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Iridium: LinkedIn MCP Server

get_activity_log

Get Activity Log

Read the user's activity log. Every action Iridium has taken, newest first.

Iridium records every attempted action in an append-only ledger: what ran, when, whether it succeeded, and the text that was actually sent. This tool reads it. Nothing is sent or changed by calling it.

USE THIS when the user asks what happened, in any form: "what did you do today?" "did that comment actually post?" "show me everything from yesterday" "what failed?"

Answer from this log rather than from memory of earlier turns in the conversation. The log is the record; the conversation is not.

Each entry has: at, action (readable label), surface, status, target (who or what it touched), summary (one sentence), detail (the text that was sent), and error when it failed. Entries older than the user's data-retention window may have no target name, because the profile behind it has been erased. That is expected and is not a failure.

Args: limit: Entries per page, 1-100 (default 20). cursor: next_cursor from a previous call, to fetch the following page. surface: "linkedin" for actions taken on LinkedIn, "iridium" for actions inside Iridium such as sign-ins and draft decisions. Omit for both. status: "success", "failed", or "skipped". Omit for all. action_type: exact slug filter, e.g. "comment_send". Omit for all.

Responses:

200: Successful Response (Success Response) Content-Type: application/json

Input Schema

NameRequiredDescriptionDefault
limitNo
cursorNo
statusNo
surfaceNo
action_typeNo

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden and does so well: it declares 'Nothing is sent or changed by calling it' (read-only safety), discloses newest-first ordering, cursor pagination, and the retention-window caveat where target names may be erased. Missing only things like rate limits or result-size ceilings.

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

Conciseness4/5

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

Front-loaded with purpose and safety before the usage triggers and arg docs; every section serves a purpose. The quoted example queries add real routing value, though the entry-field enumeration borders on verbose.

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

Completeness5/5

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

Despite no output schema and no annotations, the description specifies the returned entry fields (at, action, surface, status, target, summary, detail, error) and the pagination contract via next_cursor. An agent has everything needed to call it and interpret results.

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

Parameters5/5

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

Schema description coverage is 0% and the schema has no enums, yet the description documents every parameter: limit (1-100, default 20), cursor (next_cursor from prior call), surface values ('linkedin'/'iridium', omit for both), status values ('success'/'failed'/'skipped'), and action_type as an exact slug with an example. This fully compensates for the schema gap.

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 ('Read the user's activity log'), its scope ('Every action Iridium has taken, newest first'), and its backing store (append-only ledger). An agent can immediately distinguish it from narrow siblings like get_last_action.

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 explicit trigger conditions with concrete example queries ('what did you do today?', 'what failed?') and a strong directive to answer from the log rather than conversation memory. It does not name alternatives such as get_last_action for single-action lookups, so no exclusion guidance exists.

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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