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What Led To

Get a timeline

get_timeline

One timeline in full: TL;DR, dated entries newest first with sources and quotes, relations between entries, links to other timelines, what to watch next and open questions. Pass since=YYYY-MM-DD to get only entries dated on or after that day (what changed recently).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesTimeline slug, from list_timelines or a page URL (/events/<slug>).
limitNoMost recent entries to return (default 60).
sinceNoOnly entries dated on or after this day. Pass the updated_at you last saw to get what changed since.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations and no output schema, the description carries the full disclosure burden and does substantial work: it enumerates the response contents, states ordering ('newest first'), and explains the since filter's incremental-refresh use case. It stops short of explicitly confirming read-only semantics or what happens for an unknown slug, but the retrieval nature is unambiguous from 'get' and the content inventory.

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?

Two sentences, front-loaded with what the call returns, and the content list is dense but justified because no output schema exists to carry that information. The since sentence is compact and ends with the motivating use case. Slightly list-heavy, but nothing is padding.

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 3-param read tool with no annotations and no output schema, the description covers the response shape and the one non-obvious parameter's intent, which is the information an agent most needs. It lacks explicit read-only confirmation and error behavior for a bad slug, but overall it is complete enough to invoke 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 description coverage is 100%, so slug, limit, and since are all documented in the schema already. The description restates the since semantics with a practical framing ('what changed recently') that mildly reinforces the schema's 'updated_at you last saw' note, but adds no syntax or format detail beyond it, and says nothing about limit or slug. 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?

Specific verb+resource ('One timeline in full') followed by an explicit inventory of what is returned: TL;DR, dated entries, relations, links, watch-next, open questions. This clearly separates it from get_entry (a single entry) and list_timelines (the index), so an agent can route without opening schemas.

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

Usage Guidelines3/5

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

The description gives one concrete usage pattern for the since filter ('what changed recently'), which is genuinely actionable. However, it never states when to prefer this tool over siblings like get_entry or search_entries, nor any preconditions (e.g., needing a valid slug from list_timelines). Usage is implied rather than prescribed.

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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