity: form, both accepted. Get it from companies_posts — read data.activities[].entityId (person feeds are currently unavailable). |
| Name | Required | Description | Default |
|---|---|---|---|
| post | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the operation as read-only and idempotent; the description adds value by disclosing the 10-credit cost and noting the data.post return path. There is no contradiction with the 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?
The description is compact and front-loaded: purpose first, then the routing rule, then the cost. Every clause earns its place with no filler or repetition.
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 one-parameter, read-only tool with a rich schema and an output schema, this description covers the essential calling context: single-post scope, return path, comments alternative, and credit cost. Nothing critical is missing.
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 single parameter entityId is fully documented in the schema, including accepted formats and how to obtain it from companies_posts. Since schema coverage is 100%, the description need not add parameter detail; it adds none.
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 states that the tool returns the full content of one post and specifies the response location (data.post), which is specific and actionable. It also distinguishes itself from the comments tool by explicitly routing comment requests to /posts/comments.
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?
It provides a clear when-not/alternative rule: use /posts/comments for comments. It also scopes the call to a single post, so an agent knows this is not for listing or bulk retrieval.
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.
Most tools are separated by domain prefixes and the descriptions are unusually explicit about differences, but there are direct overlaps: companies_name_lookup is the same upstream as search_companies, companies_entity_id vs companies_universal_name_to_id resolve different id spaces, and search_people/search_people_live plus search_companies/search_companies_live cover similar ground. An agent can usually pick correctly, but only after close reading.
The set is consistently snake_case with readable domain prefixes like companies_, jobs_, posts_, profile_, and search_. Deviations include the unexplained g_* prefix, jobs_details_v2's version suffix, affiliate_program lacking a resource prefix, and the duplicate naming convention of companies_name_lookup vs search_companies.
45 tools is well above the 25+ threshold and creates a heavy surface for an agent to scan. While the domains are broad, some tools are redundant (companies_name_lookup/search_companies) or tangential (affiliate_program), so the count is not fully justified.
The server covers people, companies, jobs, posts, email, schools, and skills with both search and detail endpoints, which is strong for a read-only LinkedIn API. Obvious gaps like a global post search or a company followers list are absent, but the existing paths support most workflows without dead ends.