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Glama

TeamShared

by io.github.xhad

Version

version

Report server + memory-rule version and whether the rule needs updating.

Returns {server_version, rule_version, installed_rule_version, rule_path, update_available}. When update_available is true (the installed rule is missing or behind the canonical one), the response also includes rule_markdown — write it verbatim to your rule file (Cursor: ~/.cursor/rules/teamshared.mdc) to update the user, then tell them the memory rule was updated. See the rule's "Staying current".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
installed_rule_versionNoThe `version` from your installed teamshared rule's frontmatter (e.g. the value in ~/.cursor/rules/teamshared.mdc). Omit if your rule has no version marker.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so well: it discloses the return tuple, the condition that changes the response, and the exact follow-up action required when update_available is true. It also defines what update_available means.

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 definition is front-loaded with the purpose and keeps only high-value content: return fields, the conditional update flow, and the target file path. The final reference to the rule's 'Staying current' is slightly terse but not wasteful.

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 single-optional-parameter version check, the description is complete: it names all returned fields, specifies the conditional response, and gives the agent a concrete update procedure. Nothing critical is missing for correct invocation and handling of the main outcome.

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?

The schema already documents installed_rule_version at 100% coverage, so a baseline of 3 applies. The description adds meaning by connecting this value to the update_available logic: the installed rule being 'missing or behind the canonical one' is what triggers the update payload.

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 opens with a specific verb 'Report' and a clear resource: server plus memory-rule version, including the key decision it supports: whether the rule needs updating. This distinguishes the tool from file-version and memory-action siblings.

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 implies the usage context: check installed vs canonical rule versions, and if an update is available, write the provided markdown verbatim to the rule file and inform the user. However, it does not explicitly say when to prefer this tool over alternatives or when not to call it.

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

B3.4/5.0
Disambiguation4/5

With 104 tools across many domains (memory, work, projects, files, agents, context, strategic, ontology), the use of clear prefixes (memory_, work_, project_, file_, agent_run_, context_) makes most tools distinct. However, there are some potential confusions between memory_session_* vs memory_state_*, and memory_recall vs memory_think vs memory_assemble_context, though descriptions clarify their specific purposes. Aliases like memory_playbook_get for memory_procedure_get are explicit and reduce ambiguity.

Naming Consistency5/5

Tool names follow a highly consistent pattern: prefix_domain_action (e.g., file_create, work_update, memory_recall, agent_run_start). All use snake_case, with verbs consistently placed after the domain prefix. Even less common tools like account_brief and attention_snapshot fit the overall naming scheme, making the set predictable and easy to navigate.

Tool Count3/5

At 104 tools, this is an exceptionally large surface area, far exceeding the 25+ threshold that feels heavy. However, the server covers an extensive domain (organizational memory, work management, project tracking, file sharing, agent orchestration, and strategic planning), which justifies a large count. Still, the sheer number may overwhelm agents, and some tools could be consolidated (e.g., many memory_session_* and memory_state_* variants).

Completeness4/5

The tool surface is remarkably complete for its stated purpose, covering CRUD operations for files, work items, projects, and memory, plus lifecycle management for agents, sessions, and strategic plans. Minor gaps exist (e.g., no direct memory_item_get by ID, no section removal in projects), but agents can work around these using existing tools like memory_recall or work_create with parent_id. Overall, the set minimizes dead ends.

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