memory_strategic_objective_setPropose an objective under a plan.
| Name | Required | Description | Default |
|---|---|---|---|
| agent | No | Override agent identity | |
| title | Yes | Objective title | |
| plan_id | Yes | Parent plan UUID | |
| owner_id | No | Owner UUID | |
| owner_type | No | user or agent | |
| sort_order | No | Display order | |
| 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 behavioral disclosure. It does not state whether the operation is an upsert, create, or update; whether it is idempotent; whether it requires authorization; or what side effects it has. The word 'propose' is especially ambiguous because it could imply a non-persisting suggestion rather than a concrete set operation.
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 sentence with no filler and the main subject is front-loaded. It is structurally clean and easy to parse, though it is slightly under-specified in terms of content, so it does not earn a perfect score.
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?
Given that this is a write-style tool with no annotations and seven parameters, a one-sentence description is not fully adequate. It does not explain the strategic-hierarchy context, whether the tool creates or updates, or how 'objective' relates to plan, key_result, and initiative tools. The full schema and presence of an output schema reduce some burden, but the behavioral and selection context is still incomplete.
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 the schema already documents all seven parameters, including plan_id as 'Parent plan UUID' and title as 'Objective title'. The description's 'under a plan' only re-emphasizes the same parent relationship and does not add meaningful detail beyond the schema definitions.
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 action ('propose') and a specific resource ('objective under a plan'), which is enough to roughly distinguish it from other strategic-tool siblings like plan_set, key_result_set, and initiative_set. However, 'propose' versus the tool name 'set' leaves ambiguity about whether this creates, updates, or stages an objective, and no siblings are named explicitly.
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 phrase 'under a plan' gives some contextual signal about when this tool applies, and it clearly points to the parent-child relationship captured by plan_id. But it does not explicitly state when not to use this tool or how it differs from alternatives such as memory_strategic_key_result_set or memory_strategic_initiative_set, so the usage guidance is mostly implied rather than explicit.
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.