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Flux LinkedIn MCP

Resolve Post Collection

resolve_collection

Resolve a post collection into a concrete list of post_ids. For manual / auto_stream collections, returns stored members. For smart collections, evaluates the collection's config predicate against the user's posts and returns matches. Free — costs 0 credits.

Input Schema

NameRequiredDescriptionDefault
limitNoMax post_ids to return (default 1000)
collection_idYesCollection id (from list_collections / create_collection)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations present, the description carries the full burden and mostly delivers: it discloses that the operation is cost-free, that behavior branches by collection type, and that smart collections are evaluated by predicate rather than read from storage — a meaningful, non-obvious trait. It does not state whether the result is truncated at the schema's limit (default 1000, max 5000) or what happens for a missing/unknown collection_id.

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?

Three short sentences, front-loaded with the core action and output, then the branch conditions, then the cost note. Every sentence earns its place with no restatement of the name or title.

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

Completeness4/5

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

For a two-parameter, fully documented, non-nested read tool with no output schema, the description covers the essential contract: what is returned (post_ids) and how membership is determined. Remaining gaps (truncation at limit, ordering, error behavior for invalid ids) are minor but real.

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% — collection_id's provenance (list_collections / create_collection) and limit's bounds are already documented in the schema. The description adds no additional parameter semantics beyond the schema, so the baseline of 3 applies.

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?

States a specific verb and resource ('Resolve a post collection') plus the concrete output ('a list of post_ids'), and the second/third sentences distinguish the collection kinds (manual/auto_stream vs. smart) so the agent knows exactly what resolving means in each case. This clearly separates it from siblings like add_to_collection or get_posts.

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

Usage Guidelines4/5

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

Gives clear operating context, including which collection types it handles and the explicit cost signal ('Free — costs 0 credits'), which is a real decision input when alternatives like get_posts cost credits. It does not explicitly name an alternative tool or state when not to call it, so it stops short of a 5.

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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