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Marsell

by com.getmarsell
OverviewDiscussionsAdmin

Timeline query

timeline_query
Read-only

Reads the activity log (Everything Marsell did) for the last days, newest first: each entry's time, engine, kind, title and detail (published, scheduled, replied, ordered, signed up, contacted, decided, dropped, made), with the tokens it was charged where its work recorded them (the ledger's own count, the same the owner sees on that row). Every entry in the span, never a page of them. Use it for what happened and what it cost; what the planning passes decided is journal_read, one contact's history crm_timeline.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "days": "<days>",
      "engine": "<engine>"
    },
    "name": "timeline_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysYesThe span, in days back from now.
engineYesOnly one engine's entries, by its id (content, social, community, search, paid, sites, creators, convert, planner, operator and the rest); null for all.
projectNoThe project's id or exact name. Optional when the account has one project.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), and the description adds real behavior on top: results are newest-first and "every entry in the span, never a page of them," which warns the agent that unpaginated volume is possible. It also explains that token counts come from the ledger's own recorded count. It stops short of saying anything about cost of very wide spans beyond the note on paging, so it is strong rather than exhaustive.

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?

The purpose and scope are front-loaded and every clause is informative rather than filler. It is dense with parentheticals ("Everything Marsell did", "the ledger's own count, the same the owner sees on that row") that cost reading effort without changing what the agent would do.

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?

There is no output schema, so the description carries the return-value burden and does: field list, ordering, entry kinds, token attribution, and the no-pagination guarantee. Combined with 100% schema coverage on all three inputs, an agent has everything needed to call it correctly.

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 coverage is 100%, so the schema already documents days, engine and project. The description only loosely reinforces this with "for the last days" and the engine examples that are already present in the schema; it adds no format or syntax detail beyond it. Baseline 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 (reads the activity log) plus the exact shape of what comes back: time, engine, kind, title, detail and charged tokens, newest first. It also names what it is not — journal_read for planning decisions, crm_timeline for a single contact — so an agent can separate it from the crowded sibling set without opening a schema.

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?

"Use it for what happened and what it cost" gives the positive selection rule, and the following clause names the two alternatives with the condition that routes to each. No exclusions are left implicit.

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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