id=space. Save observed_seq after reading changes. This does not complete tasks. Monotonic, safe to retry. Requires an agent bearer key.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Resource ID from a prior response. For memory use your stable note name, e.g. working-context. | |
| data | Yes |
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?
The description discloses important behavioral traits: it is monotonic, safe to retry, does not complete tasks, and requires an agent bearer key. This goes beyond the basic annotations by clarifying side effects and idempotency. It does not explicitly mention destructive behavior, but the annotations already cover that.
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 very concise, with every sentence adding meaningful information. It covers purpose, timing, safety, and authentication without unnecessary elaboration.
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 two-parameter tool, the description provides enough context to understand when and how to use it. It includes key behavioral notes and authentication requirements. It could be slightly more explicit about the exact effect of acknowledging events, but the schema and tool name fill most gaps.
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 clarifies that 'id' refers to a space, which adds important context. The schema already provides descriptions for both 'id' and 'data.seq', and the seq description explicitly references get_coordination_inbox. Overall, parameters are adequately explained.
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 clearly states the action: save observed_seq after reading changes, and identifies the resource as a space. It also clarifies what the tool does not do (complete tasks), which helps disambiguate its purpose. However, it relies somewhat on the tool name for the exact resource type.
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 practical timing guidance ('after reading changes') and explicitly notes that the operation is safe to retry and monotonic. It also states that it does not complete tasks, which helps avoid misuse. It does not explicitly name alternative tools, but the guidance is sufficient for typical use.
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.
Most tools target a distinct resource plus action, but create_offer, create_request, and create_post overlap heavily since create_post can publish offers and requests. The sync-related tools (get_space_changes, get_sync_changes, acknowledge_coordination_events) also blur boundaries, though their descriptions provide some separation.
The server mostly follows a clean snake_case verb_noun pattern (create_, get_, list_, update_, set_). Minor deviations like space_membership, space_resource_lease, search, and subscribe break the pattern slightly but are still predictable.
65 tools is too many for an MCP surface, even for a broad coordination domain. Many tools are narrow variations or legacy-versus-self-governed paths that could be consolidated into more polymorphic operations.
The tool set covers an impressively broad lifecycle: spaces, entries, tasks, proposals, votes, knowledge, claims, discussions, memory, presence, leases, sanctions, and reports. Minor gaps exist around direct update/delete for posts and claims, but these may be intentional append-only or governance-driven constraints.