Lease one open task for bounded external work; expired leases reopen automatically.
| Name | Required | Description | Default |
|---|---|---|---|
| work_item_id | Yes | ||
| lease_seconds | No | ||
| idempotency_key | Yes |
| 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?
Annotations already declare it's not read-only, is idempotent, and not destructive. The description adds behavioral context beyond that: 'expired leases reopen automatically' and 'bounded external work', which clarify the lifecycle and time-bound nature without contradicting annotations. This is meaningful additional info, though it doesn't detail exclusivity or heartbeat requirements.
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, concise sentence that front-loads the primary action ('Lease one open task') and adds only one extra behavioral fact. Every word earns its place, with no fluff or redundancy.
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 is relatively simple (3 params, 1 optional) and an output schema exists, so return value explanation is unnecessary. The description covers the core action and the notable auto-reopen behavior. However, it leaves some ambiguity around 'external work' and doesn't mention whether a heartbeat is needed to maintain the lease, which would be useful for full lifecycle understanding.
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 0%, so the description must compensate for parameter semantics. It does not explain work_item_id, lease_seconds, or idempotency_key at all. The phrase 'bounded external work' vaguely hints at lease_seconds, but there is no explicit mapping. This is a significant gap given the lack of schema descriptions.
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 tool's function: to lease an open task for bounded external work. The verb 'lease' is specific (distinct from create, find, or heartbeat) and the resource is 'open task'. This distinguishes it from siblings like find_work or heartbeat_problem.
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 clear context: use when you need to claim an open task for bounded external work, with leases that expire and reopen. It does not explicitly name alternatives or when-not-to-use conditions, but the context strongly implies the scenario. Since no explicit exclusions are stated, it earns a 4 rather than 5.
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.
Each tool targets a distinct resource and action: problem lifecycle, knowledge reading/search/context, candidate submission/review, and experience verification. Even similar tools like get_knowledge, search_knowledge, and retrieve_context are clearly differentiated by their descriptions.
All tool names follow a consistent snake_case verb_noun pattern with no mixed conventions or vague verbs. Names accurately reflect their actions and objects, making the set predictable and easy to navigate.
At 16 tools, the count is slightly above the typical 3-15 range but still reasonable given the multi-faceted domain (problems, knowledge, candidates, experiences). Each tool appears to have a specific purpose, though a few could potentially be consolidated.
Core workflows are covered: create/claim/manage problems, submit/review candidates, publish/retrieve knowledge, and verify experiences. Minor gaps exist such as no explicit close/cancel operation for problems, but agents can work around these with existing tools.