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Get X following

get_twitter_following
Read-only

Accounts the user follows on X (Twitter), from the synced follow graph — name, @handle, and bio. query filters by name, handle, or bio text ('who do I follow in AI?'). Reads the last sync, so a just-followed account may be missing; total_followed is the synced total. If it reports no account connected, tell the user to connect one at /user/integrations/twitter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax accounts to return (default 50, max 200).
queryNoCase-insensitive filter on name, handle, or bio.
handleNoOne connected @handle whose follows to read. Omit for all connected accounts.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

The description meaningfully extends the readOnlyHint annotation by disclosing that it reads the last sync (so recent follows may be missing), explaining that total_followed is the synced total, and giving explicit user-facing guidance for the disconnected-account case. This adds real behavioral context beyond the annotation.

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?

The description is three dense sentences with no filler. It front-loads the core purpose, then adds the sync caveat and connection fallback, all of which are necessary for correct use.

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?

For a read-only tool with no output schema, the description covers essential context: what is returned, how query filters, data freshness limitations, the meaning of total_followed, and error handling when no account is connected. The optional parameters are already documented in the schema, so nothing critical is missing.

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 the baseline is 3. The description adds a concrete query example ('who do I follow in AI?') but otherwise repeats the schema's parameter semantics. It does not substantially deepen understanding of limit or handle beyond their existing schema descriptions.

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?

The description states a specific verb ('Accounts the user follows') and resource ('synced follow graph'), and enumerates returned fields (name, @handle, bio). This clearly distinguishes it from siblings like get_twitter_profile or get_my_tweets, even without naming them explicitly.

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?

The description provides clear operational context: it reads from the last sync, explains the `query` filter usage, and instructs the agent on what to do if no account is connected. However, it does not explicitly state when not to use this tool or name alternative tools, so it falls 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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TDQS

A4/5.0
Disambiguation5/5

Each tool targets a distinct resource and action, with clear boundaries even within overlapping domains like LinkedIn (search vs. free-form query vs. profile vs. summary) and graph deletion (soft single, bulk soft, permanent single). Descriptions explicitly cross-reference related tools to prevent misselection.

Naming Consistency4/5

The vast majority follow a consistent verb_noun pattern (get_, list_, search_, create_, delete_, etc.). A few noun-phrase exceptions like linkedin_analytics, mutual_connections, similar_objects, and what_needs_attention deviate slightly, but they are still descriptive and do not create confusion.

Tool Count2/5

At 66 tools this is far beyond the 25+ threshold considered too many, even though the server covers many integration domains. Each domain has a coherent subset, but the overall surface is heavy for agents to navigate and would benefit from consolidation or namespacing.

Completeness4/5

The set provides deep read/search coverage across Gmail, Slack, Calendar, LinkedIn, HubSpot, Obsidian, Twitter, and a graph store, with core write operations for calendar, drafts, Slack, and graph objects. Minor gaps exist—notably no calendar delete, no direct Gmail send to third parties (only drafts), and no LinkedIn post/message actions—but these appear deliberate and do not block typical workflows.