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Glama

twitr.sh

by sh.twitr

x_profile

Edit a connected X/Twitter account's profile: display name, bio, location, website link, avatar image, and banner image. Acts only on handles this wallet connected.

Guidance: PREREQUISITE: connect an X account. Acts as a handle THIS wallet owns. action=update_profile (any of name, description, location, url) | set_avatar (media_url) | set_banner (media_url). account required. Payment settles before the change; Idempotency-Key required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoupdate_profile: new website URL.
nameNoupdate_profile: new display name.
actionYesWhich profile edit to make.
accountYesA connected X handle owned by this wallet (no @).
locationNoupdate_profile: new location.
media_urlNoset_avatar|set_banner: public image URL.
descriptionNoupdate_profile: new bio.

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

No annotations present, so description carries full burden. Discloses payment settlement before change, idempotency-key requirement, and how actions (update_profile, set_avatar, set_banner) work. No mention of side effects or destructive behavior beyond editing.

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?

Three clear sentences with a guidance block. Front-loaded purpose and essential details. No redundancy, but could be slightly more compact without losing completeness.

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?

Given 7 parameters, no output schema, and no annotations, the description covers prerequisites, actions, payment, and idempotency. Missing details on return values or error conditions, but acceptable for a mutation tool.

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

Parameters4/5

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

Schema coverage is 100% (baseline 3). Description adds value by grouping parameters per action, e.g., 'action=update_profile (any of name, description, location, url)' which clarifies conditional parameter usage beyond schema.

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?

Clear verb 'Edit' and specific resource 'connected X/Twitter account's profile' with explicit fields (display name, bio, location, etc.). Distinguishes from sibling tools like x_compose or x_write.

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?

Explicit prerequisite stated ('PREREQUISITE: connect an X account') and constraint ('Acts only on handles this wallet connected'). Guidance on action parameter usage provided, but no explicit when-not-to-use or alternatives mentioned.

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

A4.3/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (write, read, search, monitor, compose, etc.), but some overlaps exist: x_read includes trending topics while x_radar is dedicated to trends, and x_timeline provides engagement lists that overlap with x_extract's extractors. Descriptions help differentiate them, but an agent might initially confuse the boundary between x_read, x_search, and x_timeline for tweet retrieval.

Naming Consistency4/5

All tool names share the x_ prefix and are single words, but mix verb forms (read, search, write, compose, extract, monitor) with noun forms (draws, radar, inbox, lists, profile, timeline). The convention is predictable and uniformly lowercase, but a fully consistent verb_noun or noun-only pattern would be clearer. Minor deviation: x_communities vs x_community are nearly identical and refer to reading vs managing.

Tool Count5/5

14 tools is well within the ideal 3-15 range and each tool covers a distinct functional area of X/Twitter: reading, writing, searching, monitoring, extracting, composing, community management, etc. The count feels appropriate for the broad scope of the server, neither bloated nor thin.

Completeness5/5

The tool surface covers the major X/Twitter interactions comprehensively: fully capable read (x_read, x_search, x_timeline), write (x_write, x_profile), community and list operations, real-time monitoring, bulk extraction, direct messaging, media, trends, and even AI-assisted composition and giveaways. Obvious gaps are minimal, such as no list creation/management commands, but the core lifecycle of tweets, users, communities, and accounts is well covered.

Resources