memory_strategic_initiative_setPropose a strategic initiative.
| Name | Required | Description | Default |
|---|---|---|---|
| agent | No | Override agent identity | |
| title | Yes | Initiative title | |
| plan_id | Yes | Parent plan UUID | |
| objective_id | No | Aligned objective UUID | |
| key_result_id | No | Aligned key result UUID | |
| description_md | No | Optional description |
| 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?
No annotations are provided, so the description carries the full burden of disclosing behavior, but it only says 'propose'—a non-committal verb. It does not state whether the initiative is persisted, whether an existing initiative with the same title gets overwritten, or whether alignment to objective/key_result is enforced. For a mutation-style 'set' tool, this is a significant transparency gap.
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 short sentence with no fluff, so it is concise. However, it is under-specified rather than efficiently complete—at this length it fails to convey behavior or usage, so the brevity does not add value beyond stating the basic resource.
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?
The tool sits in a hierarchy of strategic-memory setters (plan, objective, key result, initiative, statement), yet the description gives no context on how an initiative relates to those entities or what 'propose' means in that workflow. With six parameters and no annotations, an agent needs more operational context to call it correctly. The presence of an output schema covers return values, but not the surrounding strategic-memory workflow.
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?
Schema description coverage is 100%, so every parameter is already documented, including plan_id as 'Parent plan UUID' and objective_id as 'Aligned objective UUID'. The description adds no parameter semantics beyond what the schema provides, so the baseline 3 applies.
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 uses a specific verb ('propose') and resource ('strategic initiative'), which is more than a tautology, but 'propose' is ambiguous—it does not clarify whether this creates, updates, or merely flags an initiative. It also does not distinguish this from sibling setters like memory_strategic_objective_set or memory_strategic_key_result_set beyond the resource name. An agent gets only a general sense of the tool's domain, not its exact operation.
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 on when to use this tool versus its siblings. No prerequisites (e.g., existence of the parent plan) or exclusions (e.g., use objective_set for objectives) are mentioned. An agent must infer usage entirely from parameter names and required fields, which is the schema's job, not the description's.
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.