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Glama

TeamShared

by io.github.xhad

Memory Skill Set

memory_skill_set

Insert a new version of a skill. Each call creates a new version.

Skills are atomic instruction building blocks. Playbooks compose them via tool_recipe.skills on memory_procedure_set. Routed through the guarded ingestion pipeline; only active skills are visible to recall and memory_skill_get.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesSkill name (stable id)
tagsNoTags for discovery
agentNoOverride agent identity
body_mdYesMarkdown body the agent will read
owner_idNoOrg member UUID. Omit inherits last owner or the writer.
tool_hintsNoOptional structured hints (preferred MCP tools, params)
descriptionNoOne-line summary
verification_daysNoVerification window: 30, 90, or 180 days; 0 for none. Omit inherits the last window.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedInput schema / properties / owner_id
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Org member UUID. Omit inherits last owner or the writer."
+}
    • addedInput schema / properties / verification_days
      Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Verification window: 30, 90, or 180 days; 0 for none. Omit inherits the last window."
+}
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden. It discloses that each call creates a new version, routes through a guarded ingestion pipeline, and only exposes active skills to recall and memory_skill_get. This is useful side-effect and visibility information, though it omits details like authentication requirements and exactly what makes a version 'active'.

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 concise sentences. The first sentence states the core action; the second gives domain context about where skills fit; the third explains pipeline and visibility. Every sentence earns its place, and there is no redundancy or fluff.

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?

The tool has full schema coverage and an output schema, so parameters and return values are handled by structured data. The description adds essential versioning and visibility context. The main gap is that 'active' status is referenced but not explained, and there is no mention of auth or ownership preconditions.

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 tool description adds no parameter-specific meaning and doesn't clarify how fields like owner_id, verification_days, or tool_hints interact with the versioning model. It therefore does not exceed the schema's parameter documentation.

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 action: 'Insert a new version of a skill' and reinforces that every call creates a new version. This clearly separates it from read/list/delete siblings such as memory_skill_get, memory_skills_list, and memory_forget_skill. The verb+resource pair is unambiguous.

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 provides implied usage context by explaining that skills are building blocks for playbooks and that only active skills are visible to recall and memory_skill_get. However, it never explicitly states when to use this tool versus alternatives, nor does it give any when-not-to-use guidance, leaving the agent to infer the write path.

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.

Resources