memory_procedures_listList playbooks (latest version of each) in the caller's org.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | Filter by tag | |
| limit | No | ||
| offset | No | Pagination offset | |
| include_body | No | Include full steps_md and tool_recipe |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral disclosure, and it does add useful context: only the latest version of each playbook is returned, scoped to the caller's org. However, it does not mention read-only behavior, default body exclusion, pagination behavior, or other side effects, though the output schema mitigates some ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence with no filler. Key qualifiers like 'latest version of each' and 'caller's org' are front-loaded, and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with an output schema and mostly self-descriptive parameters, the description is adequate. However, the absence of annotations and the presence of many closely related memory tools mean the definition should clarify the procedures-versus-playbooks terminology and its relationship to list/get siblings. It is sufficient but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no per-parameter meaning beyond the input schema. Schema descriptions already cover tag, offset, and include_body, while limit is inferable from its minimum, maximum, and default. With roughly 75% schema coverage, the schema does most of the parameter-documentation work, so the description does not need to compensate much.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('List'), a concrete resource ('playbooks'), and a scope ('in the caller's org'), while adding the important qualifier 'latest version of each'. However, it does not explicitly differentiate this from sibling tools like memory_playbooks_list, and the tool name says 'procedures' while the description says 'playbooks', which introduces mild ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance about when this tool should be preferred over alternatives such as memory_playbooks_list, memory_procedure_get, or memory_playbook_get. It is a bare listing statement with no when-to-use, when-not-to-use, or alternative conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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).
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.